[CI] Discover Rust coverage artifacts from build metadata

Co-authored-by: OpenAI Codex <codex@openai.com>

.buildkite/ci_config_intel.yaml

@@ -3,6 +3,7 @@ job_dirs:
   - ".buildkite/intel_jobs"
 run_all_patterns:
   - ".buildkite/ci_config_intel.yaml"
+  - ".buildkite/scripts/hardware_ci/run-intel-test.sh"
   - "docker/Dockerfile"
   - "docker/Dockerfile.xpu"
   - "CMakeLists.txt"

.buildkite/ci_config_rocm.yaml

@@ -8,6 +8,7 @@ run_all_patterns:
   - "docker/docker-bake-rocm.hcl"
   - ".buildkite/hardware_tests/amd.yaml"
   - ".buildkite/scripts/ci-bake-rocm.sh"
+  - ".buildkite/scripts/rocm/"
   - ".buildkite/scripts/hardware_ci/run-amd-test.py"
   - ".buildkite/scripts/hardware_ci/run-amd-test.sh"
   - "CMakeLists.txt"

.buildkite/hardware_tests/amd.yaml

@@ -1,5 +1,30 @@
 group: Hardware - AMD Build
+
+# ROCm image flow:
+# 1. Refresh the long-lived ROCm base image only when Dockerfile.rocm_base changes.
+# 2. Build ci_base from either the stable base or the freshly refreshed base.
+# 3. Build the per-commit ROCm CI image and smoke-test it before GPU jobs run.
 steps:
+  - label: "AMD: :docker: refresh ROCm base"
+    key: refresh-rocm-base-amd
+    depends_on: []
+    device: amd_cpu
+    no_plugin: true
+    commands:
+      - bash .buildkite/scripts/rocm/refresh-base-image.sh
+    env:
+      DOCKER_BUILDKIT: "1"
+      BUILDKIT_PROGRESS: "tty"
+      TERM: "xterm-256color"
+    retry:
+      automatic:
+        - exit_status: 1  # Transient Docker/BuildKit failure
+          limit: 1
+        - exit_status: -1  # Agent was lost
+          limit: 1
+        - exit_status: -10  # Agent was lost
+          limit: 1
+
   # Ensure ci_base is up-to-date before building the test image.
   # Compares a content hash of ci_base-affecting files against the remote
   # image label. If hashes match the build is skipped (< 30 s); if they
@@ -7,19 +32,24 @@ steps:
   - label: "AMD: :docker: ensure ci_base"
     key: ensure-ci-base-amd
     soft_fail: false
-    depends_on: []
+    depends_on:
+      - refresh-rocm-base-amd
     device: amd_cpu
     no_plugin: true
     commands:
-      - bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
+      - bash .buildkite/scripts/rocm/build-ci-base.sh
     env:
       DOCKER_BUILDKIT: "1"
+      BUILDKIT_PROGRESS: "tty"
+      TERM: "xterm-256color"
       VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
       PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
       REMOTE_VLLM: "1"
       VLLM_BRANCH: "$BUILDKITE_COMMIT"
     retry:
       automatic:
+        - exit_status: 1  # Transient Docker/BuildKit failure
+          limit: 1
         - exit_status: -1  # Agent was lost
           limit: 1
         - exit_status: -10  # Agent was lost
@@ -33,35 +63,12 @@ steps:
     device: amd_cpu
     no_plugin: true
     commands:
-      - |
-        if [[ "${ROCM_CI_ARTIFACT_ONLY:-0}" == "1" ]]; then
-          echo "ROCM_CI_ARTIFACT_ONLY=1; building ROCm wheel artifact only"
-          IMAGE_TAG="" bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-artifacts
-        else
-          bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-wheel
-        fi
-      - |
-        docker run --rm --network=none --entrypoint /bin/bash "rocm/vllm-ci:${BUILDKITE_COMMIT}" -ec '
-          if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
-          if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
-          if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
-          if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
-          command -v python3
-          command -v uv
-          command -v pytest
-          if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
-            echo No ROCm CLI found in image >&2
-            exit 1
-          fi
-          python3 - <<PY
-        import torch, vllm
-        print(torch.__version__)
-        print(vllm.__version__)
-        PY
-          echo AMD image smoke OK
-        '
+      - bash .buildkite/scripts/rocm/build-test-image.sh
+      - bash .buildkite/scripts/rocm/smoke-test-image.sh
     env:
       DOCKER_BUILDKIT: "1"
+      BUILDKIT_PROGRESS: "tty"
+      TERM: "xterm-256color"
       VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
       PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
       IMAGE_TAG: "rocm/vllm-ci:$BUILDKITE_COMMIT"
@@ -69,6 +76,8 @@ steps:
       VLLM_BRANCH: "$BUILDKITE_COMMIT"
     retry:
       automatic:
+        - exit_status: 1  # Transient Docker/BuildKit failure
+          limit: 1
         - exit_status: -1  # Agent was lost
           limit: 1
         - exit_status: -10  # Agent was lost

.buildkite/hardware_tests/cpu.yaml

@@ -17,16 +17,22 @@ steps:
   - tests/kernels/test_awq_int4_to_int8.py
   - tests/kernels/quantization/test_cpu_fp8_scaled_mm.py
   - tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
+  - tests/kernels/mamba/test_cpu_short_conv.py
+  - tests/kernels/mamba/test_causal_conv1d.py
+  - tests/kernels/mamba/test_mamba_ssm.py
   commands:
     - |
       bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 30m "
       pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
       pytest -x -v -s tests/kernels/moe/test_cpu_fused_moe.py
       pytest -x -v -s tests/kernels/moe/test_cpu_quant_fused_moe.py
+      pytest -x -v -s tests/kernels/mamba/test_cpu_short_conv.py
       pytest -x -v -s tests/kernels/test_onednn.py
       pytest -x -v -s tests/kernels/test_awq_int4_to_int8.py
       pytest -x -v -s tests/kernels/quantization/test_cpu_fp8_scaled_mm.py
-      pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
+      pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
+      pytest -x -v -s tests/kernels/mamba/test_causal_conv1d.py
+      pytest -x -v -s tests/kernels/mamba/test_mamba_ssm.py"
 
 # Note: SDE can't be downloaded from CI host because of AWS WAF
 # - label: CPU-Compatibility Tests
@@ -139,9 +145,22 @@ steps:
   commands:
     - |
       bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
-      pytest -x -v -s tests/models/multimodal/generation --ignore=tests/models/multimodal/generation/test_pixtral.py -m cpu_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
+      pytest -x -v -s tests/models/multimodal/generation --ignore=tests/models/multimodal/generation/test_pixtral.py --ignore=tests/models/multimodal/generation/test_qwen2_5_vl.py -m cpu_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB"
   parallelism: 4
 
+- label: CPU-Qwen2.5-VL Multimodal Tests
+  depends_on: []
+  device: intel_cpu
+  no_plugin: true
+  source_file_dependencies:
+  # - vllm/
+  - vllm/model_executor/layers/rotary_embedding
+  - tests/models/multimodal/generation/
+  commands:
+    - |
+      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 40m "
+      VLLM_CI_ENV=0 pytest -x -v -s tests/models/multimodal/generation/test_qwen2_5_vl.py"
+
 - label: "Arm CPU Test"
   depends_on: []
   soft_fail: false

.buildkite/hardware_tests/intel_xpu_ci/test-intel.yaml

@@ -18,7 +18,7 @@ steps:
   - label: "XPU example Test"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 50
     optional: true
     device: intel_gpu
     agent_tags:
@@ -39,13 +39,13 @@ steps:
   - label: "XPU V1 test"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 70
     optional: true
     device: intel_gpu
     agent_tags:
       label: production
       gpu: 1+
-      mem: 16+
+      mem: 24+
     no_plugin: true
     env:
       REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -60,7 +60,7 @@ steps:
   - label: "XPU server test"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 45
     optional: true
     device: intel_gpu
     agent_tags:

.buildkite/image_build/image_build.sh

@@ -79,12 +79,18 @@ setup_buildx_builder() {
     docker buildx ls | grep -E '^\*|^NAME' || docker buildx ls
 }
 
+annotate_image_tags() {
+    .buildkite/scripts/annotate-image-build.sh \
+        "${IMAGE_TAG:-}" "${IMAGE_TAG_LATEST:-}"
+}
+
 check_and_skip_if_image_exists() {
     if [[ -n "${IMAGE_TAG:-}" ]]; then
         echo "--- :mag: Checking if image exists"
         if docker manifest inspect "${IMAGE_TAG}" >/dev/null 2>&1; then
             echo "Image already exists: ${IMAGE_TAG}"
             echo "Skipping build"
+            annotate_image_tags
             exit 0
         fi
         echo "Image not found, proceeding with build"
@@ -171,6 +177,18 @@ BRANCH=$4
 IMAGE_TAG=$5
 IMAGE_TAG_LATEST=${6:-} # only used for main branch, optional
 
+# When TORCH_NIGHTLY=1, build the base CI image against PyTorch nightly so the
+# entire existing pipeline runs on nightly torch (CUDA/GPU lane only). Delegate
+# to the dedicated nightly build (PYTORCH_NIGHTLY=1, CUDA 13.0) and tag it at the
+# normal IMAGE_TAG that every test step already pulls -- no separate image tag,
+# no duplicate "vLLM Against PyTorch Nightly" pipeline section.
+if [[ "${TORCH_NIGHTLY:-0}" == "1" ]]; then
+    echo "--- :warning: TORCH_NIGHTLY=1 -- building base image on PyTorch nightly"
+    SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+    exec "${SCRIPT_DIR}/image_build_torch_nightly.sh" \
+        "${REGISTRY}" "${REPO}" "${BUILDKITE_COMMIT}" "${BRANCH}" "${IMAGE_TAG}"
+fi
+
 # build config
 TARGET="test-ci"
 VLLM_BAKE_FILE_PATH="${VLLM_BAKE_FILE_PATH:-docker/docker-bake.hcl}"
@@ -254,3 +272,5 @@ echo "--- :docker: Building ${TARGET}"
 docker --debug buildx bake -f "${VLLM_BAKE_FILE_PATH}" -f "${CI_HCL_PATH}" --progress plain "${TARGET}"
 
 echo "--- :white_check_mark: Build complete"
+
+annotate_image_tags

.buildkite/image_build/image_build_arm64.sh

@@ -9,30 +9,31 @@ fi
 REGISTRY=$1
 REPO=$2
 BUILDKITE_COMMIT=$3
+IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-arm64"
 
 # authenticate with AWS ECR
 aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 
 # skip build if image already exists
-if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64) ]]; then
-  echo "Image not found, proceeding with build..."
-else
+if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
   echo "Image found"
-  exit 0
+else
+  echo "Image not found, proceeding with build..."
+  # build for arm64 GPU targets: Grace/GH200 (sm_90),
+  # Blackwell/Thor (sm_100/sm_103/sm_110), and DGX Spark/GB10
+  # (sm_121, family-covered by 12.0 under CUDA 13)
+  docker build --file docker/Dockerfile \
+    --platform linux/arm64 \
+    --build-arg max_jobs=16 \
+    --build-arg nvcc_threads=4 \
+    --build-arg torch_cuda_arch_list="9.0 10.0 11.0 12.0" \
+    --build-arg USE_SCCACHE=1 \
+    --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
+    --tag "$IMAGE" \
+    --target test \
+    --progress plain .
+  # push
+  docker push "$IMAGE"
 fi
 
-# build for arm64 GPU targets: Grace/GH200 (sm_90) and DGX Spark/GB10
-# (sm_121, family-covered by 12.0 under CUDA 13)
-docker build --file docker/Dockerfile \
-  --platform linux/arm64 \
-  --build-arg max_jobs=16 \
-  --build-arg nvcc_threads=4 \
-  --build-arg torch_cuda_arch_list="9.0 12.0" \
-  --build-arg USE_SCCACHE=1 \
-  --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
-  --tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64 \
-  --target test \
-  --progress plain .
-
-# push
-docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64
+.buildkite/scripts/annotate-image-build.sh "$IMAGE"

.buildkite/image_build/image_build_cpu.sh

@@ -9,26 +9,26 @@ fi
 REGISTRY=$1
 REPO=$2
 BUILDKITE_COMMIT=$3
+IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-cpu"
 
 # authenticate with AWS ECR
 aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 
 # skip build if image already exists
-if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu) ]]; then
-  echo "Image not found, proceeding with build..."
-else
+if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
   echo "Image found"
-  exit 0
+else
+  echo "Image not found, proceeding with build..."
+  # build
+  docker build --file docker/Dockerfile.cpu \
+    --build-arg max_jobs=16 \
+    --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
+    --build-arg VLLM_CPU_X86=true \
+    --tag "$IMAGE" \
+    --target vllm-test \
+    --progress plain .
+  # push
+  docker push "$IMAGE"
 fi
 
-# build
-docker build --file docker/Dockerfile.cpu \
-  --build-arg max_jobs=16 \
-  --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
-  --build-arg VLLM_CPU_X86=true \
-  --tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu \
-  --target vllm-test \
-  --progress plain .
-
-# push
-docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-cpu
+.buildkite/scripts/annotate-image-build.sh "$IMAGE"

.buildkite/image_build/image_build_cpu_arm64.sh

@@ -9,25 +9,25 @@ fi
 REGISTRY=$1
 REPO=$2
 BUILDKITE_COMMIT=$3
+IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-arm64-cpu"
 
 # authenticate with AWS ECR
 aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 
 # skip build if image already exists
-if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu) ]]; then
-  echo "Image not found, proceeding with build..."
-else
+if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
   echo "Image found"
-  exit 0
+else
+  echo "Image not found, proceeding with build..."
+  # build
+  docker build --file docker/Dockerfile.cpu \
+    --build-arg max_jobs=16 \
+    --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
+    --tag "$IMAGE" \
+    --target vllm-test \
+    --progress plain .
+  # push
+  docker push "$IMAGE"
 fi
 
-# build
-docker build --file docker/Dockerfile.cpu \
-  --build-arg max_jobs=16 \
-  --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
-  --tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu \
-  --target vllm-test \
-  --progress plain .
-
-# push
-docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-arm64-cpu
+.buildkite/scripts/annotate-image-build.sh "$IMAGE"

.buildkite/image_build/image_build_hpu.sh

@@ -9,26 +9,26 @@ fi
 REGISTRY=$1
 REPO=$2
 BUILDKITE_COMMIT=$3
+IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-hpu"
 
 # authenticate with AWS ECR
 aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 
 # skip build if image already exists
-if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu) ]]; then
-  echo "Image not found, proceeding with build..."
-else
+if docker manifest inspect "$IMAGE" >/dev/null 2>&1; then
   echo "Image found"
-  exit 0
+else
+  echo "Image not found, proceeding with build..."
+  # build
+  docker build \
+    --file tests/pytorch_ci_hud_benchmark/Dockerfile.hpu \
+    --build-arg max_jobs=16 \
+    --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
+    --tag "$IMAGE" \
+    --progress plain \
+    https://github.com/vllm-project/vllm-gaudi.git
+  # push
+  docker push "$IMAGE"
 fi
 
-# build
-docker build \
-  --file tests/pytorch_ci_hud_benchmark/Dockerfile.hpu \
-  --build-arg max_jobs=16 \
-  --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
-  --tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu \
-  --progress plain \
-  https://github.com/vllm-project/vllm-gaudi.git
-
-# push
-docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu
+.buildkite/scripts/annotate-image-build.sh "$IMAGE"

.buildkite/image_build/image_build_torch_nightly.sh

@@ -40,6 +40,7 @@ docker buildx ls
 echo "--- :mag: Checking if image already exists"
 if docker manifest inspect "$IMAGE_TAG" >/dev/null 2>&1; then
   echo "Image found: $IMAGE_TAG — skipping build"
+  .buildkite/scripts/annotate-image-build.sh "$IMAGE_TAG"
   exit 0
 fi
 echo "Image not found, proceeding with build..."
@@ -66,3 +67,5 @@ docker buildx build --file docker/Dockerfile \
   --progress plain .
 
 echo "--- :white_check_mark: Torch nightly image build complete: $IMAGE_TAG"
+
+.buildkite/scripts/annotate-image-build.sh "$IMAGE_TAG"

.buildkite/image_build/image_build_xpu.sh

@@ -9,26 +9,26 @@ fi
 REGISTRY=$1
 REPO=$2
 BUILDKITE_COMMIT=$3
+IMAGE="$REGISTRY/$REPO:$BUILDKITE_COMMIT-xpu"
 
 # authenticate with AWS ECR
 aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com || true
 
 # skip build if image already exists
-if ! docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu &> /dev/null; then
-  echo "Image not found, proceeding with build..."
-else
+if docker manifest inspect "$IMAGE" &> /dev/null; then
   echo "Image found"
-  exit 0
+else
+  echo "Image not found, proceeding with build..."
+  # build
+  docker build \
+    --file docker/Dockerfile.xpu \
+    --build-arg max_jobs=16 \
+    --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
+    --tag "$IMAGE" \
+    --progress plain .
+  # push
+  docker push "$IMAGE"
 fi
 
-# build
-docker build \
-  --file docker/Dockerfile.xpu \
-  --build-arg max_jobs=16 \
-  --build-arg buildkite_commit="$BUILDKITE_COMMIT" \
-  --tag "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu \
-  --progress plain .
-
-# push
-docker push "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-xpu
+.buildkite/scripts/annotate-image-build.sh "$IMAGE"

.buildkite/intel_jobs/basic_correctness.yaml

@@ -3,7 +3,7 @@ depends_on:
   - image-build-xpu
 steps:
 - label: XPU Sleep Mode
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: intel_gpu
   agent_tags:
     label: production
@@ -23,4 +23,5 @@ steps:
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
       export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
+      pytest -v -s basic_correctness/test_cpu_offload.py &&
       pytest -v -s basic_correctness/test_mem.py::test_end_to_end'

.buildkite/intel_jobs/lora_intel.yaml

@@ -81,10 +81,12 @@ steps:
       'cd tests &&
       export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       set -o pipefail &&
-      pytest -v -s lora/test_punica_ops.py --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype0-3-43264-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype1-1-2049-64-128-16]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-128-1-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-256-1-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-256-8-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels[expand-0-xpu:0-dtype0-3-2049-128-8-16]" --deselect="tests/lora/test_punica_ops.py::test_kernels[shrink-0-xpu:0-dtype0-1-2049-128-8-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels[expand-0-xpu:0-dtype1-1-2049-256-128-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype0-3-64256-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype1-2-29696-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype1-3-49408-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[shrink-0-xpu:0-dtype0-2-16384-32-4-4]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype0-2-51328-32-4-4]"'
+      pytest -v -s lora/test_punica_ops.py::test_kernels &&
+      pytest -v -s lora/test_punica_ops.py::test_kernels_hidden_size &&
+      pytest -v -s lora/test_punica_ops.py::test_add_lora_fused_moe_early_exit'
 
 - label: LoRA Punica FP8/XPU Ops
-  timeout_in_minutes: 45
+  timeout_in_minutes: 60
   device: intel_gpu
   agent_tags:
     label: production
@@ -128,10 +130,10 @@ steps:
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
       export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
-      (pytest -v -s lora/test_mixtral.py --deselect="tests/lora/test_mixtral.py::test_mixtral_lora[4]" || true) &&
       pytest -v -s lora/test_quant_model.py --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model0]" --deselect="tests/lora/test_quant_model.py::test_quant_model_lora[model1]" --deselect="tests/lora/test_quant_model.py::test_quant_model_tp_equality[model0]" &&
       pytest -v -s lora/test_transformers_model.py &&
       pytest -v -s lora/test_chatglm3_tp.py &&
+      pytest -v -s lora/test_llama_tp.py::test_llama_lora &&
       pytest -s -v lora/test_minicpmv_tp.py'
 
 - label: LoRA Multimodal

.buildkite/intel_jobs/misc_intel.yaml

@@ -3,7 +3,7 @@ depends_on:
   - image-build-xpu
 steps:
 - label: V1 Core + KV + Metrics
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: intel_gpu
   agent_tags:
     label: production
@@ -33,12 +33,12 @@ steps:
       pytest -v -s v1/executor'
 
 - label: V1 Sample + Logits
-  timeout_in_minutes: 30
+  timeout_in_minutes: 90
   device: intel_gpu
   agent_tags:
     label: production
     gpu: 1+
-    mem: 16+
+    mem: 24+
   no_plugin: true
   working_dir: "."
   env:
@@ -72,9 +72,31 @@ steps:
       pytest -v -s v1/test_oracle.py &&
       pytest -v -s v1/test_request.py &&
       pytest -v -s v1/test_outputs.py &&
-      pytest -v -s v1/sample/test_topk_topp_sampler.py &&
-      pytest -v -s v1/sample/test_logprobs.py &&
-      pytest -v -s v1/sample/test_logprobs_e2e.py'
+      pytest -v -s v1/sample'
+
+- label: Basic Models Tests (Initialization)
+  timeout_in_minutes: 60
+  device: intel_gpu
+  agent_tags:
+    label: production
+    gpu: 1+
+    mem: 16+
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+    - vllm/
+    - tests/models/test_initialization.py
+    - tests/models/registry.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'export VLLM_XPU_FUSED_MOE_USE_REF=1 &&
+      cd tests &&
+      pytest -v -s models/test_initialization.py::test_can_initialize_large_subset[Eagle3MiniMaxM2ForCausalLM]'
 
 - label: XPU CPU Offload
   timeout_in_minutes: 60
@@ -103,9 +125,34 @@ steps:
       pytest -v -s v1/kv_offload &&
       pytest -v -s v1/kv_connector/unit/test_offloading_connector.py'
 
+- label: NixlConnector PD accuracy (2 GPUs)
+  timeout_in_minutes: 60
+  num_devices: 2
+  device: intel_gpu
+  agent_tags:
+    label: production
+    gpu: 2+
+    mem: 16+
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
+    - vllm/v1/worker/kv_connector_model_runner_mixin.py
+    - tests/v1/kv_connector/nixl_integration/
+    - vllm/platforms/xpu.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'cd tests &&
+      bash v1/kv_connector/nixl_integration/run_xpu_disagg_accuracy_test.sh'
+
 - label: Regression
   key: regression
-  timeout_in_minutes: 30
+  timeout_in_minutes: 50
   device: intel_gpu
   agent_tags:
     label: production
@@ -133,13 +180,13 @@ steps:
   commands:
   - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install modelscope &&
+      'pip install modelscope\<1.38 &&
       cd tests &&
       pytest -v -s test_regression.py'
 
 - label: Metrics, Tracing (2 GPUs)
   key: metrics-tracing-2-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   num_devices: 2
   device: intel_gpu
   agent_tags:
@@ -175,7 +222,7 @@ steps:
 
 - label: Async Engine, Inputs, Utils, Worker
   key: async-engine-inputs-utils-worker
-  timeout_in_minutes: 30
+  timeout_in_minutes: 55
   device: intel_gpu
   agent_tags:
     label: production

.buildkite/intel_jobs/models_distributed_intel.yaml

@@ -0,0 +1,27 @@
+group: Models - Distributed
+depends_on: 
+  - image-build-xpu
+steps:
+- label: Distributed Model Tests (2 GPUs)
+  key: distributed-model-tests-2-gpus
+  timeout_in_minutes: 65
+  device: intel_gpu
+  agent_tags:
+    label: production
+    gpu: 2+
+    mem: 16+
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+  - vllm/model_executor/model_loader/sharded_state_loader.py
+  - vllm/model_executor/models/
+  - tests/model_executor/model_loader/test_sharded_state_loader.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'cd tests &&
+      pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m "not slow_test"'

.buildkite/intel_jobs/models_multimodal_intel.yaml

@@ -4,12 +4,12 @@ depends_on:
 steps:
 - label: "Multi-Modal Models (Standard) 1: qwen2"
   key: multi-modal-models-standard-1-qwen2
-  timeout_in_minutes: 45
+  timeout_in_minutes: 70
   device: intel_gpu
   agent_tags:
     label: production
     gpu: 1+
-    mem: 16+
+    mem: 24+
   no_plugin: true
   working_dir: "."
   env:
@@ -22,14 +22,14 @@ steps:
   commands:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
+      'pip install av &&
       cd tests &&
       pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2" &&
       pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model'
 
 - label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
   key: multi-modal-models-standard-2-qwen3-gemma
-  timeout_in_minutes: 45
+  timeout_in_minutes: 70
   device: intel_gpu
   agent_tags:
     label: production
@@ -47,12 +47,35 @@ steps:
   commands:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
-      cd tests &&
+      'cd tests &&
       pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model'
 
 - label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
   key: multi-modal-models-standard-3-llava-qwen2-vl
+  timeout_in_minutes: 65
+  device: intel_gpu
+  agent_tags:
+    label: production
+    gpu: 1+
+    mem: 24+
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+  - vllm/
+  - tests/models/multimodal
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'cd tests &&
+      pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma" &&
+      pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model'
+
+- label: "Multi-Modal Models (Standard) 4: other + whisper"
+  key: multi-modal-models-standard-4-other-whisper
   timeout_in_minutes: 45
   device: intel_gpu
   agent_tags:
@@ -71,43 +94,18 @@ steps:
   commands:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install git+https://github.com/TIGER-AI-Lab/Mantis.git &&
-      cd tests &&
-      pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma" &&
-      pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model'
-
-- label: "Multi-Modal Models (Standard) 4: other + whisper"
-  key: multi-modal-models-standard-4-other-whisper
-  timeout_in_minutes: 45
-  device: intel_gpu
-  agent_tags:
-    label: production
-    gpu: 1+
-    mem: 16+
-  no_plugin: true
-  working_dir: "."
-  env:
-    REGISTRY: "public.ecr.aws/q9t5s3a7"
-    REPO: "vllm-ci-test-repo"
-    VLLM_TEST_DEVICE: "xpu"
-  source_file_dependencies:
-  - vllm/
-  - tests/models/multimodal
-  commands:
-    - >-
-      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install av git+https://github.com/TIGER-AI-Lab/Mantis.git &&
+      'pip install av &&
       cd tests &&
       pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py  --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/processing'
 
 - label: Multi-Modal Processor # 44min
   key: multi-modal-processor
-  timeout_in_minutes: 45
+  timeout_in_minutes: 60
   device: intel_gpu
   agent_tags:
     label: production
     gpu: 1+
-    mem: 16+
+    mem: 24+
   no_plugin: true
   working_dir: "."
   env:
@@ -121,11 +119,9 @@ steps:
   commands:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
-      'pip install av matplotlib ftfy git+https://github.com/TIGER-AI-Lab/Mantis.git &&
+      'pip install av matplotlib ftfy &&
       pip install open-clip-torch --no-deps &&
       cd tests &&
       pytest -v -s models/multimodal/processing/test_tensor_schema.py
-      --deselect "tests/models/multimodal/processing/test_tensor_schema.py::test_model_tensor_schema[mistralai/Mistral-Large-3-675B-Instruct-2512-NVFP4]"
-      --deselect "tests/models/multimodal/processing/test_tensor_schema.py::test_model_tensor_schema[Qwen/Qwen2.5-Omni-7B-AWQ]"
       --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB'
   parallelism: 4

.buildkite/intel_jobs/quantization.yaml

@@ -0,0 +1,28 @@
+group: Quantization
+depends_on:
+  - image-build-xpu
+steps:
+- label: Quantization
+  key: quantization
+  timeout_in_minutes: 30
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  no_plugin: true
+  working_dir: "."
+  device: intel_gpu
+  agent_tags:
+    label: production
+    gpu: 1+
+    mem: 16+
+  source_file_dependencies:
+  - csrc/
+  - vllm/model_executor/layers/quantization
+  - tests/quantization
+  commands:
+  # - VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
+  - >-
+    bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+    'VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s tests/quantization/test_per_token_kv_cache.py --deselect="tests/quantization/test_per_token_kv_cache.py::test_triton_unified_attention_per_token_head_scale[int4-16-128-num_heads0-seq_lens1]"'
+

.buildkite/intel_jobs/test-intel.yaml

@@ -17,7 +17,7 @@ steps:
   - label: "XPU example Test"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 50
     device: intel_gpu
     agent_tags:
       label: production
@@ -42,21 +42,46 @@ steps:
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --kv-cache-dtype fp8 &&
         python3 examples/basic/offline_inference/generate.py --model nvidia/Llama-3.1-8B-Instruct-FP8 --block-size 64 --enforce-eager --quantization modelopt --kv-cache-dtype fp8 --attention-backend TRITON_ATTN --max-model-len 4096 &&
         python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --block-size 64 --enforce-eager --max-model-len 8192 &&
+        python3 examples/basic/offline_inference/generate.py --model TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ --block-size 64 --enforce-eager &&
         python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 &&
         python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel &&
         python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --max-model-len 8192 &&
         VLLM_XPU_FUSED_MOE_USE_REF=1 python3 examples/basic/offline_inference/generate.py --model Qwen/Qwen3-30B-A3B-Instruct-2507-FP8 --enforce-eager -tp 2 --max-model-len 8192 &&
         python3 examples/basic/offline_inference/generate.py --model INCModel/Qwen3-30B-A3B-Instruct-2507-MXFP4-LLMC --enforce-eager -tp 2 --max-model-len 8192
         '
-  - label: "XPU V1 test"
+  - label: "XPU W8A8 FP8 Linear Examples"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 60
     device: intel_gpu
     agent_tags:
       label: production
       gpu: 1+
-      mem: 16+
+      mem: 24+
+    no_plugin: true
+    env:
+      REGISTRY: "public.ecr.aws/q9t5s3a7"
+      REPO: "vllm-ci-test-repo"
+      VLLM_TEST_DEVICE: "xpu"
+    source_file_dependencies:
+      - vllm/
+      - .buildkite/intel_jobs/test-intel.yaml
+    commands:
+      - >-
+        bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+        'python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8 --enforce-eager --max-model-len 4096 &&
+        python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model neuralmagic/Llama-3.2-1B-Instruct-FP8-dynamic --enforce-eager --max-model-len 4096 &&
+        python3 examples/basic/offline_inference/generate.py --linear-backend xpu --model meta-llama/Llama-3.2-1B-Instruct --quantization fp8 --enforce-eager --max-model-len 4096
+        '
+  - label: "XPU V1 test"
+    depends_on:
+      - image-build-xpu
+    timeout_in_minutes: 70
+    device: intel_gpu
+    agent_tags:
+      label: production
+      gpu: 1+
+      mem: 24+
     no_plugin: true
     env:
       REGISTRY: "public.ecr.aws/q9t5s3a7"
@@ -68,19 +93,19 @@ steps:
       - >-
         bash .buildkite/scripts/hardware_ci/run-intel-test.sh
         'cd tests &&
-        bash v1/kv_connector/nixl_integration/run_xpu_disagg_accuracy_test.sh &&
         pytest -v -s v1/core --ignore=v1/core/test_reset_prefix_cache_e2e.py --ignore=v1/core/test_scheduler_e2e.py &&
         pytest -v -s v1/engine --ignore=v1/engine/test_output_processor.py &&
         pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py -k "not test_topk_only and not test_topp_only and not test_topk_and_topp" &&
         pytest -v -s v1/worker --ignore=v1/worker/test_gpu_model_runner.py --ignore=v1/worker/test_worker_memory_snapshot.py &&
         pytest -v -s v1/structured_output &&
         pytest -v -s v1/test_serial_utils.py &&
+        pytest -v -s v1/e2e/general/test_correctness_sliding_window.py --deselect="tests/v1/e2e/general/test_correctness_sliding_window.py::test_sliding_window_retrieval[True-1-5-google/gemma-3-1b-it]" &&
         pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py &&
         pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py'
   - label: "XPU server test"
     depends_on:
       - image-build-xpu
-    timeout_in_minutes: 30
+    timeout_in_minutes: 45
     device: intel_gpu
     agent_tags:
       label: production
@@ -120,4 +145,27 @@ steps:
       - >-
         bash .buildkite/scripts/hardware_ci/run-intel-test.sh
         'cd tests &&
-        pytest -v -s quantization/test_auto_round.py'
+        pytest -v -s quantization/test_auto_round.py'
+  - label: "XPU compressed tensors FP8 test"
+    depends_on:
+      - image-build-xpu
+    timeout_in_minutes: 60
+    device: intel_gpu
+    agent_tags:
+      label: production
+      gpu: 1+
+      mem: 16+
+    no_plugin: true
+    env:
+      REGISTRY: "public.ecr.aws/q9t5s3a7"
+      REPO: "vllm-ci-test-repo"
+      VLLM_TEST_DEVICE: "xpu"
+    source_file_dependencies:
+      - vllm/
+      - tests/quantization/test_compressed_tensors.py
+      - .buildkite/intel_jobs/test-intel.yaml
+    commands:
+      - >-
+        bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+        'cd tests &&
+        pytest -v -s quantization/test_compressed_tensors.py::test_compressed_tensors_fp8'

.buildkite/lm-eval-harness/configs/Meta-Llama-4-Maverick-17B-128E-Instruct-FP8.yaml

@@ -1,6 +1,7 @@
 # For hf script, without -t option (tensor parallel size).
 # bash .buildkite/lm-eval-harness/run-lm-eval-mmlupro-vllm-baseline.sh -m meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8 -l 250 -t 8 -f 5
 model_name: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8"
+rocm_safetensors_load_strategy: lazy
 required_gpu_arch:
   - gfx942
   - gfx950

.buildkite/lm-eval-harness/test_lm_eval_correctness.py

@@ -72,6 +72,11 @@ def launch_lm_eval(eval_config, tp_size):
     if moe_backend is not None:
         model_args += f"moe_backend={moe_backend},"
 
+    if current_platform.is_rocm():
+        rocm_load_strategy = eval_config.get("rocm_safetensors_load_strategy")
+        if rocm_load_strategy is not None:
+            model_args += f"safetensors_load_strategy={rocm_load_strategy},"
+
     env_vars = eval_config.get("env_vars", None)
     with scoped_env_vars(env_vars):
         results = lm_eval.simple_evaluate(

.buildkite/scripts/annotate-build-artifact.sh

@@ -3,7 +3,8 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 #
 # Append a build artifact line to the Buildkite annotation.
-# Usage: annotate-build-artifact.sh <label> <value>
+# Usage: annotate-build-artifact.sh <label> <value> <context>
 set -e
 echo "- **${1}**: \`${2}\`" | \
-  buildkite-agent annotate --append --style 'info' --context 'release-artifacts'
+  buildkite-agent annotate --append --style 'info' \
+    --context "${3:?context is required}"

.buildkite/scripts/annotate-image-build.sh

@@ -0,0 +1,36 @@
+#!/bin/bash
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+#
+# Append the Docker image tag(s) an image-build step pushed to a Buildkite
+# annotation, so the built image tags show up on the build page instead of
+# being buried in the job logs.
+#
+# Usage: annotate-image-build.sh <image_tag> [<image_tag> ...]
+set -euo pipefail
+
+# buildkite-agent only exists on Buildkite agents; no-op elsewhere so the
+# image build scripts stay runnable locally.
+if ! command -v buildkite-agent >/dev/null 2>&1; then
+    echo "buildkite-agent not found; skipping image tag annotation"
+    exit 0
+fi
+
+label="${BUILDKITE_LABEL:-Image build}"
+content=""
+for image in "$@"; do
+    [[ -n "$image" ]] || continue
+    content+="- **${label}**: \`${image}\`"$'\n'
+done
+
+if [[ -z "$content" ]]; then
+    echo "No image tags provided; nothing to annotate"
+    exit 0
+fi
+
+# Best-effort: a flaky annotation must never fail an otherwise successful
+# (and expensive) image build.
+if ! printf '%s' "$content" | \
+    buildkite-agent annotate --append --style 'info' --context 'docker-images'; then
+    echo "warning: failed to annotate build with image tags"
+fi

.buildkite/scripts/build-macos-wheel.sh

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+#
+# Build the macOS arm64 CPU wheel natively on a macOS agent (the `macmini`
+# queue) into artifacts/dist/ for upload-nightly-wheels.sh.
+
+set -euo pipefail
+
+# The Rust frontend build needs protoc.
+if ! command -v protoc >/dev/null 2>&1; then
+  brew install protobuf
+fi
+
+# upload-nightly-wheels.sh expects exactly one wheel.
+rm -rf artifacts/dist
+mkdir -p artifacts/dist
+
+export VLLM_TARGET_DEVICE=cpu
+export VLLM_REQUIRE_RUST_FRONTEND=1
+export MACOSX_DEPLOYMENT_TARGET=11.0
+# uv's CPython is universal2; force an arm64-only build and tag so the wheel
+# isn't mislabelled universal2 and installed on Intel Macs where import fails.
+export ARCHFLAGS="-arch arm64"
+export _PYTHON_HOST_PLATFORM="macosx-11.0-arm64"
+export CMAKE_BUILD_PARALLEL_LEVEL="${CMAKE_BUILD_PARALLEL_LEVEL:-4}"
+
+uv venv --python 3.12
+uv pip install -r requirements/build/cpu.txt --index-strategy unsafe-best-match
+uv build --wheel --no-build-isolation -o artifacts/dist
+
+ls -l artifacts/dist/*.whl

.buildkite/scripts/check-ray-compatibility.sh

@@ -29,7 +29,11 @@ if python3 -c "import torch; assert torch.version.hip" 2>/dev/null; then
         TORCH_INDEX_URL=""
     fi
 else
-    TORCH_INDEX_URL="https://download.pytorch.org/whl/cu130"
+    if [ "${TORCH_NIGHTLY:-0}" = "1" ]; then
+        TORCH_INDEX_URL="https://download.pytorch.org/whl/nightly/cu130"
+    else
+        TORCH_INDEX_URL="https://download.pytorch.org/whl/cu130"
+    fi
 fi
 echo ">>> Using PyTorch index: ${TORCH_INDEX_URL:-PyPI default}"
 

.buildkite/scripts/ci-bake-rocm.sh

@@ -15,9 +15,9 @@ set -euo pipefail
 
 DEFAULT_REPO_SLUG="vllm-project/vllm"
 DEFAULT_CI_HCL_SOURCE="docker/ci-rocm.hcl"
-DEFAULT_CI_BASE_CONTENT_FILES="requirements/common.txt requirements/rocm.txt requirements/test/rocm.txt docker/Dockerfile.rocm_base docker/ci-rocm.hcl docker/docker-bake-rocm.hcl tools/install_torchcodec_rocm.sh tests/vllm_test_utils .buildkite/scripts/ci-bake-rocm.sh"
+DEFAULT_CI_BASE_CONTENT_FILES="requirements/common.txt requirements/rocm.txt requirements/test/rocm.txt docker/Dockerfile.rocm_base docker/ci-rocm.hcl docker/docker-bake-rocm.hcl tools/install_torchcodec_rocm.sh tools/install_protoc.sh rust-toolchain.toml tests/vllm_test_utils .buildkite/scripts/ci-bake-rocm.sh .buildkite/scripts/rocm/build-ci-base.sh"
 DEFAULT_CI_BASE_DOCKERFILE="docker/Dockerfile.rocm"
-DEFAULT_CI_BASE_DOCKERFILE_STAGES="base build_rixl build_rocshmem build_deepep mori_base ci_base"
+DEFAULT_CI_BASE_DOCKERFILE_STAGES="base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust-toolchain build_rixl build_rocshmem build_deepep mori_base ci_base"
 DEFAULT_CI_BASE_METADATA_VERSION="1"
 IMAGE_EXISTED_BEFORE_BUILD=0
 
@@ -285,7 +285,7 @@ get_content_arg_names() {
     fi | awk 'NF && !seen[$0]++'
 }
 
-compute_ci_base_content_hash() {
+compute_ci_base_content_hash_once() {
     local -a content_paths=()
     local -a content_args=()
     local dockerfile="${CI_BASE_DOCKERFILE:-}"
@@ -301,7 +301,8 @@ compute_ci_base_content_hash() {
         if [[ -n "${dockerfile}" ]]; then
             printf 'dockerfile:%s\n' "${dockerfile}"
             printf 'resolved-build-args:\n'
-            hash_dockerfile_arg_values "${dockerfile}" "${content_args[@]}"
+            hash_dockerfile_arg_values "${dockerfile}" "${content_args[@]}" \
+                || return 1
             if [[ -n "${stages}" ]]; then
                 printf 'dockerfile-stages:%s\n' "${stages}"
                 if [[ -f "${dockerfile}" ]]; then
@@ -314,6 +315,53 @@ compute_ci_base_content_hash() {
     } | sha256sum | cut -d' ' -f1
 }
 
+compute_ci_base_content_hash() {
+    local attempts="${CI_BASE_HASH_ATTEMPTS:-3}"
+    local delay_secs="${CI_BASE_HASH_RETRY_DELAY:-5}"
+    local attempt=0
+    local hash=""
+    local failed=0
+    local -a hashes=()
+
+    if [[ ! "${attempts}" =~ ^[1-9][0-9]*$ ]]; then
+        echo "Invalid CI_BASE_HASH_ATTEMPTS: ${attempts}" >&2
+        return 1
+    fi
+    if [[ ! "${delay_secs}" =~ ^[0-9]+$ ]]; then
+        echo "Invalid CI_BASE_HASH_RETRY_DELAY: ${delay_secs}" >&2
+        return 1
+    fi
+
+    for ((attempt = 1; attempt <= attempts; attempt++)); do
+        if ! hash=$(compute_ci_base_content_hash_once); then
+            echo "ci_base content hash calculation ${attempt}/${attempts} failed" >&2
+            failed=1
+        else
+            hashes+=("${hash}")
+            echo "ci_base content hash calculation ${attempt}/${attempts}: ${hash}" >&2
+        fi
+
+        if ((attempt < attempts)); then
+            sleep "${delay_secs}"
+        fi
+    done
+
+    if ((failed)) || ((${#hashes[@]} != attempts)); then
+        echo "Could not calculate a reliable ci_base content hash" >&2
+        return 1
+    fi
+
+    for hash in "${hashes[@]:1}"; do
+        if [[ "${hash}" != "${hashes[0]}" ]]; then
+            echo "ci_base content hash changed between calculations" >&2
+            printf '  observed: %s\n' "${hashes[@]}" >&2
+            return 1
+        fi
+    done
+
+    printf '%s\n' "${hashes[0]}"
+}
+
 extract_dockerfile_arg_default() {
     local dockerfile="$1"
     local arg_name="$2"
@@ -366,7 +414,11 @@ hash_dockerfile_arg_values() {
         printf 'arg:%s=%s\n' "${arg_name}" "${arg_value:-<empty>}"
         if [[ "${arg_name}" == "BASE_IMAGE" && -n "${arg_value}" ]]; then
             digest=$(resolve_image_digest "${arg_value}")
-            printf 'arg:%s.digest=%s\n' "${arg_name}" "${digest:-unknown}"
+            if [[ -z "${digest}" ]]; then
+                echo "Failed to resolve digest for BASE_IMAGE=${arg_value}" >&2
+                return 1
+            fi
+            printf 'arg:%s.digest=%s\n' "${arg_name}" "${digest}"
         fi
     done
 }
@@ -393,6 +445,16 @@ should_upload_wheel_artifacts() {
         || "${TARGET}" == *"artifact"* ]]
 }
 
+set_buildkite_metadata() {
+    local key="$1"
+    local value="$2"
+
+    [[ -n "${value}" ]] || return 0
+    if command -v buildkite-agent >/dev/null 2>&1; then
+        buildkite-agent meta-data set "${key}" "${value}" || true
+    fi
+}
+
 get_remote_image_label() {
     local image_ref="$1"
     local label_key="$2"
@@ -733,6 +795,8 @@ configure_ci_base_image_refs() {
 
     if is_ci_base_target; then
         IMAGE_TAG="${primary_tag}"
+        CI_BASE_IMAGE="${primary_tag}"
+        export CI_BASE_IMAGE
         export IMAGE_TAG
 
         echo "ci_base primary image tag: ${CI_BASE_IMAGE_TAG}"
@@ -750,6 +814,10 @@ configure_ci_base_image_refs() {
             echo "ci_base stable alias will not be pushed for this build"
             echo "Set NIGHTLY=1 on ${CI_BASE_STABLE_BRANCH:-main} to refresh ${stable_tag}"
         fi
+        set_buildkite_metadata "rocm-ci-base-image" "${CI_BASE_IMAGE_TAG}"
+        set_buildkite_metadata "rocm-ci-base-image-content" "${content_tag}"
+        set_buildkite_metadata "rocm-ci-base-image-commit" "${CI_BASE_IMAGE_TAG_COMMIT_REF:-}"
+        set_buildkite_metadata "rocm-ci-base-image-stable" "${CI_BASE_IMAGE_TAG_STABLE:-}"
         return 0
     fi
 
@@ -1195,12 +1263,24 @@ uses_rocm_csrc_cache() {
     esac
 }
 
+uses_rocm_rust_cache() {
+    case "${TARGET}" in
+        rust-rocm-ci|test-rocm-ci|test-rocm-ci-with-wheel|test-rocm-ci-with-artifacts|export-wheel-rocm)
+            return 0
+            ;;
+        *)
+            return 1
+            ;;
+    esac
+}
+
 compute_rocm_csrc_content_hash() {
     local bake_dir=""
     local dockerfile_rocm=""
     local -a content_paths=(
         "requirements/common.txt"
         "requirements/rocm.txt"
+        "pyproject.toml"
         "setup.py"
         "CMakeLists.txt"
         "cmake"
@@ -1244,6 +1324,56 @@ compute_rocm_csrc_content_hash_if_needed() {
     echo "ROCm csrc content cache ref: ${ROCM_CSRC_CONTENT_CACHE_REF}"
 }
 
+compute_rocm_rust_content_hash() {
+    local bake_dir=""
+    local dockerfile_rocm=""
+    local -a content_paths=(
+        "requirements/build/rust.txt"
+        "rust/Cargo.lock"
+        "rust/Cargo.toml"
+        "rust/proto"
+        "rust/src"
+        "rust-toolchain.toml"
+        "tools/build_rust.py"
+        "tools/install_protoc.sh"
+        "build_rust.sh"
+    )
+    local -a content_args=()
+
+    bake_dir=$(dirname "${VLLM_BAKE_FILE}")
+    dockerfile_rocm="${bake_dir}/Dockerfile.rocm"
+    mapfile -t content_args < <(
+        get_content_arg_names "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build" "${ROCM_RUST_CONTENT_ARGS:-}"
+    )
+
+    {
+        printf 'rust-input-files-hash:%s\n' "$(compute_content_hash "${content_paths[@]}")"
+        printf 'dockerfile:%s\n' "${dockerfile_rocm}"
+        printf 'resolved-build-args:\n'
+        hash_dockerfile_arg_values "${dockerfile_rocm}" "${content_args[@]}"
+        printf 'dockerfile-stages:base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build\n'
+        if [[ -f "${dockerfile_rocm}" ]]; then
+            hash_dockerfile_stages "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build"
+        else
+            printf 'missing:%s\n' "${dockerfile_rocm}"
+        fi
+    } | sha256sum | cut -d' ' -f1
+}
+
+compute_rocm_rust_content_hash_if_needed() {
+    local cache_repo="${DOCKERHUB_CACHE_REPO:-rocm/vllm-ci-cache}"
+
+    if [[ "${ROCM_RUST_CONTENT_CACHE:-1}" == "0" ]] || ! uses_rocm_rust_cache; then
+        return 0
+    fi
+
+    ROCM_RUST_CONTENT_HASH=$(compute_rocm_rust_content_hash)
+    ROCM_RUST_CONTENT_CACHE_REF="${cache_repo}:rust-rocm-input-${ROCM_RUST_CONTENT_HASH}"
+    export ROCM_RUST_CONTENT_HASH
+    export ROCM_RUST_CONTENT_CACHE_REF
+    echo "ROCm Rust content cache ref: ${ROCM_RUST_CONTENT_CACHE_REF}"
+}
+
 write_hcl_string_list_entries() {
     local indent="$1"
     local value=""
@@ -1301,6 +1431,7 @@ write_rocm_build_arg_override() {
                 "${CI_BASE_DOCKERFILE_STAGES:-${DEFAULT_CI_BASE_DOCKERFILE_STAGES}}" \
                 "${CI_BASE_CONTENT_ARGS:-}"
             get_content_arg_names "${dockerfile_rocm}" "base csrc-build" "${ROCM_CSRC_CONTENT_ARGS:-}"
+            get_content_arg_names "${dockerfile_rocm}" "base rust_toolchain_input_0 rust_toolchain_input_1 rust-toolchain-input rust_input_0 rust_input_1 rust-input rust-toolchain rust-build" "${ROCM_RUST_CONTENT_ARGS:-}"
         } | awk 'NF && !seen[$0]++'
     )
 
@@ -1349,46 +1480,133 @@ validate_cache_export_mode() {
     esac
 }
 
+validate_content_cache_export_mode() {
+    local mode="$1"
+    local env_name="$2"
+
+    case "${mode}" in
+        missing|always|never)
+            ;;
+        *)
+            echo "Error: ${env_name} must be one of: missing, always, never"
+            exit 1
+            ;;
+    esac
+}
+
+should_export_content_cache_ref() {
+    local cache_ref="$1"
+    local cache_name="$2"
+    local mode="${ROCM_CONTENT_CACHE_EXPORT_MODE:-missing}"
+
+    case "${mode}" in
+        always)
+            echo "${cache_name} content cache export mode is always; exporting ${cache_ref}"
+            return 0
+            ;;
+        never)
+            echo "${cache_name} content cache export mode is never; not exporting ${cache_ref}"
+            return 1
+            ;;
+        missing|"")
+            if docker buildx imagetools inspect "${cache_ref}" >/dev/null 2>&1; then
+                echo "${cache_name} content cache exists; not re-exporting ${cache_ref}"
+                return 1
+            fi
+            echo "${cache_name} content cache missing; will export ${cache_ref}"
+            return 0
+            ;;
+        *)
+            echo "Error: ROCM_CONTENT_CACHE_EXPORT_MODE must be one of: missing, always, never"
+            exit 1
+            ;;
+    esac
+}
+
 write_rocm_cache_override() {
     local cache_repo="${DOCKERHUB_CACHE_REPO:-rocm/vllm-ci-cache}"
+    local content_cache_export_mode="${ROCM_CONTENT_CACHE_EXPORT_MODE:-missing}"
     local csrc_cache_to_mode="${ROCM_CSRC_CACHE_TO_MODE:-max}"
+    local rust_cache_to_mode="${ROCM_RUST_CACHE_TO_MODE:-max}"
     local rocm_cache_to_mode="${ROCM_FINAL_CACHE_TO_MODE:-min}"
-    local -a content_cache_from=()
+    local -a csrc_content_cache_from=()
+    local -a rust_content_cache_from=()
+    local -a combined_content_cache_from=()
     local -a csrc_cache_to=()
+    local -a rust_cache_to=()
     local -a rocm_cache_to=()
     local -a export_wheel_cache_to=()
+    local export_csrc_cache=1
+    local export_rust_cache=1
 
-    if ! uses_rocm_csrc_cache; then
+    if ! uses_rocm_csrc_cache && ! uses_rocm_rust_cache; then
         return 0
     fi
 
+    validate_content_cache_export_mode \
+        "${content_cache_export_mode}" \
+        "ROCM_CONTENT_CACHE_EXPORT_MODE"
     validate_cache_export_mode "${csrc_cache_to_mode}" "ROCM_CSRC_CACHE_TO_MODE"
+    validate_cache_export_mode "${rust_cache_to_mode}" "ROCM_RUST_CACHE_TO_MODE"
     validate_cache_export_mode "${rocm_cache_to_mode}" "ROCM_FINAL_CACHE_TO_MODE"
+    echo "ROCm content cache export mode: ${content_cache_export_mode}"
     echo "ROCm csrc cache export mode: ${csrc_cache_to_mode}"
+    echo "ROCm Rust cache export mode: ${rust_cache_to_mode}"
     echo "ROCm final image cache export mode: ${rocm_cache_to_mode}"
 
     if [[ -n "${ROCM_CSRC_CONTENT_CACHE_REF:-}" ]]; then
-        content_cache_from+=("type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF}")
-        csrc_cache_to+=(
-            "type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF},mode=${csrc_cache_to_mode},ignore-error=true"
-        )
+        csrc_content_cache_from+=("type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF}")
+        if should_export_content_cache_ref "${ROCM_CSRC_CONTENT_CACHE_REF}" "ROCm csrc"; then
+            csrc_cache_to+=(
+                "type=registry,ref=${ROCM_CSRC_CONTENT_CACHE_REF},mode=${csrc_cache_to_mode},ignore-error=true"
+            )
+        else
+            export_csrc_cache=0
+        fi
     fi
 
+    if [[ -n "${ROCM_RUST_CONTENT_CACHE_REF:-}" ]]; then
+        rust_content_cache_from+=("type=registry,ref=${ROCM_RUST_CONTENT_CACHE_REF}")
+        if should_export_content_cache_ref "${ROCM_RUST_CONTENT_CACHE_REF}" "ROCm Rust"; then
+            rust_cache_to+=(
+                "type=registry,ref=${ROCM_RUST_CONTENT_CACHE_REF},mode=${rust_cache_to_mode},ignore-error=true"
+            )
+        else
+            export_rust_cache=0
+        fi
+    fi
+
+    combined_content_cache_from=("${csrc_content_cache_from[@]}" "${rust_content_cache_from[@]}")
+
     # Docker Hub cache exports are best-effort. A cache-only target failure can
     # otherwise cancel the sibling image target before its manifest is pushed.
     if [[ -n "${BUILDKITE_COMMIT:-}" ]]; then
-        csrc_cache_to+=(
-            "type=registry,ref=${cache_repo}:csrc-rocm-${BUILDKITE_COMMIT},mode=${csrc_cache_to_mode},ignore-error=true"
-        )
+        if [[ ${export_csrc_cache} -eq 1 ]]; then
+            csrc_cache_to+=(
+                "type=registry,ref=${cache_repo}:csrc-rocm-${BUILDKITE_COMMIT},mode=${csrc_cache_to_mode},ignore-error=true"
+            )
+        fi
+        if [[ ${export_rust_cache} -eq 1 ]]; then
+            rust_cache_to+=(
+                "type=registry,ref=${cache_repo}:rust-rocm-${BUILDKITE_COMMIT},mode=${rust_cache_to_mode},ignore-error=true"
+            )
+        fi
         rocm_cache_to+=(
             "type=registry,ref=${cache_repo}:rocm-${BUILDKITE_COMMIT},mode=${rocm_cache_to_mode},ignore-error=true"
         )
     fi
 
     if [[ -n "${ROCM_CACHE_BRANCH_TAG:-}" ]]; then
-        csrc_cache_to+=(
-            "type=registry,ref=${cache_repo}:csrc-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${csrc_cache_to_mode},ignore-error=true"
-        )
+        if [[ ${export_csrc_cache} -eq 1 ]]; then
+            csrc_cache_to+=(
+                "type=registry,ref=${cache_repo}:csrc-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${csrc_cache_to_mode},ignore-error=true"
+            )
+        fi
+        if [[ ${export_rust_cache} -eq 1 ]]; then
+            rust_cache_to+=(
+                "type=registry,ref=${cache_repo}:rust-rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${rust_cache_to_mode},ignore-error=true"
+            )
+        fi
         rocm_cache_to+=(
             "type=registry,ref=${cache_repo}:rocm-branch-${ROCM_CACHE_BRANCH_TAG},mode=${rocm_cache_to_mode},ignore-error=true"
         )
@@ -1406,7 +1624,7 @@ target "csrc-rocm-ci" {
   cache-from = concat(
     get_cache_from_rocm_csrc(),
 EOF
-        write_hcl_string_list "    " "${content_cache_from[@]}"
+        write_hcl_string_list "    " "${csrc_content_cache_from[@]}"
         cat <<EOF
   )
 EOF
@@ -1414,11 +1632,23 @@ EOF
         cat <<EOF
 }
 
+target "rust-rocm-ci" {
+  cache-from = concat(
+    get_cache_from_rocm_rust(),
+EOF
+        write_hcl_string_list "    " "${rust_content_cache_from[@]}"
+        cat <<EOF
+  )
+EOF
+        write_hcl_string_list_attr "  " "cache-to" "${rust_cache_to[@]}"
+        cat <<EOF
+}
+
 target "test-rocm-ci" {
   cache-from = concat(
     get_cache_from_rocm(),
 EOF
-        write_hcl_string_list "    " "${content_cache_from[@]}"
+        write_hcl_string_list "    " "${combined_content_cache_from[@]}"
         cat <<EOF
   )
 EOF
@@ -1430,7 +1660,7 @@ target "export-wheel-rocm" {
   cache-from = concat(
     get_cache_from_rocm(),
 EOF
-        write_hcl_string_list "    " "${content_cache_from[@]}"
+        write_hcl_string_list "    " "${combined_content_cache_from[@]}"
         cat <<EOF
   )
 EOF
@@ -1720,8 +1950,8 @@ confirm_remote_image_push() {
         fi
 
         if [[ -z "${remote_revision}" \
-              && ${IMAGE_EXISTED_BEFORE_BUILD} -eq 0 \
-              && image_tag_is_commit_scoped ]]; then
+              && ${IMAGE_EXISTED_BEFORE_BUILD} -eq 0 ]] \
+            && image_tag_is_commit_scoped; then
             echo "Remote image exists under a commit-scoped tag; accepting push despite missing revision label."
             return 0
         fi
@@ -1779,7 +2009,10 @@ seed_dependency_caches_if_needed() {
 
         echo "--- :docker: Seeding ${target}"
         echo "Expected cache ref: ${cache_ref}"
-        docker buildx bake "${BAKE_FILES[@]}" --progress plain "${target}"
+        docker buildx bake \
+            "${BAKE_FILES[@]}" \
+            --progress "${BUILDKIT_PROGRESS:-plain}" \
+            "${target}"
         verify_dependency_cache_ref "${cache_ref}"
     done
 }
@@ -1807,7 +2040,10 @@ run_bake() {
     local build_rc=0
 
     echo "--- :docker: Building ${TARGET}"
-    docker buildx bake "${BAKE_FILES[@]}" --progress plain "${BAKE_TARGETS[@]}" || build_rc=$?
+    docker buildx bake \
+        "${BAKE_FILES[@]}" \
+        --progress "${BUILDKIT_PROGRESS:-plain}" \
+        "${BAKE_TARGETS[@]}" || build_rc=$?
 
     if [[ ${build_rc} -eq 0 ]]; then
         echo "--- :white_check_mark: Build complete"
@@ -1845,36 +2081,57 @@ upload_wheel_artifacts_if_present() {
     local wheel_dir="./wheel-export"
     local artifact_dir="artifacts/vllm-rocm-install"
     local archive_name="vllm-rocm-install.tar.gz"
+    local metadata_dir="${wheel_dir}/.vllm-ci-artifact"
+    local native_base_image=""
     local whl=""
     local whl_name=""
+    local -a wheels=()
 
     if ! should_upload_wheel_artifacts; then
         return 0
     fi
 
-    if [[ ! -d "${wheel_dir}" ]] || ! ls "${wheel_dir}"/*.whl >/dev/null 2>&1; then
-        echo "No ROCm wheel artifacts found in ${wheel_dir}"
-        return 0
+    if [[ -d "${wheel_dir}" ]]; then
+        mapfile -t wheels < <(find "${wheel_dir}" -maxdepth 1 -type f -name '*.whl' -print)
+    fi
+    if [[ ${#wheels[@]} -ne 1 ]]; then
+        echo "Expected exactly one ROCm wheel in ${wheel_dir}; found ${#wheels[@]}" >&2
+        return 1
+    fi
+    whl="${wheels[0]}"
+    whl_name=$(basename "${whl}")
+    native_base_image="${CI_BASE_IMAGE_TAG_COMMIT_REF:-${CI_BASE_IMAGE:-}}"
+    if [[ -z "${native_base_image}" ]]; then
+        echo "Native ROCm artifact requires a ci_base image reference" >&2
+        return 1
     fi
 
     echo "--- :package: Uploading ROCm vLLM install artifact"
-    mkdir -p "${artifact_dir}"
+    rm -rf "${artifact_dir}" "${metadata_dir}"
+    mkdir -p "${artifact_dir}" "${metadata_dir}"
+
+    printf '%s\n' "${BUILDKITE_COMMIT:-local}" > "${metadata_dir}/commit.txt"
+    printf '%s\n' "${native_base_image}" > "${metadata_dir}/native-base-image.txt"
+    printf '%s\n' "${CI_BASE_IMAGE:-}" > "${metadata_dir}/ci-base-image.txt"
+    printf '%s\n' "${IMAGE_TAG:-}" > "${metadata_dir}/fallback-image.txt"
+    printf '%s\n' "${whl_name}" > "${metadata_dir}/wheel-filename.txt"
 
     tar -C "${wheel_dir}" -czf "${artifact_dir}/${archive_name}" .
+    (
+        cd "${artifact_dir}"
+        sha256sum "${archive_name}" > "${archive_name}.sha256"
+    )
     echo "Created ${archive_name}: $(du -sh "${artifact_dir}/${archive_name}" | cut -f1)"
-    printf '%s\n' "${CI_BASE_IMAGE:-}" > "${artifact_dir}/ci-base-image.txt"
-    printf '%s\n' "${IMAGE_TAG:-}" > "${artifact_dir}/fallback-image.txt"
-
-    for whl in "${wheel_dir}"/*.whl; do
-        [[ -f "${whl}" ]] || continue
-        whl_name=$(basename "${whl}")
-        cp "${whl}" "${artifact_dir}/${whl_name}"
-        echo "Copied ${whl_name}: $(du -sh "${artifact_dir}/${whl_name}" | cut -f1)"
-    done
+    cp "${metadata_dir}"/*.txt "${artifact_dir}/"
+    cp "${whl}" "${artifact_dir}/${whl_name}"
+    echo "Copied ${whl_name}: $(du -sh "${artifact_dir}/${whl_name}" | cut -f1)"
 
     if command -v buildkite-agent >/dev/null 2>&1; then
-        buildkite-agent artifact upload "${artifact_dir}/*"
+        buildkite-agent artifact upload "${artifact_dir}/*" || return 1
         echo "ROCm vLLM install artifacts uploaded to ${artifact_dir}/"
+    elif [[ "${BUILDKITE:-false}" == "true" ]]; then
+        echo "buildkite-agent not found; cannot upload required ROCm artifacts" >&2
+        return 1
     else
         echo "Not in Buildkite, skipping artifact upload"
     fi
@@ -1898,6 +2155,7 @@ main() {
     compute_dependency_cache_keys
     write_ci_base_label_override
     compute_rocm_csrc_content_hash_if_needed
+    compute_rocm_rust_content_hash_if_needed
     write_rocm_cache_override
     resolve_ci_base_dependency_targets
     print_bake_config
@@ -1905,6 +2163,11 @@ main() {
         echo "BAKE_PRINT_ONLY=1 set; skipping build"
         return 0
     fi
+    if should_upload_wheel_artifacts; then
+        # wheel-export is an output directory, not a BuildKit cache. Starting
+        # clean prevents a failed/retried export from packaging a stale wheel.
+        rm -rf ./wheel-export
+    fi
     seed_dependency_caches_if_needed
     run_bake
     upload_wheel_artifacts_if_present

.buildkite/scripts/generate-and-upload-nightly-index.sh

@@ -45,8 +45,10 @@ $PYTHON .buildkite/scripts/generate-nightly-index.py --version "$SUBPATH" --curr
 echo "Uploading indices to $S3_COMMIT_PREFIX"
 aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "$S3_COMMIT_PREFIX"
 
-# copy to /nightly/ only if it is on the main branch and not a PR
-if [[ "$BUILDKITE_BRANCH" == "main" && "$BUILDKITE_PULL_REQUEST" == "false" ]]; then
+# copy to /nightly/ only when enabled for a main branch build that is not a PR
+if [[ "${UPDATE_NIGHTLY_INDEX:-1}" == "1" && \
+      "$BUILDKITE_BRANCH" == "main" && \
+      "$BUILDKITE_PULL_REQUEST" == "false" ]]; then
     echo "Uploading indices to overwrite /nightly/"
     aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "s3://$BUCKET/nightly/"
 fi
@@ -67,7 +69,7 @@ pure_version="${version%%+*}"
 echo "Pure version (without variant): $pure_version"
 
 # re-generate and copy to /<pure_version>/ only if it does not have "dev" in the version
-if [[ "$version" != *"dev"* ]]; then
+if [[ "${UPDATE_VERSION_INDEX:-1}" == "1" && "$version" != *"dev"* ]]; then
     echo "Re-generating indices for /$pure_version/"
     rm -rf "${INDICES_OUTPUT_DIR:?}"
     mkdir -p "$INDICES_OUTPUT_DIR"

.buildkite/scripts/hardware_ci/run-amd-test.sh

@@ -1,7 +1,7 @@
 #!/bin/bash
 
-# This script runs tests inside the corresponding ROCm docker container.
-# It handles both single-node and multi-node test configurations.
+# This script runs ROCm tests either directly in a native CI pod or inside the
+# corresponding Docker container. Multi-node tests continue to use Docker.
 #
 # Multi-node detection: Instead of matching on fragile group names, we detect
 # multi-node jobs structurally by looking for the bracket command syntax
@@ -28,6 +28,34 @@
 ###############################################################################
 set -o pipefail
 
+: "${BUILDKIT_PROGRESS:=plain}"
+: "${TERM:=xterm-256color}"
+: "${FORCE_COLOR:=1}"
+: "${CLICOLOR_FORCE:=1}"
+: "${PY_COLORS:=1}"
+: "${ROCM_DOCKER_TTY:=1}"
+: "${PYTHONFAULTHANDLER:=1}"
+: "${PYTEST_TIMEOUT:=2100}"
+if [[ " ${PYTEST_ADDOPTS:-} " != *" --color"* ]]; then
+  PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--color=yes"
+fi
+if [[ " ${PYTEST_ADDOPTS:-} " != *" --durations="* ]]; then
+  PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--durations=25"
+fi
+if [[ " ${PYTEST_ADDOPTS:-} " != *" --durations-min="* ]]; then
+  PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--durations-min=1.0"
+fi
+# Dump stacks after 15 minutes, then stop an individual test after 35 minutes.
+if [[ " ${PYTEST_ADDOPTS:-} " != *" faulthandler_timeout="* ]]; then
+  PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }-o faulthandler_timeout=900"
+fi
+if [[ " ${PYTEST_ADDOPTS:-} " != *" --timeout-method="* &&
+  " ${PYTEST_ADDOPTS:-} " != *" --timeout-method "* ]]; then
+  PYTEST_ADDOPTS="${PYTEST_ADDOPTS:+${PYTEST_ADDOPTS} }--timeout-method=thread"
+fi
+export BUILDKIT_PROGRESS TERM FORCE_COLOR CLICOLOR_FORCE PY_COLORS PYTEST_ADDOPTS PYTEST_TIMEOUT ROCM_DOCKER_TTY
+export PYTHONFAULTHANDLER
+
 # Export Python path for commands that run directly on the host. Containerized
 # tests set this to /vllm-workspace below so spawned Python processes do not
 # depend on their current working directory.
@@ -42,6 +70,28 @@ report_docker_usage() {
   docker system df || true
 }
 
+clear_ci_orchestration_env() {
+  unset -v \
+    VLLM_TEST_GROUP_NAME \
+    VLLM_CI_REQUIRE_PERSISTENT_HF_CACHE \
+    VLLM_CI_ARTIFACT_STEP \
+    VLLM_TEST_CACHE \
+    VLLM_CI_EXECUTION_MODE \
+    VLLM_CI_WORKSPACE \
+    VLLM_CI_REQUIRE_WORKSPACE_MOUNT \
+    VLLM_TEST_COMMANDS \
+    VLLM_CI_BRANCH \
+    VLLM_CI_BASE_IMAGE \
+    VLLM_CI_FALLBACK_IMAGE \
+    VLLM_CI_DOCKER_DISABLED \
+    VLLM_CI_ARTIFACT_GLOB \
+    VLLM_CI_ARTIFACT_CHECKSUM_GLOB \
+    VLLM_CI_EXPECTED_GPU_COUNT \
+    VLLM_CI_USE_ARTIFACTS \
+    VLLM_CI_RESULTS_ROOT \
+    VLLM_ALLOW_DEPRECATED_BEAM_SEARCH
+}
+
 cleanup_network() {
   local max_nodes=${NUM_NODES:-2}
   for node in $(seq 0 $((max_nodes - 1))); do
@@ -134,7 +184,11 @@ prepare_artifact_image() {
   fi
 
   cp "${wheel_dir}"/*.whl "${context_dir}/wheels/" || return 1
-  tar -C "${wheel_dir}" --exclude='*.whl' -cf - . \
+  tar -C "${wheel_dir}" \
+    --exclude='*.whl' \
+    --exclude='.vllm-ci-artifact' \
+    --exclude='./.vllm-ci-artifact' \
+    -cf - . \
     | tar -C "${workspace_dir}" -xf - || return 1
   cat > "${context_dir}/Dockerfile" <<'EOF'
 ARG BASE_IMAGE
@@ -149,6 +203,7 @@ EOF
   echo "--- Building local ROCm test image"
   docker build \
     --pull=false \
+    --progress "${BUILDKIT_PROGRESS}" \
     --build-arg "BASE_IMAGE=${base_image}" \
     -t "${artifact_image}" \
     "${context_dir}" || return 1
@@ -156,6 +211,257 @@ EOF
   return 0
 }
 
+is_native_runtime() {
+  [[ "${AMD_CI_RUNTIME:-}" == "native" || "${NATIVE_CI:-}" == "true" ]]
+}
+
+validate_native_workspace() {
+  local workspace_dir="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
+  local workspace_real=""
+  local checkout_real=""
+  local workspace_mount=""
+
+  mkdir -p "${workspace_dir}" || return 1
+  workspace_real=$(readlink -m "${workspace_dir}") || return 1
+  if [[ -n "${BUILDKITE_BUILD_CHECKOUT_PATH:-}" ]]; then
+    checkout_real=$(readlink -m "${BUILDKITE_BUILD_CHECKOUT_PATH}") || return 1
+    if [[ "${checkout_real}" == "${workspace_real}" \
+      || "${checkout_real}" == "${workspace_real}/"* \
+      || "${workspace_real}" == "${checkout_real}/"* ]]; then
+      echo "Refusing to replace ${workspace_real}; it overlaps the Buildkite checkout ${checkout_real}" >&2
+      return 1
+    fi
+  fi
+  if [[ "${VLLM_CI_REQUIRE_WORKSPACE_MOUNT:-1}" == "1" ]]; then
+    if ! command -v findmnt >/dev/null 2>&1; then
+      echo "findmnt is required to verify the native workspace mount" >&2
+      return 1
+    fi
+    workspace_mount=$(findmnt -n -T "${workspace_real}" -o TARGET 2>/dev/null || true)
+    if [[ "$(readlink -m "${workspace_mount:-/}")" != "${workspace_real}" ]]; then
+      echo "Native CI requires a dedicated volume mounted at ${workspace_real}" >&2
+      return 1
+    fi
+  fi
+}
+
+prepare_native_workspace() {
+  if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" != "1" ]]; then
+    echo "Native CI requires VLLM_CI_USE_ARTIFACTS=1"
+    return 1
+  fi
+  if ! command -v buildkite-agent >/dev/null 2>&1; then
+    echo "buildkite-agent not found; cannot download ROCm wheel artifact"
+    return 1
+  fi
+  validate_native_workspace || return 1
+
+  local artifact_glob="${VLLM_CI_ARTIFACT_GLOB:-artifacts/vllm-rocm-install/vllm-rocm-install.tar.gz}"
+  local artifact_checksum_glob="${VLLM_CI_ARTIFACT_CHECKSUM_GLOB:-${artifact_glob}.sha256}"
+  local artifact_step="${VLLM_CI_ARTIFACT_STEP:-image-build-amd}"
+  local archive=""
+  local checksum=""
+  local download_dir=""
+  local metadata_dir=""
+  local recorded_base=""
+  local recorded_commit=""
+  local recorded_wheel=""
+  local workspace_dir="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
+  local wheel_dir=""
+  local attempt=0
+  local attempt_dir=""
+  local -a archives=()
+  local -a checksums=()
+  local -a wheels=()
+
+  artifact_work_dir=$(mktemp -d -t vllm-rocm-artifact.XXXXXX) || return 1
+  wheel_dir="${artifact_work_dir}/wheels"
+  mkdir -p "${wheel_dir}" || return 1
+
+  echo "--- Downloading ROCm wheel artifact from ${artifact_step} (native in-pod)"
+  for attempt in 1 2 3; do
+    attempt_dir="${artifact_work_dir}/download-${attempt}"
+    rm -rf "${attempt_dir}" || return 1
+    mkdir -p "${attempt_dir}" || return 1
+    if buildkite-agent artifact download \
+      "${artifact_glob}" "${attempt_dir}" --step "${artifact_step}" \
+      && buildkite-agent artifact download \
+        "${artifact_checksum_glob}" "${attempt_dir}" --step "${artifact_step}"; then
+      download_dir="${attempt_dir}"
+      break
+    fi
+    echo "Artifact download attempt ${attempt}/3 failed"
+    if [[ "${attempt}" -lt 3 ]]; then
+      sleep $((attempt * 2))
+    fi
+  done
+  if [[ -z "${download_dir}" ]]; then
+    echo "Failed to download ${artifact_glob} and ${artifact_checksum_glob} from ${artifact_step}"
+    return 1
+  fi
+
+  mapfile -t archives < <(
+    find "${download_dir}" -name "vllm-rocm-install.tar.gz" -type f -print
+  )
+  mapfile -t checksums < <(
+    find "${download_dir}" -name "vllm-rocm-install.tar.gz.sha256" -type f -print
+  )
+  if [[ ${#archives[@]} -ne 1 || ${#checksums[@]} -ne 1 ]]; then
+    echo "Expected exactly one ROCm archive and checksum; found ${#archives[@]} archive(s) and ${#checksums[@]} checksum(s)" >&2
+    return 1
+  fi
+  archive="${archives[0]}"
+  checksum="${checksums[0]}"
+  if [[ "$(dirname "${archive}")" != "$(dirname "${checksum}")" ]]; then
+    echo "ROCm archive and checksum were downloaded to different directories" >&2
+    return 1
+  fi
+  (
+    cd "$(dirname "${archive}")"
+    sha256sum -c "$(basename "${checksum}")"
+  ) || return 1
+
+  tar --no-same-owner -xzf "${archive}" -C "${wheel_dir}" || return 1
+  mapfile -t wheels < <(
+    find "${wheel_dir}" -maxdepth 1 -type f -name '*.whl' -print
+  )
+  if [[ ${#wheels[@]} -ne 1 ]]; then
+    echo "ROCm artifact must contain exactly one top-level wheel; found ${#wheels[@]}" >&2
+    return 1
+  fi
+  metadata_dir="${wheel_dir}/.vllm-ci-artifact"
+  for metadata_file in commit.txt native-base-image.txt wheel-filename.txt; do
+    if [[ ! -s "${metadata_dir}/${metadata_file}" ]]; then
+      echo "ROCm artifact metadata is missing ${metadata_file}" >&2
+      return 1
+    fi
+  done
+  for metadata_file in ci-base-image.txt fallback-image.txt; do
+    if [[ ! -f "${metadata_dir}/${metadata_file}" ]]; then
+      echo "ROCm artifact metadata is missing ${metadata_file}" >&2
+      return 1
+    fi
+  done
+
+  recorded_commit=$(tr -d '\r\n' < "${metadata_dir}/commit.txt")
+  recorded_base=$(tr -d '\r\n' < "${metadata_dir}/native-base-image.txt")
+  recorded_wheel=$(tr -d '\r\n' < "${metadata_dir}/wheel-filename.txt")
+  if [[ -z "${BUILDKITE_COMMIT:-}" || "${recorded_commit}" != "${BUILDKITE_COMMIT}" ]]; then
+    echo "ROCm artifact commit ${recorded_commit} does not match ${BUILDKITE_COMMIT:-unset}" >&2
+    return 1
+  fi
+  if [[ -z "${VLLM_CI_BASE_IMAGE:-}" || "${recorded_base}" != "${VLLM_CI_BASE_IMAGE}" ]]; then
+    echo "ROCm artifact base ${recorded_base} does not match ${VLLM_CI_BASE_IMAGE:-unset}" >&2
+    return 1
+  fi
+  if [[ "${recorded_wheel}" != "$(basename "${wheels[0]}")" ]]; then
+    echo "ROCm artifact wheel manifest ${recorded_wheel} does not match $(basename "${wheels[0]}")" >&2
+    return 1
+  fi
+  for required_dir in tests .buildkite requirements; do
+    if [[ ! -d "${wheel_dir}/${required_dir}" ]]; then
+      echo "ROCm wheel artifact did not contain ${required_dir}/" >&2
+      return 1
+    fi
+  done
+
+  echo "--- Installing ROCm wheel into pod environment"
+  python3 -m pip install --no-deps --force-reinstall "${wheels[0]}" || return 1
+
+  echo "--- Preparing ${workspace_dir} from artifact"
+  find "${workspace_dir}" -mindepth 1 -maxdepth 1 -exec rm -rf -- {} + || return 1
+  tar -C "${wheel_dir}" \
+    --exclude='*.whl' \
+    --exclude='.vllm-ci-artifact' \
+    --exclude='./.vllm-ci-artifact' \
+    -cf - . | tar --no-same-owner -C "${workspace_dir}" -xf - || return 1
+  if [[ ! -d "${workspace_dir}/tests" ]]; then
+    echo "Failed to stage the native test workspace" >&2
+    return 1
+  fi
+
+  return 0
+}
+
+initialize_native_environment() {
+  local job_id="${BUILDKITE_JOB_ID:-${BUILDKITE_PARALLEL_JOB:-local}}"
+  local job_id_suffix=""
+  local native_root=""
+  local hf_mount=""
+
+  if [[ "$(id -u)" -ne 0 ]]; then
+    echo "Native ROCm CI currently requires the ci_base container to run as root" >&2
+    return 1
+  fi
+
+  job_id="${job_id//[^A-Za-z0-9_.-]/_}"
+  job_id_suffix="${job_id##*-}"
+  job_id_suffix="${job_id_suffix:0:12}"
+  native_root="/tmp/vllm-native-${job_id}"
+  TMPDIR="/tmp/vllm-${job_id_suffix}/tmp"
+  VLLM_RPC_BASE_PATH="/tmp"
+  : "${TORCHINDUCTOR_CACHE_DIR:=${native_root}/cache/torchinductor}"
+  : "${TRITON_CACHE_DIR:=${native_root}/cache/triton}"
+  : "${VLLM_CACHE_ROOT:=${native_root}/cache/vllm}"
+  : "${XDG_CACHE_HOME:=${native_root}/cache/xdg}"
+  : "${HF_HOME:=/home/buildkite-agent/huggingface}"
+  : "${HF_HUB_DOWNLOAD_TIMEOUT:=300}"
+  : "${HF_HUB_ETAG_TIMEOUT:=60}"
+  export TMPDIR VLLM_RPC_BASE_PATH
+  export TORCHINDUCTOR_CACHE_DIR TRITON_CACHE_DIR VLLM_CACHE_ROOT XDG_CACHE_HOME
+  export HF_HOME HF_HUB_DOWNLOAD_TIMEOUT HF_HUB_ETAG_TIMEOUT
+  export PYTORCH_ROCM_ARCH=""
+
+  mkdir -p "${TMPDIR}" \
+    "${TORCHINDUCTOR_CACHE_DIR}" \
+    "${TRITON_CACHE_DIR}" \
+    "${VLLM_CACHE_ROOT}" \
+    "${XDG_CACHE_HOME}" \
+    "${HF_HOME}" || return 1
+
+  if [[ "${VLLM_CI_REQUIRE_PERSISTENT_HF_CACHE:-0}" == "1" ]]; then
+    if ! command -v findmnt >/dev/null 2>&1; then
+      echo "findmnt is required to verify the native Hugging Face cache mount" >&2
+      return 1
+    fi
+    hf_mount=$(findmnt -n -T "${HF_HOME}" -o TARGET 2>/dev/null || true)
+    if [[ -z "${hf_mount}" || "${hf_mount}" == "/" ]]; then
+      echo "Native CI requires a persistent volume mounted at or above ${HF_HOME}" >&2
+      return 1
+    fi
+  fi
+}
+
+run_native_preflight() {
+  local expected_gpus="${VLLM_CI_EXPECTED_GPU_COUNT:-1}"
+
+  if [[ ! "${expected_gpus}" =~ ^[0-9]+$ ]]; then
+    echo "Invalid VLLM_CI_EXPECTED_GPU_COUNT=${expected_gpus}" >&2
+    return 1
+  fi
+
+  python3 -c "import encodings, importlib.metadata as im, importlib.util as iu; [im.version(d) for d in ('transformers', 'torch', 'ray', 'sympy', 'markupsafe', 'vllm')]; missing=[m for m in ('torch.utils.model_zoo', 'transformers.models.nomic_bert', 'ray.dag', 'sympy.physics', 'markupsafe._speedups') if iu.find_spec(m) is None]; assert not missing, missing" || return 1
+
+  if [[ "${expected_gpus}" == "0" ]]; then
+    echo "Native CPU-only AMD job: skipping ROCm device validation"
+    return 0
+  fi
+
+  echo "--- ROCm info"
+  rocminfo || return 1
+  VLLM_CI_EXPECTED_GPU_COUNT="${expected_gpus}" python3 - <<'PY'
+import os
+
+import torch
+
+expected = int(os.environ["VLLM_CI_EXPECTED_GPU_COUNT"])
+assert torch.version.hip, "PyTorch is not a ROCm build"
+assert torch.cuda.is_available(), "ROCm GPU is not available to PyTorch"
+actual = torch.cuda.device_count()
+assert actual == expected, f"Expected {expected} ROCm GPU(s), found {actual}"
+PY
+}
+
 is_multi_node() {
   local cmds="$1"
   # Primary signal: NUM_NODES environment variable set by the pipeline
@@ -338,7 +644,58 @@ re_quote_pytest_markers() {
 # Main
 ###############################################################################
 
-# --- GPU initialization ---
+if is_native_runtime; then
+  echo "--- Native in-pod ROCm CI (AMD_CI_RUNTIME=${AMD_CI_RUNTIME:-unset}, NATIVE_CI=${NATIVE_CI:-unset})"
+  artifact_work_dir=""
+
+  cleanup_native_workspace() {
+    if [[ -n "${artifact_work_dir}" ]]; then
+      rm -rf "${artifact_work_dir}"
+    fi
+  }
+  trap cleanup_native_workspace EXIT
+
+  if [[ -n "${VLLM_TEST_COMMANDS:-}" ]]; then
+    commands="${VLLM_TEST_COMMANDS}"
+    commands_source="env"
+  else
+    commands="$*"
+    commands_source="argv"
+    if [[ -z "$commands" ]]; then
+      echo "Error: No test commands provided for native CI." >&2
+      exit 1
+    fi
+  fi
+
+  if [[ "$commands_source" == "argv" ]]; then
+    commands=$(re_quote_pytest_markers "$commands")
+  fi
+
+  if is_multi_node "$commands"; then
+    echo "Native CI does not support multi-node jobs yet."
+    exit 1
+  fi
+
+  if ! initialize_native_environment; then
+    echo "Failed to initialize the native test environment"
+    exit 1
+  fi
+  if ! prepare_native_workspace; then
+    echo "Failed to prepare native test workspace"
+    exit 1
+  fi
+
+  export PYTHONPATH="${VLLM_CI_WORKSPACE:-/vllm-workspace}"
+
+  echo "Native test commands: $commands"
+  run_native_preflight || exit 1
+  # Keep AMD CI orchestration variables out of vLLM's runtime environment.
+  clear_ci_orchestration_env
+  /bin/bash -o pipefail -c "${commands}"
+  handle_pytest_exit "$?"
+fi
+
+# --- GPU initialization for legacy Docker execution ---
 echo "--- ROCm info"
 rocminfo
 
@@ -440,23 +797,27 @@ fi
 
 echo "Final commands: $commands"
 
-# The ROCm test image often ships /vllm-workspace without .git (artifact tarball unpack).
-# tests/standalone_tests/python_only_compile.sh uses merge-base(HEAD, origin/main) for
-# wheels.vllm.ai; compute on the agent (full git checkout) and pass into the container.
-vllm_standalone_merge_base=""
-checkout="${BUILDKITE_BUILD_CHECKOUT_PATH:-}"
-if [[ -z "${checkout}" || ! -d "${checkout}" ]]; then
-  checkout="."
+standalone_merge_base_env=()
+if [[ "$commands" == *python_only_compile.sh* ]]; then
+  # The ROCm test image often ships /vllm-workspace without .git. Resolve the
+  # wheels.vllm.ai commit from the agent checkout for this test only.
+  vllm_standalone_merge_base=""
+  checkout="${BUILDKITE_BUILD_CHECKOUT_PATH:-}"
+  if [[ -z "${checkout}" || ! -d "${checkout}" ]]; then
+    checkout="."
+  fi
+  # Pass safe.directory per-command because Buildkite uses mixed user IDs.
+  if git -c "safe.directory=${checkout}" -C "${checkout}" rev-parse --is-inside-work-tree >/dev/null 2>&1; then
+    vllm_standalone_merge_base="$(
+      git -c "safe.directory=${checkout}" -C "${checkout}" merge-base HEAD origin/main 2>/dev/null || true
+    )"
+  fi
+  if [[ -z "${vllm_standalone_merge_base}" ]]; then
+    vllm_standalone_merge_base="${BUILDKITE_COMMIT:-}"
+  fi
+  echo "INFO: passing CI_STANDALONE_MERGE_BASE into container: ${vllm_standalone_merge_base}"
+  standalone_merge_base_env=(-e "CI_STANDALONE_MERGE_BASE=${vllm_standalone_merge_base}")
 fi
-if git -C "${checkout}" rev-parse --is-inside-work-tree >/dev/null 2>&1; then
-  vllm_standalone_merge_base="$(
-    git -C "${checkout}" merge-base HEAD origin/main 2>/dev/null || true
-  )"
-fi
-if [[ -z "${vllm_standalone_merge_base}" ]]; then
-  vllm_standalone_merge_base="${BUILDKITE_COMMIT:-}"
-fi
-echo "INFO: passing VLLM_STANDALONE_MERGE_BASE into container: ${vllm_standalone_merge_base}"
 
 MYPYTHONPATH="/vllm-workspace"
 
@@ -487,6 +848,7 @@ else
 fi
 
 # --- Route: multi-node vs single-node ---
+clear_ci_orchestration_env
 if is_multi_node "$commands"; then
   echo "--- Multi-node job detected"
   export DCKR_VER=$(docker --version | sed 's/Docker version \(.*\), build .*/\1/')
@@ -533,14 +895,37 @@ if is_multi_node "$commands"; then
 else
   echo "--- Single-node job"
   echo "Render devices: $BUILDKITE_AGENT_META_DATA_RENDER_DEVICES"
+  docker_run_terminal_args=(-i)
+  if [[ "${ROCM_DOCKER_TTY}" == "1" ]]; then
+    docker_run_terminal_args+=(-t)
+    echo "Docker interactive stdin: enabled; TTY allocation: enabled"
+  else
+    echo "Docker interactive stdin: enabled; TTY allocation: disabled"
+  fi
+
+  ulimit_core_hard=$(ulimit -H -c)
+  if [[ "$ulimit_core_hard" == "unlimited" ]]; then
+    # docker run can't pass "unlimited" to --ulimit
+    ulimit_core_hard="-1"
+  fi
+   # Disable core dumps in the ROCm test container unless the ROCm debug agent is enabled
+  coredump_flags="--ulimit core=0:$ulimit_core_hard"
+  if [[ "$commands" == *"ROCm debug agent enabled"* ]]; then
+    # Works around https://github.com/rocm/rocm-systems/issues/6206
+    coredump_flags='-e HSA_COREDUMP_PATTERN="/tmp/gpucore.%p"'
+  else
+    echo "ROCm debug agent not enabled, coredumps are disabled in the test container."
+  fi
 
   docker run \
+    "${docker_run_terminal_args[@]}" \
     --device /dev/kfd $BUILDKITE_AGENT_META_DATA_RENDER_DEVICES \
     $RDMA_FLAGS \
     --network=host \
     --shm-size=16gb \
     --group-add "$render_gid" \
     --rm \
+    $coredump_flags \
     -e HF_TOKEN \
     -e "HF_HUB_DOWNLOAD_TIMEOUT=${HF_HUB_DOWNLOAD_TIMEOUT}" \
     -e "HF_HUB_ETAG_TIMEOUT=${HF_HUB_ETAG_TIMEOUT}" \
@@ -548,6 +933,13 @@ else
     -e AWS_SECRET_ACCESS_KEY \
     -e BUILDKITE_PARALLEL_JOB \
     -e BUILDKITE_PARALLEL_JOB_COUNT \
+    -e TERM \
+    -e FORCE_COLOR \
+    -e CLICOLOR_FORCE \
+    -e PY_COLORS \
+    -e PYTHONFAULTHANDLER \
+    -e PYTEST_ADDOPTS \
+    -e PYTEST_TIMEOUT \
     -v "${HF_CACHE}:${HF_MOUNT}" \
     -e "HF_HOME=${HF_MOUNT}" \
     -e "PYTHONPATH=${MYPYTHONPATH}" \
@@ -557,7 +949,7 @@ else
     -e "VLLM_CACHE_ROOT=${CONTAINER_CACHE_ROOT}/vllm" \
     -e "XDG_CACHE_HOME=${CONTAINER_CACHE_ROOT}/xdg" \
     -e "PYTORCH_ROCM_ARCH=" \
-    -e "VLLM_STANDALONE_MERGE_BASE=${vllm_standalone_merge_base}" \
+    "${standalone_merge_base_env[@]}" \
     --name "${container_name}" \
     "${image_name}" \
     /bin/bash -c "${CONTAINER_PREFLIGHT} && ${commands}"

.buildkite/scripts/hardware_ci/run-cpu-test-arm.sh

@@ -38,7 +38,11 @@ function cpu_tests() {
     pytest -x -v -s tests/kernels/attention/test_cpu_attn.py
     pytest -x -v -s tests/kernels/core/test_cpu_activation.py
     pytest -x -v -s tests/kernels/moe/test_cpu_fused_moe.py
-    pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
+    pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py
+    pytest -x -v -s tests/kernels/moe/test_cpu_int4_moe.py
+    pytest -x -v -s tests/kernels/mamba/test_cpu_short_conv.py
+    pytest -x -v -s tests/kernels/mamba/test_causal_conv1d.py
+    pytest -x -v -s tests/kernels/mamba/test_mamba_ssm.py"
 
   # skip tests requiring model downloads if HF_TOKEN is not set
   # due to rate-limits
@@ -62,7 +66,6 @@ function cpu_tests() {
     set -e
     pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs"
 
-
   # basic online serving
   docker exec cpu-test bash -c '
     set -e
@@ -96,3 +99,4 @@ function cpu_tests() {
 # All of CPU tests are expected to be finished less than 40 mins.
 export -f cpu_tests
 timeout 2h bash -c cpu_tests
+

.buildkite/scripts/hardware_ci/run-intel-ci-test.sh

@@ -21,6 +21,7 @@ case "${test_suite}" in
     python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --kv-cache-dtype fp8
     python3 examples/basic/offline_inference/generate.py --model nvidia/Llama-3.1-8B-Instruct-FP8 --block-size 64 --enforce-eager --quantization modelopt --kv-cache-dtype fp8 --attention-backend TRITON_ATTN --max-model-len 4096
     python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --block-size 64 --enforce-eager --max-model-len 8192
+    python3 examples/basic/offline_inference/generate.py --model TheBloke/TinyLlama-1.1B-Chat-v0.3-AWQ --block-size 64 --enforce-eager 
     python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2
     python3 examples/basic/offline_inference/generate.py --model ibm-research/PowerMoE-3b --block-size 64 --enforce-eager -tp 2 --enable-expert-parallel
     python3 examples/basic/offline_inference/generate.py --model superjob/Qwen3-4B-Instruct-2507-GPTQ-Int4 --max-model-len 8192
@@ -34,6 +35,7 @@ case "${test_suite}" in
     pytest -v -s v1/worker --ignore=v1/worker/test_gpu_model_runner.py --ignore=v1/worker/test_worker_memory_snapshot.py
     pytest -v -s v1/structured_output
     pytest -v -s v1/test_serial_utils.py
+    pytest -v -s v1/e2e/general/test_correctness_sliding_window.py --deselect="tests/v1/e2e/general/test_correctness_sliding_window.py::test_sliding_window_retrieval[True-1-5-google/gemma-3-1b-it]"
     pytest -v -s v1/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.py --ignore=v1/spec_decode/test_speculators_correctness.py
     pytest -v -s v1/kv_connector/unit --ignore=v1/kv_connector/unit/test_multi_connector.py --ignore=v1/kv_connector/unit/test_example_connector.py --ignore=v1/kv_connector/unit/test_lmcache_integration.py --ignore=v1/kv_connector/unit/test_hf3fs_client.py --ignore=v1/kv_connector/unit/test_hf3fs_connector.py --ignore=v1/kv_connector/unit/test_hf3fs_metadata_server.py --ignore=v1/kv_connector/unit/test_offloading_connector.py
     ;;

.buildkite/scripts/hardware_ci/run-intel-test.sh

@@ -360,7 +360,7 @@ export HF_TOKEN ZE_AFFINITY_MASK
     --ipc=host \
     --privileged \
     -v /dev/dri/by-path:/dev/dri/by-path \
-    -v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
+    -v "/data/huggingface:/root/.cache/huggingface" \
     --entrypoint='' \
     -e HF_TOKEN \
     -e ZE_AFFINITY_MASK \

.buildkite/scripts/hardware_ci/run-npu-test.sh

@@ -85,7 +85,7 @@ RUN pip config set global.index-url http://cache-service-vllm.nginx-pypi-cache.s
 
 # Install for pytest to make the docker build cache layer always valid
 RUN --mount=type=cache,target=/root/.cache/pip \
-    pip install pytest>=6.0  modelscope
+    pip install pytest>=6.0  'modelscope<1.38'
 
 WORKDIR /workspace/vllm
 

.buildkite/scripts/publish-release-images.sh

@@ -130,6 +130,22 @@ docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm
 docker push vllm/vllm-openai-rocm:latest-base
 docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
 
+# ---- XPU ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu vllm/vllm-openai-xpu:latest-x86_64
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-xpu vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64
+docker push vllm/vllm-openai-xpu:latest-x86_64
+docker push vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64
+
+docker manifest rm vllm/vllm-openai-xpu:latest || true
+docker manifest rm vllm/vllm-openai-xpu:v${RELEASE_VERSION} || true
+docker manifest create vllm/vllm-openai-xpu:latest vllm/vllm-openai-xpu:latest-x86_64 --amend
+docker manifest create vllm/vllm-openai-xpu:v${RELEASE_VERSION} vllm/vllm-openai-xpu:v${RELEASE_VERSION}-x86_64 --amend
+docker manifest push vllm/vllm-openai-xpu:latest
+docker manifest push vllm/vllm-openai-xpu:v${RELEASE_VERSION}
+
 # ---- CPU ----
 # CPU images are behind separate block steps and may not have been built.
 # All-or-nothing: inspect both arches first, then either publish everything

.buildkite/scripts/rocm/build-ci-base.sh

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+# Build the ROCm ci_base image, optionally from a freshly rebuilt ROCm base.
+
+set -euo pipefail
+
+metadata_get() {
+    local key="$1"
+    if command -v buildkite-agent >/dev/null 2>&1; then
+        buildkite-agent meta-data get "${key}" 2>/dev/null || true
+    fi
+}
+
+main() {
+    local base_refreshed=""
+
+    base_refreshed="$(metadata_get rocm-base-refresh)"
+    if [[ "${base_refreshed}" == "1" ]]; then
+        export BASE_IMAGE
+        export CI_BASE_PUSH_STABLE_TAG
+
+        BASE_IMAGE="$(metadata_get rocm-base-image)"
+        CI_BASE_PUSH_STABLE_TAG="$(metadata_get rocm-base-push-stable-tag)"
+        CI_BASE_PUSH_STABLE_TAG="${CI_BASE_PUSH_STABLE_TAG:-0}"
+
+        echo "Using refreshed ROCm base image for ci_base: ${BASE_IMAGE}"
+        echo "Push stable ci_base tag: ${CI_BASE_PUSH_STABLE_TAG}"
+    fi
+
+    bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
+}
+
+main "$@"

.buildkite/scripts/rocm/build-test-image.sh

@@ -0,0 +1,68 @@
+#!/usr/bin/env bash
+# Build the ROCm CI test image or wheel artifact.
+#
+# When Dockerfile.rocm_base changes, always build the full image so downstream
+# ROCm tests can validate the freshly rebuilt base -> ci_base -> ci image chain.
+
+set -euo pipefail
+
+metadata_get() {
+    local key="$1"
+    if command -v buildkite-agent >/dev/null 2>&1; then
+        buildkite-agent meta-data get "${key}" 2>/dev/null || true
+    fi
+}
+
+use_ci_base_if_present() {
+    local ci_base_image=""
+
+    ci_base_image="$(metadata_get rocm-ci-base-image)"
+    if [[ -z "${ci_base_image}" ]]; then
+        return 1
+    fi
+
+    export CI_BASE_IMAGE="${ci_base_image}"
+    echo "Using ROCm ci_base image selected by the preceding build step: ${CI_BASE_IMAGE}"
+}
+
+use_refreshed_base_if_present() {
+    local base_refreshed=""
+
+    base_refreshed="$(metadata_get rocm-base-refresh)"
+    if [[ "${base_refreshed}" != "1" ]]; then
+        return 1
+    fi
+
+    export BASE_IMAGE
+    export IMAGE_TAG_LATEST
+
+    BASE_IMAGE="$(metadata_get rocm-base-image)"
+    IMAGE_TAG_LATEST="$(metadata_get rocm-ci-image-descriptive)"
+
+    echo "Using refreshed ROCm base image for test image: ${BASE_IMAGE}"
+    if [[ -n "${IMAGE_TAG_LATEST}" ]]; then
+        echo "Also tagging full ROCm CI image as: ${IMAGE_TAG_LATEST}"
+    fi
+
+    return 0
+}
+
+main() {
+    local base_refreshed=0
+
+    use_ci_base_if_present || true
+
+    if use_refreshed_base_if_present; then
+        base_refreshed=1
+    fi
+
+    if [[ "${ROCM_CI_ARTIFACT_ONLY:-0}" == "1" && "${base_refreshed}" != "1" ]]; then
+        echo "ROCM_CI_ARTIFACT_ONLY=1; building ROCm wheel artifact only"
+        IMAGE_TAG="" bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-artifacts
+        return
+    fi
+
+    bash .buildkite/scripts/ci-bake-rocm.sh test-rocm-ci-with-wheel
+}
+
+main "$@"

.buildkite/scripts/rocm/refresh-base-image.sh

@@ -0,0 +1,513 @@
+#!/usr/bin/env bash
+# Build and publish a fresh ROCm base image when Dockerfile.rocm_base changes.
+#
+# Normal AMD CI builds should not pay for this path. The script no-ops unless
+# docker/Dockerfile.rocm_base changed relative to the branch base, the previous
+# main commit, or ROCM_BASE_REFRESH_FORCE=1 is set.
+
+set -euo pipefail
+
+DOCKERFILE="${ROCM_BASE_DOCKERFILE:-docker/Dockerfile.rocm_base}"
+BASE_REPO="${ROCM_BASE_IMAGE_REPO:-rocm/vllm-dev}"
+CI_IMAGE_REPO="${ROCM_CI_IMAGE_REPO:-rocm/vllm-ci}"
+BUILDER_NAME="${ROCM_BASE_BUILDER_NAME:-vllm-rocm-base-builder}"
+DEFAULT_ROCM_BASE_METADATA_VERSION="1"
+DEFAULT_ROCM_BASE_CONTENT_FILES="${DOCKERFILE}"
+DEFAULT_ROCM_BASE_CONTENT_ARGS="BASE_IMAGE TRITON_BRANCH TRITON_REPO PYTORCH_BRANCH PYTORCH_REPO PYTORCH_VISION_BRANCH PYTORCH_VISION_REPO PYTORCH_AUDIO_BRANCH PYTORCH_AUDIO_REPO FA_BRANCH FA_REPO AITER_BRANCH AITER_REPO MORI_BRANCH MORI_REPO PYTORCH_ROCM_ARCH PYTHON_VERSION USE_SCCACHE"
+
+metadata_set() {
+    local key="$1"
+    local value="$2"
+
+    [[ -n "${value}" ]] || return 0
+    if command -v buildkite-agent >/dev/null 2>&1; then
+        buildkite-agent meta-data set "${key}" "${value}" || true
+    fi
+}
+
+compute_content_hash() {
+    local path=""
+    local file=""
+
+    for path in "$@"; do
+        if [[ -d "${path}" ]]; then
+            while IFS= read -r -d '' file; do
+                printf 'file:%s\n' "${file}"
+                sha256sum "${file}"
+            done < <(find "${path}" -type f -print0 | sort -z)
+        elif [[ -f "${path}" ]]; then
+            printf 'file:%s\n' "${path}"
+            sha256sum "${path}"
+        else
+            printf 'missing:%s\n' "${path}"
+        fi
+    done | sha256sum | cut -d' ' -f1
+}
+
+clean_docker_tag() {
+    local input="$1"
+    echo "${input}" | sed 's/[^a-zA-Z0-9._-]/_/g' | cut -c1-128
+}
+
+tag_component() {
+    local input="$1"
+    local max_chars="${2:-24}"
+
+    clean_docker_tag "${input:-unknown}" | cut -c1-"${max_chars}"
+}
+
+extract_arg_default() {
+    local arg_name="$1"
+
+    sed -n -E "s/^[[:space:]]*ARG[[:space:]]+${arg_name}=\"?([^\"[:space:]]+)\"?.*/\\1/p" \
+        "${DOCKERFILE}" | head -1
+}
+
+resolve_image_digest() {
+    local image_ref="$1"
+
+    docker buildx imagetools inspect "${image_ref}" 2>/dev/null \
+        | sed -n -E 's/^Digest:[[:space:]]+//p' \
+        | head -1 || true
+}
+
+resolve_rocm_base_arg_value() {
+    local arg_name="$1"
+    local use_sccache="$2"
+
+    case "${arg_name}" in
+        USE_SCCACHE)
+            printf '%s\n' "${use_sccache}"
+            ;;
+        *)
+            extract_arg_default "${arg_name}"
+            ;;
+    esac
+}
+
+hash_rocm_base_arg_values() {
+    local use_sccache="$1"
+    local base_image_digest="$2"
+    local arg_name=""
+    local arg_value=""
+    shift 2 || true
+
+    for arg_name in "$@"; do
+        [[ -n "${arg_name}" ]] || continue
+        arg_value=$(resolve_rocm_base_arg_value "${arg_name}" "${use_sccache}")
+        printf 'arg:%s=%s\n' "${arg_name}" "${arg_value:-<empty>}"
+        if [[ "${arg_name}" == "BASE_IMAGE" && -n "${arg_value}" ]]; then
+            printf 'arg:%s.digest=%s\n' "${arg_name}" "${base_image_digest:-unknown}"
+        fi
+    done
+}
+
+rocm_version_from_base_image() {
+    local base_image="$1"
+    local version=""
+
+    version="$(sed -n -E 's/.*:([0-9]+\.[0-9]+(\.[0-9]+)?)-.*/\1/p' <<<"${base_image}")"
+    tag_component "${version:-${base_image}}" 16
+}
+
+git_diff_changed_base() {
+    local range="$1"
+    [[ -n "$(git diff --name-only "${range}" -- "${DOCKERFILE}" 2>/dev/null)" ]]
+}
+
+short_git_ref() {
+    local ref="$1"
+
+    git rev-parse --short "${ref}" 2>/dev/null || printf '%s\n' "${ref}"
+}
+
+extract_arg_default_from_ref() {
+    local ref="$1"
+    local arg_name="$2"
+    local content=""
+
+    content="$(git show "${ref}:${DOCKERFILE}" 2>/dev/null || true)"
+    sed -n -E "s/^[[:space:]]*ARG[[:space:]]+${arg_name}=\"?([^\"[:space:]]+)\"?.*/\\1/p" \
+        <<<"${content}" | head -1
+}
+
+log_arg_default_changes() {
+    local old_ref="$1"
+    local new_ref="$2"
+    local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
+    local arg_name=""
+    local old_value=""
+    local new_value=""
+    local changed=0
+
+    echo "Changed ROCm base ARG defaults:"
+    for arg_name in ${content_args}; do
+        old_value="$(extract_arg_default_from_ref "${old_ref}" "${arg_name}")"
+        new_value="$(extract_arg_default_from_ref "${new_ref}" "${arg_name}")"
+        if [[ "${old_value}" != "${new_value}" ]]; then
+            echo "  - ${arg_name}: ${old_value:-<unset>} -> ${new_value:-<unset>}"
+            changed=1
+        fi
+    done
+
+    if [[ "${changed}" == "0" ]]; then
+        echo "  - none detected; Dockerfile instructions changed outside tracked ARG defaults"
+    fi
+}
+
+log_arg_line_diff() {
+    local range="$1"
+    local arg_diff=""
+
+    arg_diff="$(
+        git diff --unified=0 "${range}" -- "${DOCKERFILE}" 2>/dev/null \
+            | awk '/^[+-][[:space:]]*ARG[[:space:]]/ && $0 !~ /^(---|\+\+\+)/ { print "  " $0 }' \
+            || true
+    )"
+
+    if [[ -n "${arg_diff}" ]]; then
+        echo "Changed Dockerfile ARG lines:"
+        printf '%s\n' "${arg_diff}"
+    fi
+}
+
+log_rocm_base_change_check() {
+    local context="$1"
+    local range="$2"
+    local old_ref="$3"
+    local old_short=""
+    local head_short=""
+
+    old_short="$(short_git_ref "${old_ref}")"
+    head_short="$(short_git_ref HEAD)"
+
+    echo "--- :mag: ROCm base refresh check"
+    echo "Context: ${context}"
+    echo "Dockerfile: ${DOCKERFILE}"
+    echo "Base revision: ${old_short}"
+    echo "Head revision: ${head_short}"
+    echo "Git diff range: ${range}"
+}
+
+log_rocm_base_rebuild_reason() {
+    local context="$1"
+    local range="$2"
+    local old_ref="$3"
+    local changed_files=""
+
+    log_rocm_base_change_check "${context}" "${range}" "${old_ref}"
+
+    changed_files="$(git diff --name-only "${range}" -- "${DOCKERFILE}" 2>/dev/null || true)"
+    echo "Changed files:"
+    if [[ -n "${changed_files}" ]]; then
+        sed 's/^/  - /' <<<"${changed_files}"
+    else
+        echo "  - ${DOCKERFILE}"
+    fi
+    log_arg_default_changes "${old_ref}" HEAD
+    log_arg_line_diff "${range}"
+    echo "Decision: rebuilding ROCm base image because ${DOCKERFILE} changed."
+}
+
+rocm_base_changed_in_range() {
+    local context="$1"
+    local range="$2"
+    local old_ref="$3"
+
+    if git_diff_changed_base "${range}"; then
+        log_rocm_base_rebuild_reason "${context}" "${range}" "${old_ref}"
+        return 0
+    fi
+
+    log_rocm_base_change_check "${context}" "${range}" "${old_ref}"
+    echo "Decision: ROCm base refresh not required; ${DOCKERFILE} is unchanged."
+    return 1
+}
+
+rocm_base_changed() {
+    local base_branch="${BUILDKITE_PULL_REQUEST_BASE_BRANCH:-main}"
+    local base_ref="refs/remotes/origin/${base_branch}"
+    local merge_base=""
+
+    if [[ "${ROCM_BASE_REFRESH_SKIP:-0}" == "1" ]]; then
+        echo "ROCM_BASE_REFRESH_SKIP=1 set; skipping ROCm base refresh"
+        return 1
+    fi
+
+    if [[ "${ROCM_BASE_REFRESH_FORCE:-0}" == "1" ]]; then
+        echo "ROCM_BASE_REFRESH_FORCE=1 set; refreshing ROCm base image"
+        return 0
+    fi
+
+    if ! git rev-parse --is-inside-work-tree >/dev/null 2>&1; then
+        echo "Not in a git checkout; skipping ROCm base refresh unless forced"
+        return 1
+    fi
+
+    if [[ "${BUILDKITE_PULL_REQUEST:-false}" != "false" ]]; then
+        git fetch --no-tags --depth=200 origin \
+            "+refs/heads/${base_branch}:${base_ref}" >/dev/null 2>&1 || true
+        merge_base=$(git merge-base HEAD "${base_ref}" 2>/dev/null || true)
+        if [[ -z "${merge_base}" ]]; then
+            echo "Unable to determine merge base with PR base ${base_ref}; skipping ROCm base refresh unless forced"
+            return 1
+        fi
+        if rocm_base_changed_in_range \
+            "pull request build against ${base_ref}" \
+            "${merge_base}...HEAD" \
+            "${merge_base}"; then
+            return 0
+        fi
+    elif [[ "${BUILDKITE_BRANCH:-}" == "${ROCM_BASE_STABLE_BRANCH:-main}" ]] \
+        && git rev-parse --verify HEAD~1 >/dev/null 2>&1; then
+        if rocm_base_changed_in_range \
+            "stable branch build; comparing against previous ${ROCM_BASE_STABLE_BRANCH:-main} commit" \
+            "HEAD~1..HEAD" \
+            "HEAD~1"; then
+            return 0
+        fi
+    else
+        git fetch --no-tags --depth=200 origin \
+            "+refs/heads/${base_branch}:${base_ref}" >/dev/null 2>&1 || true
+        merge_base=$(git merge-base HEAD "${base_ref}" 2>/dev/null || true)
+        if [[ -z "${merge_base}" ]]; then
+            echo "Unable to determine merge base with branch base ${base_ref}; skipping ROCm base refresh unless forced"
+            return 1
+        fi
+        if rocm_base_changed_in_range \
+            "branch build against ${base_ref}" \
+            "${merge_base}...HEAD" \
+            "${merge_base}"; then
+            return 0
+        fi
+    fi
+
+    return 1
+}
+
+should_push_stable_tag() {
+    if [[ "${BUILDKITE_PULL_REQUEST:-false}" != "false" ]]; then
+        return 1
+    fi
+
+    if [[ "${ROCM_BASE_PUSH_STABLE_TAG:-}" == "1" ]]; then
+        return 0
+    fi
+    if [[ "${ROCM_BASE_PUSH_STABLE_TAG:-}" == "0" ]]; then
+        return 1
+    fi
+
+    [[ "${BUILDKITE_PULL_REQUEST:-false}" == "false" \
+        && "${BUILDKITE_BRANCH:-}" == "${ROCM_BASE_STABLE_BRANCH:-main}" ]]
+}
+
+setup_builder() {
+    echo "--- :buildkite: Setting up buildx builder for ROCm base"
+    if docker buildx inspect "${BUILDER_NAME}" >/dev/null 2>&1; then
+        docker buildx use "${BUILDER_NAME}"
+    else
+        docker buildx create --name "${BUILDER_NAME}" --driver docker-container --use
+    fi
+    docker buildx inspect --bootstrap
+}
+
+compute_base_content_hash() {
+    local use_sccache="$1"
+    local base_image_digest="$2"
+    local content_files="${ROCM_BASE_CONTENT_FILES:-${DEFAULT_ROCM_BASE_CONTENT_FILES}}"
+    local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
+    local -a content_paths=()
+    local -a content_arg_names=()
+
+    read -r -a content_paths <<< "${content_files}"
+    read -r -a content_arg_names <<< "${content_args}"
+
+    {
+        printf 'content-files-hash:%s\n' "$(compute_content_hash "${content_paths[@]}")"
+        printf 'dockerfile:%s\n' "${DOCKERFILE}"
+        printf 'resolved-build-args:\n'
+        hash_rocm_base_arg_values \
+            "${use_sccache}" "${base_image_digest}" "${content_arg_names[@]}"
+    } | sha256sum | cut -d' ' -f1
+}
+
+build_base_image() {
+    local use_sccache="${ROCM_BASE_USE_SCCACHE:-${USE_SCCACHE:-0}}"
+    local base_hash=""
+    local build_date=""
+    local build_suffix=""
+    local base_image_arg=""
+    local base_image_digest=""
+    local rocm_version=""
+    local triton_arg=""
+    local pytorch_arg=""
+    local pytorch_vision_arg=""
+    local pytorch_audio_arg=""
+    local fa_arg=""
+    local aiter_arg=""
+    local mori_arg=""
+    local python_version_arg=""
+    local pytorch_rocm_arch_arg=""
+    local pytorch_branch=""
+    local aiter_branch=""
+    local dependency_summary=""
+    local descriptor=""
+    local ci_descriptor=""
+    local descriptive_tag=""
+    local stable_tag="${BASE_REPO}:base"
+    local ci_descriptive_tag=""
+    local content_files="${ROCM_BASE_CONTENT_FILES:-${DEFAULT_ROCM_BASE_CONTENT_FILES}}"
+    local content_args="${ROCM_BASE_CONTENT_ARGS:-${DEFAULT_ROCM_BASE_CONTENT_ARGS}}"
+    local content_files_hash=""
+    local metadata_version="${ROCM_BASE_METADATA_VERSION:-${DEFAULT_ROCM_BASE_METADATA_VERSION}}"
+    local -a tags=()
+    local -a no_cache_args=()
+    local -a sccache_args=()
+    local -a content_paths=()
+
+    if [[ ! -f "${DOCKERFILE}" ]]; then
+        echo "Error: ROCm base Dockerfile not found: ${DOCKERFILE}" >&2
+        exit 1
+    fi
+
+    build_date="${ROCM_BASE_TAG_DATE:-$(date -u +%Y%m%d)}"
+    if [[ -n "${BUILDKITE_BUILD_NUMBER:-}" ]]; then
+        build_suffix="_bk_${BUILDKITE_BUILD_NUMBER}"
+    fi
+    base_image_arg="$(extract_arg_default BASE_IMAGE)"
+    base_image_digest="$(resolve_image_digest "${base_image_arg}")"
+    read -r -a content_paths <<< "${content_files}"
+    content_files_hash="$(compute_content_hash "${content_paths[@]}")"
+    base_hash=$(compute_base_content_hash "${use_sccache}" "${base_image_digest}")
+    rocm_version="$(rocm_version_from_base_image "${base_image_arg}")"
+    triton_arg="$(extract_arg_default TRITON_BRANCH)"
+    pytorch_arg="$(extract_arg_default PYTORCH_BRANCH)"
+    pytorch_vision_arg="$(extract_arg_default PYTORCH_VISION_BRANCH)"
+    pytorch_audio_arg="$(extract_arg_default PYTORCH_AUDIO_BRANCH)"
+    fa_arg="$(extract_arg_default FA_BRANCH)"
+    aiter_arg="$(extract_arg_default AITER_BRANCH)"
+    mori_arg="$(extract_arg_default MORI_BRANCH)"
+    python_version_arg="$(extract_arg_default PYTHON_VERSION)"
+    pytorch_rocm_arch_arg="$(extract_arg_default PYTORCH_ROCM_ARCH)"
+    pytorch_branch="$(tag_component "${pytorch_arg}" 16)"
+    aiter_branch="$(tag_component "${aiter_arg}" 24)"
+    dependency_summary="base=${base_image_arg},rocm=${rocm_version},python=${python_version_arg},pytorch=${pytorch_arg},torchvision=${pytorch_vision_arg},torchaudio=${pytorch_audio_arg},triton=${triton_arg},flash-attn=${fa_arg},aiter=${aiter_arg},mori=${mori_arg},pytorch-rocm-arch=${pytorch_rocm_arch_arg}"
+    descriptor="$(clean_docker_tag "base_custom_aiter_${aiter_branch}_torch_${pytorch_branch}_${build_date}${build_suffix}")"
+    ci_descriptor="$(clean_docker_tag "ci_custom_aiter_${aiter_branch}_torch_${pytorch_branch}_${build_date}${build_suffix}")"
+
+    descriptive_tag="${BASE_REPO}:${descriptor}"
+    ci_descriptive_tag="${CI_IMAGE_REPO}:${ci_descriptor}"
+
+    tags=(-t "${descriptive_tag}")
+    if should_push_stable_tag; then
+        tags+=(-t "${stable_tag}")
+        metadata_set "rocm-base-push-stable-tag" "1"
+    else
+        metadata_set "rocm-base-push-stable-tag" "0"
+    fi
+
+    if [[ "${ROCM_BASE_NO_CACHE:-1}" == "1" ]]; then
+        no_cache_args=(--no-cache)
+    fi
+
+    for env_name in \
+        SCCACHE_DOWNLOAD_URL \
+        SCCACHE_ENDPOINT \
+        SCCACHE_BUCKET_NAME \
+        SCCACHE_REGION_NAME \
+        SCCACHE_S3_NO_CREDENTIALS; do
+        if [[ -n "${!env_name:-}" ]]; then
+            sccache_args+=(--build-arg "${env_name}=${!env_name}")
+        fi
+    done
+
+    echo "--- :docker: Building ROCm base image"
+    echo "Dockerfile: ${DOCKERFILE}"
+    echo "Descriptive tag: ${descriptive_tag}"
+    echo "Stable tag: ${stable_tag} ($(should_push_stable_tag && echo enabled || echo disabled))"
+    echo "Content hash: ${base_hash}"
+    echo "Dependency summary: ${dependency_summary}"
+    echo "USE_SCCACHE: ${use_sccache}"
+
+    docker buildx build \
+        "${no_cache_args[@]}" \
+        --pull \
+        --progress "${BUILDKIT_PROGRESS:-plain}" \
+        --file "${DOCKERFILE}" \
+        --build-arg "USE_SCCACHE=${use_sccache}" \
+        "${sccache_args[@]}" \
+        --label "org.opencontainers.image.source=https://github.com/vllm-project/vllm" \
+        --label "org.opencontainers.image.vendor=vLLM" \
+        --label "org.opencontainers.image.title=vLLM ROCm base" \
+        --label "org.opencontainers.image.revision=${BUILDKITE_COMMIT:-}" \
+        --label "vllm.rocm_base.metadata_version=${metadata_version}" \
+        --label "vllm.rocm_base.content_hash=${base_hash}" \
+        --label "vllm.rocm_base.content_files_hash=${content_files_hash}" \
+        --label "vllm.rocm_base.dockerfile=${DOCKERFILE}" \
+        --label "vllm.rocm_base.image.descriptive=${descriptive_tag}" \
+        --label "vllm.rocm_base.image.stable=${stable_tag}" \
+        --label "vllm.rocm_base.git_commit=${BUILDKITE_COMMIT:-}" \
+        --label "vllm.rocm_base.stable_branch=${ROCM_BASE_STABLE_BRANCH:-main}" \
+        --label "vllm.rocm_base.descriptor=${descriptor}" \
+        --label "vllm.rocm_base.dependency_summary=${dependency_summary}" \
+        --label "vllm.rocm_base.base_image=${base_image_arg}" \
+        --label "vllm.rocm_base.base_image_digest=${base_image_digest}" \
+        --label "vllm.rocm_base.dependency.rocm=${rocm_version}" \
+        --label "vllm.rocm_base.dependency.python=${python_version_arg}" \
+        --label "vllm.rocm_base.dependency.pytorch=${pytorch_arg}" \
+        --label "vllm.rocm_base.dependency.torchvision=${pytorch_vision_arg}" \
+        --label "vllm.rocm_base.dependency.torchaudio=${pytorch_audio_arg}" \
+        --label "vllm.rocm_base.dependency.triton=${triton_arg}" \
+        --label "vllm.rocm_base.dependency.flash_attention=${fa_arg}" \
+        --label "vllm.rocm_base.dependency.aiter=${aiter_arg}" \
+        --label "vllm.rocm_base.dependency.mori=${mori_arg}" \
+        --label "vllm.rocm_base.pytorch_rocm_arch=${pytorch_rocm_arch_arg}" \
+        "${tags[@]}" \
+        --push \
+        .
+
+    docker buildx imagetools inspect "${descriptive_tag}" >/dev/null
+
+    metadata_set "rocm-base-refresh" "1"
+    metadata_set "rocm-base-image" "${descriptive_tag}"
+    metadata_set "rocm-base-image-descriptive" "${descriptive_tag}"
+    metadata_set "rocm-base-image-stable" "${stable_tag}"
+    metadata_set "rocm-base-image-ci-descriptive" "${ci_descriptive_tag}"
+    metadata_set "rocm-base-metadata-version" "${metadata_version}"
+    metadata_set "rocm-base-content-hash" "${base_hash}"
+    metadata_set "rocm-base-content-files-hash" "${content_files_hash}"
+    metadata_set "rocm-base-content-files" "${content_files}"
+    metadata_set "rocm-base-content-args" "${content_args}"
+    metadata_set "rocm-base-base-image-digest" "${base_image_digest}"
+    metadata_set "rocm-base-dockerfile" "${DOCKERFILE}"
+    metadata_set "rocm-base-descriptor" "${descriptor}"
+    metadata_set "rocm-base-dependency-summary" "${dependency_summary}"
+    metadata_set "rocm-base-dependency-rocm" "${rocm_version}"
+    metadata_set "rocm-base-dependency-python" "${python_version_arg}"
+    metadata_set "rocm-base-dependency-pytorch" "${pytorch_arg}"
+    metadata_set "rocm-base-dependency-torchvision" "${pytorch_vision_arg}"
+    metadata_set "rocm-base-dependency-torchaudio" "${pytorch_audio_arg}"
+    metadata_set "rocm-base-dependency-triton" "${triton_arg}"
+    metadata_set "rocm-base-dependency-flash-attention" "${fa_arg}"
+    metadata_set "rocm-base-dependency-aiter" "${aiter_arg}"
+    metadata_set "rocm-base-dependency-mori" "${mori_arg}"
+    metadata_set "rocm-base-pytorch-rocm-arch" "${pytorch_rocm_arch_arg}"
+    metadata_set "rocm-ci-image-descriptive" "${ci_descriptive_tag}"
+
+    echo "--- :white_check_mark: ROCm base image published"
+    echo "Use BASE_IMAGE=${descriptive_tag} for downstream ROCm CI builds"
+}
+
+main() {
+    metadata_set "rocm-base-refresh" "0"
+
+    if ! rocm_base_changed; then
+        echo "ROCm base Dockerfile did not change; skipping base image refresh"
+        return 0
+    fi
+
+    setup_builder
+    build_base_image
+}
+
+main "$@"

.buildkite/scripts/rocm/smoke-test-image.sh

@@ -0,0 +1,32 @@
+#!/usr/bin/env bash
+# Fast structural smoke test for the full ROCm CI image.
+
+set -euo pipefail
+
+image_ref="${VLLM_CI_SMOKE_IMAGE:-rocm/vllm-ci:${BUILDKITE_COMMIT:?BUILDKITE_COMMIT is required}}"
+
+docker run --rm --network=none --entrypoint /bin/bash "${image_ref}" -ec '
+  if [ ! -d /vllm-workspace ]; then echo Missing directory: /vllm-workspace >&2; exit 1; fi
+  if [ ! -d /vllm-workspace/tests ]; then echo Missing directory: /vllm-workspace/tests >&2; exit 1; fi
+  if [ ! -d /vllm-workspace/src/vllm ]; then echo Missing directory: /vllm-workspace/src/vllm >&2; exit 1; fi
+  if [ ! -x /vllm-workspace/src/vllm/vllm-rs ]; then echo Missing executable: /vllm-workspace/src/vllm/vllm-rs >&2; exit 1; fi
+
+  command -v python3
+  command -v uv
+  command -v pytest
+
+  if ! command -v amd-smi >/dev/null 2>&1 && ! command -v rocminfo >/dev/null 2>&1; then
+    echo No ROCm CLI found in image >&2
+    exit 1
+  fi
+
+  python3 - <<PY
+import torch
+import vllm
+
+print(torch.__version__)
+print(vllm.__version__)
+PY
+
+  echo AMD image smoke OK
+'

.buildkite/scripts/run-multi-node-test.sh

@@ -109,7 +109,9 @@ run_nodes() {
         if [ "$node" -ne 0 ]; then
             docker exec -d "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
         else
-            docker exec "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
+            # Allocate a TTY (-t -i) for the foreground head node so its output
+            # keeps ANSI color in the Buildkite log (see run-amd-test.sh).
+            docker exec -t -i "node$node" /bin/bash -c "cd $WORKING_DIR ; ${COMMANDS[$node]}"
         fi
     done
 }

.buildkite/scripts/run-rust-frontend-cargo-ci.sh

@@ -8,7 +8,12 @@ if [[ "$MODE" != "style-clippy" && "$MODE" != "test" ]]; then
   exit 2
 fi
 
-ROOT_DIR="$(git rev-parse --show-toplevel)"
+if ROOT_DIR="$(git rev-parse --show-toplevel 2>/dev/null)"; then
+  :
+else
+  SCRIPT_DIR="$(cd -- "$(dirname -- "${BASH_SOURCE[0]}")" && pwd -P)"
+  ROOT_DIR="$(cd -- "${SCRIPT_DIR}/../.." && pwd -P)"
+fi
 cd "$ROOT_DIR"
 
 export CARGO_TERM_COLOR="${CARGO_TERM_COLOR:-always}"
@@ -16,16 +21,21 @@ export CARGO_HOME="${CARGO_HOME:-$HOME/.cargo}"
 export RUSTUP_HOME="${RUSTUP_HOME:-$HOME/.rustup}"
 export PATH="$CARGO_HOME/bin:$PATH"
 
+PROTOC_VERSION="${PROTOC_VERSION:-31.1}"
+CARGO_BINSTALL_VERSION="${CARGO_BINSTALL_VERSION:-1.20.1}"
+UV_VERSION="${UV_VERSION:-0.11.28}"
+PYO3_PYTHON_VERSION="${PYO3_PYTHON_VERSION:-3.12}"
+
+CARGO_SORT_VERSION_REQ="${CARGO_SORT_VERSION_REQ:-2}"
+CARGO_DENY_VERSION_REQ="${CARGO_DENY_VERSION_REQ:-0.20}"
+CARGO_NEXTEST_VERSION_REQ="${CARGO_NEXTEST_VERSION_REQ:-0.9}"
+CARGO_LLVM_COV_VERSION="${CARGO_LLVM_COV_VERSION:-0.8.7}"
+
 log_section() {
   echo "--- $*"
 }
 
 install_protoc() {
-  if command -v protoc >/dev/null 2>&1; then
-    return
-  fi
-
-  local version="${PROTOC_VERSION:-31.1}"
   local arch
   case "$(uname -m)" in
     x86_64)
@@ -40,16 +50,17 @@ install_protoc() {
       ;;
   esac
 
-  local url="https://github.com/protocolbuffers/protobuf/releases/download/v${version}/protoc-${version}-linux-${arch}.zip"
+  local url="https://github.com/protocolbuffers/protobuf/releases/download/v${PROTOC_VERSION}/protoc-${PROTOC_VERSION}-linux-${arch}.zip"
   local tmp_dir
   tmp_dir="$(mktemp -d)"
 
-  log_section "Installing protoc ${version}"
+  log_section "Installing protoc ${PROTOC_VERSION}"
   curl -L --proto '=https' --tlsv1.2 -sSf "$url" -o "$tmp_dir/protoc.zip"
   mkdir -p "$CARGO_HOME/bin"
   unzip -q "$tmp_dir/protoc.zip" bin/protoc 'include/*' -d "$CARGO_HOME"
   chmod +x "$CARGO_HOME/bin/protoc"
   rm -rf "$tmp_dir"
+  protoc --version
 }
 
 rust_toolchain() {
@@ -70,66 +81,60 @@ install_rust_toolchain() {
 }
 
 install_cargo_binstall() {
-  if command -v cargo-binstall >/dev/null 2>&1; then
-    return
-  fi
-
-  log_section "Installing cargo-binstall"
+  log_section "Installing cargo-binstall ${CARGO_BINSTALL_VERSION}"
   curl -L --proto '=https' --tlsv1.2 -sSf \
-    https://raw.githubusercontent.com/cargo-bins/cargo-binstall/main/install-from-binstall-release.sh \
-    | bash
+    "https://raw.githubusercontent.com/cargo-bins/cargo-binstall/v${CARGO_BINSTALL_VERSION}/install-from-binstall-release.sh" \
+    | env BINSTALL_VERSION="$CARGO_BINSTALL_VERSION" bash
+  cargo-binstall -V
 }
 
 install_cargo_sort() {
-  if command -v cargo-sort >/dev/null 2>&1; then
-    return
-  fi
-
-  log_section "Installing cargo-sort"
-  install_cargo_binstall
-  cargo binstall --no-confirm cargo-sort
+  log_section "Installing cargo-sort ${CARGO_SORT_VERSION_REQ}"
+  cargo binstall --no-confirm --force "cargo-sort@${CARGO_SORT_VERSION_REQ}"
 }
 
 install_cargo_deny() {
-  if command -v cargo-deny >/dev/null 2>&1; then
-    return
-  fi
-
-  log_section "Installing cargo-deny"
-  install_cargo_binstall
-  cargo binstall --no-confirm cargo-deny
+  log_section "Installing cargo-deny ${CARGO_DENY_VERSION_REQ}"
+  cargo binstall --no-confirm --force "cargo-deny@${CARGO_DENY_VERSION_REQ}"
 }
 
 install_cargo_nextest() {
-  if command -v cargo-nextest >/dev/null 2>&1; then
-    return
-  fi
+  log_section "Installing cargo-nextest ${CARGO_NEXTEST_VERSION_REQ}"
+  cargo binstall \
+    --no-confirm \
+    --force \
+    --secure \
+    "cargo-nextest@${CARGO_NEXTEST_VERSION_REQ}"
+}
 
-  log_section "Installing cargo-nextest"
-  install_cargo_binstall
-  cargo binstall --no-confirm --secure cargo-nextest
+install_cargo_llvm_cov() {
+  log_section "Installing cargo-llvm-cov ${CARGO_LLVM_COV_VERSION}"
+  local toolchain
+  toolchain="$(rust_toolchain)"
+  rustup component add --toolchain "$toolchain" llvm-tools-preview
+  cargo binstall \
+    --no-confirm \
+    --force \
+    --secure \
+    "cargo-llvm-cov@${CARGO_LLVM_COV_VERSION}"
 }
 
 install_uv() {
-  if command -v uv >/dev/null 2>&1; then
-    return
-  fi
-
-  log_section "Installing uv"
-  curl -LsSf --proto '=https' --tlsv1.2 https://astral.sh/uv/install.sh \
+  log_section "Installing uv ${UV_VERSION}"
+  curl -L --proto '=https' --tlsv1.2 -sSf \
+    "https://github.com/astral-sh/uv/releases/download/${UV_VERSION}/uv-installer.sh" \
     | env UV_INSTALL_DIR="$CARGO_HOME/bin" sh
+  uv --version
 }
 
 setup_pyo3_python() {
-  local python_version="${PYO3_PYTHON_VERSION:-3.12}"
-
-  log_section "Installing Python ${python_version} for PyO3 tests"
-  uv python install "$python_version"
+  log_section "Installing Python ${PYO3_PYTHON_VERSION} for PyO3 tests"
+  uv python install "$PYO3_PYTHON_VERSION"
   PYO3_PYTHON="$(uv python find \
     --managed-python \
     --no-project \
     --resolve-links \
-    "$python_version")"
+    "$PYO3_PYTHON_VERSION")"
   export PYO3_PYTHON
 
   local python_libdir
@@ -151,6 +156,7 @@ PY
 }
 
 run_style_clippy() {
+  install_cargo_binstall
   install_cargo_sort
   install_cargo_deny
 
@@ -163,8 +169,8 @@ run_style_clippy() {
   log_section "Checking Rust dependency bans"
   cargo deny \
     --manifest-path rust/Cargo.toml \
-    check \
     --config rust/deny.toml \
+    check \
     bans
 
   log_section "Running clippy"
@@ -181,15 +187,43 @@ run_style_clippy() {
 run_tests() {
   install_uv
   setup_pyo3_python
+  install_cargo_binstall
   install_cargo_nextest
+  install_cargo_llvm_cov
 
-  log_section "Running cargo nextest"
-  cargo nextest run \
+  log_section "Running cargo nextest with Rust coverage"
+  mkdir -p artifacts
+  export LLVM_PROFILE_FILE_NAME="vllm-rust-unit-%4m.profraw"
+  cargo llvm-cov clean \
+    --manifest-path rust/Cargo.toml \
+    --profraw-only
+
+  set +e
+  cargo llvm-cov nextest \
     --manifest-path rust/Cargo.toml \
     --workspace \
     --all-features \
     --locked \
-    --no-fail-fast
+    --no-fail-fast \
+    --no-clean \
+    --lcov \
+    --output-path artifacts/rust-unit.lcov \
+    --ignore-filename-regex='/\.cargo/(registry|git)/|/rustc/|/target/'
+  local coverage_rc=$?
+
+  local upload_rc=0
+  if [[ $coverage_rc -eq 0 ]]; then
+    # shellcheck source=.buildkite/scripts/rust-coverage.sh
+    source .buildkite/scripts/rust-coverage.sh
+    rust_coverage_upload artifacts/rust-unit.lcov rust-unit
+    upload_rc=$?
+  fi
+  set -e
+
+  if [[ $coverage_rc -ne 0 ]]; then
+    return "$coverage_rc"
+  fi
+  return "$upload_rc"
 }
 
 install_protoc

.buildkite/scripts/rust-coverage.sh

@@ -0,0 +1,182 @@
+#!/bin/sh
+
+RUST_CODECOV_VERSION="v11.3.1"
+RUST_CODECOV_SHA256="ca1d64196d2d34771084afe76ea657d581bf628e31d993ff8e52ea09cc88a56d"
+
+rust_coverage_repo_root() {
+    if [ -f /vllm-workspace/.buildkite/scripts/rust-coverage.sh ]; then
+        printf '%s\n' /vllm-workspace
+    elif [ -n "${BUILDKITE_BUILD_CHECKOUT_PATH:-}" ] \
+        && [ -d "$BUILDKITE_BUILD_CHECKOUT_PATH" ]; then
+        printf '%s\n' "$BUILDKITE_BUILD_CHECKOUT_PATH"
+    else
+        git rev-parse --show-toplevel
+    fi
+}
+
+rust_coverage_start() {
+    RUST_COVERAGE_FLAG=${1:?coverage flag is required}
+    RUST_COVERAGE_DIR="/tmp/vllm-rust-coverage/${BUILDKITE_JOB_ID:-local}"
+    export RUST_COVERAGE_FLAG RUST_COVERAGE_DIR
+    mkdir -p "$RUST_COVERAGE_DIR"
+    LLVM_PROFILE_FILE="$RUST_COVERAGE_DIR/rust-%4m.profraw"
+    export LLVM_PROFILE_FILE
+    trap rust_coverage_finalize 0
+}
+
+rust_coverage_objects() {
+    rust_cov_objects_manifest="$(dirname "$(command -v llvm-cov)")/../objects"
+    python3 - "$rust_cov_objects_manifest" <<'PY'
+from pathlib import Path
+import sys
+
+for relative in Path(sys.argv[1]).read_text().splitlines():
+    for entry in sys.path:
+        path = Path(entry or ".").resolve() / relative
+        if path.is_file():
+            print(path)
+            break
+    else:
+        raise RuntimeError(f"installed Rust coverage object was not found: {relative}")
+PY
+}
+
+rust_coverage_collect() {
+    rust_cov_collect_flag=${1:?coverage flag is required}
+    rust_cov_collect_lcov="$RUST_COVERAGE_DIR/$rust_cov_collect_flag.lcov"
+
+    rust_cov_collect_objects=$(rust_coverage_objects) || return 1
+    rust_cov_collect_primary=
+    set --
+    while IFS= read -r rust_cov_collect_object; do
+        if [ -z "$rust_cov_collect_primary" ]; then
+            rust_cov_collect_primary=$rust_cov_collect_object
+        else
+            set -- "$@" "--object=$rust_cov_collect_object"
+        fi
+    done <<EOF
+$rust_cov_collect_objects
+EOF
+
+    llvm-profdata merge \
+        -sparse \
+        "$RUST_COVERAGE_DIR"/*.profraw \
+        -o "$RUST_COVERAGE_DIR/merged.profdata" || return 1
+    llvm-cov export \
+        "$rust_cov_collect_primary" \
+        "$@" \
+        --format=lcov \
+        --instr-profile="$RUST_COVERAGE_DIR/merged.profdata" \
+        --ignore-filename-regex='/\.cargo/(registry|git)/|/rustc/|/target/' \
+        > "$rust_cov_collect_lcov" || return 1
+    RUST_COVERAGE_LCOV=$rust_cov_collect_lcov
+    export RUST_COVERAGE_LCOV
+}
+
+rust_coverage_upload() {
+    rust_cov_upload_lcov=${1:?LCOV path is required}
+    rust_cov_upload_flag=${2:?coverage flag is required}
+    rust_cov_upload_repo_root=$(rust_coverage_repo_root) || return 1
+
+    if [ "$(uname -m)" != "x86_64" ]; then
+        echo "Rust coverage upload currently supports x86_64 CI agents" >&2
+        return 1
+    fi
+
+    rust_cov_upload_codecov_dir=$(mktemp -d /tmp/codecov-bin.XXXXXX) \
+        || return 1
+    curl -fsSL \
+        "https://github.com/codecov/codecov-cli/releases/download/${RUST_CODECOV_VERSION}/codecovcli_linux" \
+        -o "$rust_cov_upload_codecov_dir/codecov" || return 1
+    echo "$RUST_CODECOV_SHA256  $rust_cov_upload_codecov_dir/codecov" \
+        | sha256sum -c - || return 1
+    chmod +x "$rust_cov_upload_codecov_dir/codecov" || return 1
+
+    rust_cov_upload_slug="vllm-project/vllm"
+    if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
+        && [ "${BUILDKITE_PULL_REQUEST}" != "false" ] \
+        && [ -n "${BUILDKITE_PULL_REQUEST_REPO:-}" ]; then
+        rust_cov_upload_slug=$(echo "$BUILDKITE_PULL_REQUEST_REPO" \
+            | sed -E 's#(git@|https?://)([^/:]+)[:/]([^/]+/[^/.]+)(\.git)?$#\3#')
+        case "$rust_cov_upload_slug" in
+            */*) ;;
+            *) rust_cov_upload_slug="vllm-project/vllm" ;;
+        esac
+    fi
+
+    rust_cov_upload_branch=${BUILDKITE_BRANCH:?BUILDKITE_BRANCH is required}
+    if [ -z "${CODECOV_TOKEN:-}" ]; then
+        # Codecov accepts tokenless public uploads on unprotected branch names.
+        # A colon-separated prefix keeps feature-branch and fork uploads from
+        # requiring a repository secret.
+        if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
+            && [ "${BUILDKITE_PULL_REQUEST}" != "false" ]; then
+            rust_cov_upload_branch="pr${BUILDKITE_PULL_REQUEST}:$rust_cov_upload_branch"
+        else
+            rust_cov_upload_branch="buildkite:$rust_cov_upload_branch"
+        fi
+    fi
+
+    set --
+    set -- "$@" upload-process
+    set -- "$@" --file "$rust_cov_upload_lcov"
+    # LCOV paths are mapped server-side by codecov.yml. Skip the CLI's local
+    # source-line fix scanning, which is unrelated to path mapping.
+    set -- "$@" --disable-search --disable-file-fixes
+    set -- "$@" --fail-on-error --git-service github
+    set -- "$@" --build "${BUILDKITE_BUILD_NUMBER:?BUILDKITE_BUILD_NUMBER is required}"
+    set -- "$@" --branch "$rust_cov_upload_branch"
+    set -- "$@" --sha "${BUILDKITE_COMMIT:?BUILDKITE_COMMIT is required}"
+    set -- "$@" --slug "$rust_cov_upload_slug"
+    set -- "$@" --flag "$rust_cov_upload_flag"
+    set -- "$@" --name "${rust_cov_upload_flag}-${BUILDKITE_JOB_ID:?BUILDKITE_JOB_ID is required}"
+    set -- "$@" --dir "$rust_cov_upload_repo_root"
+    set -- "$@" --network-root-folder "$rust_cov_upload_repo_root"
+    if [ -n "${BUILDKITE_PULL_REQUEST:-}" ] \
+        && [ "${BUILDKITE_PULL_REQUEST}" != "false" ]; then
+        set -- "$@" --pr "$BUILDKITE_PULL_REQUEST"
+    fi
+
+    rust_cov_upload_log="$rust_cov_upload_codecov_dir/codecov.log"
+    # E2E steps run from tests/, so execute from the repository root to resolve
+    # codecov.yml and repository paths consistently.
+    (
+        cd "$rust_cov_upload_repo_root" || exit 1
+        "$rust_cov_upload_codecov_dir/codecov" "$@"
+    ) >"$rust_cov_upload_log" 2>&1
+    rust_cov_upload_rc=$?
+    cat "$rust_cov_upload_log"
+    # v11.3.1 can log API failures while returning zero even with
+    # --fail-on-error. Preserve the strict CI contract explicitly.
+    if grep -aEq 'error.* -- ' "$rust_cov_upload_log"; then
+        echo "Codecov CLI reported an upload error" >&2
+        rust_cov_upload_rc=1
+    fi
+    rm -rf "$rust_cov_upload_codecov_dir"
+    return "$rust_cov_upload_rc"
+}
+
+rust_coverage_finalize() {
+    rust_cov_finalize_test_rc=$?
+    trap - 0
+    set +e
+
+    rust_coverage_collect "$RUST_COVERAGE_FLAG"
+    rust_cov_finalize_collect_rc=$?
+
+    rust_cov_finalize_upload_rc=0
+    if [ "$rust_cov_finalize_collect_rc" -eq 0 ]; then
+        rust_coverage_upload "$RUST_COVERAGE_LCOV" "$RUST_COVERAGE_FLAG"
+        rust_cov_finalize_upload_rc=$?
+    fi
+
+    find "$RUST_COVERAGE_DIR" -type f -name '*.profraw' -delete
+
+    if [ "$rust_cov_finalize_test_rc" -ne 0 ]; then
+        exit "$rust_cov_finalize_test_rc"
+    fi
+    if [ "$rust_cov_finalize_collect_rc" -ne 0 ]; then
+        exit "$rust_cov_finalize_collect_rc"
+    fi
+    exit "$rust_cov_finalize_upload_rc"
+}

.buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_dp4_async_eplb.sh

@@ -18,6 +18,10 @@ wait_for_server() {
 
 MODEL="Qwen/Qwen3-30B-A3B-FP8"
 BACK="allgather_reducescatter"
+if command -v rocm-smi &> /dev/null || [[ -d /opt/rocm ]] || [[ -n "${ROCM_PATH:-}" ]]; then
+  # Disable MOE padding for ROCm since it is causing eplb to fail.
+  export VLLM_ROCM_MOE_PADDING=0
+fi
 
 cleanup() {
   if [[ -n "${SERVER_PID:-}" ]] && kill -0 "${SERVER_PID}" 2>/dev/null; then

.buildkite/scripts/trigger-ci-build.sh

@@ -23,6 +23,7 @@ NC='\033[0m' # No Color
 # Default configuration
 PIPELINE="ci"
 DRY_RUN=true
+TORCH_NIGHTLY=false
 
 usage() {
     cat <<EOF
@@ -34,12 +35,14 @@ Sets RUN_ALL=1 and NIGHTLY=1 environment variables.
 SAFETY: Dry-run by default. Use --execute to actually trigger a build.
 
 Options:
-    --execute       Actually trigger the build (default: dry-run)
-    --pipeline      Buildkite pipeline slug (default: ${PIPELINE})
-    --commit        Override commit SHA (default: current HEAD)
-    --branch        Override branch name (default: current branch)
-    --message       Custom build message (default: auto-generated)
-    --help          Show this help message
+    --execute        Actually trigger the build (default: dry-run)
+    --pipeline       Buildkite pipeline slug (default: ${PIPELINE})
+    --commit         Override commit SHA (default: current HEAD)
+    --branch         Override branch name (default: current branch)
+    --message        Custom build message (default: auto-generated)
+    --torch-nightly  Also build and run the full suite against torch nightly
+                     (sets TORCH_NIGHTLY=1)
+    --help           Show this help message
 
 Prerequisites:
     - bk CLI installed: brew tap buildkite/buildkite && brew install buildkite/buildkite/bk
@@ -49,6 +52,7 @@ Examples:
     $(basename "$0")                        # Dry-run, show what would happen
     $(basename "$0") --execute              # Actually trigger the build
     $(basename "$0") --pipeline ci-shadow   # Dry-run with different pipeline
+    $(basename "$0") --torch-nightly        # Dry-run a full torch-nightly run
 EOF
     exit 1
 }
@@ -96,6 +100,10 @@ while [[ $# -gt 0 ]]; do
             MESSAGE="$2"
             shift 2
             ;;
+        --torch-nightly)
+            TORCH_NIGHTLY=true
+            shift
+            ;;
         --help|-h)
             usage
             ;;
@@ -171,11 +179,17 @@ if [[ $(echo "$REMOTE_BRANCHES" | wc -l) -gt 5 ]]; then
 fi
 echo ""
 
+# Environment variables passed to the build.
+BUILD_ENV=("RUN_ALL=1" "NIGHTLY=1")
+if [[ "$TORCH_NIGHTLY" == true ]]; then
+    BUILD_ENV+=("TORCH_NIGHTLY=1")
+fi
+
 log_info "Pipeline: ${PIPELINE}"
 log_info "Branch: ${BRANCH}"
 log_info "Commit: ${COMMIT}"
 log_info "Message: ${MESSAGE}"
-log_info "Environment: RUN_ALL=1, NIGHTLY=1"
+log_info "Environment: ${BUILD_ENV[*]}"
 echo ""
 
 # Build the command
@@ -187,9 +201,10 @@ CMD=(bk build create
     --commit "${COMMIT}"
     --branch "${BRANCH}"
     --message "${MESSAGE}"
-    --env "RUN_ALL=1"
-    --env "NIGHTLY=1"
 )
+for env_var in "${BUILD_ENV[@]}"; do
+    CMD+=(--env "${env_var}")
+done
 
 if [[ "$DRY_RUN" == true ]]; then
     echo "=========================================="
@@ -210,8 +225,14 @@ if [[ "$DRY_RUN" == true ]]; then
     echo "    --commit '$(escape_for_shell "${COMMIT}")' \\"
     echo "    --branch '$(escape_for_shell "${BRANCH}")' \\"
     echo "    --message '$(escape_for_shell "${MESSAGE}")' \\"
-    echo "    --env 'RUN_ALL=1' \\"
-    echo "    --env 'NIGHTLY=1'"
+    last_idx=$(( ${#BUILD_ENV[@]} - 1 ))
+    for i in "${!BUILD_ENV[@]}"; do
+        if [[ $i -eq $last_idx ]]; then
+            echo "    --env '$(escape_for_shell "${BUILD_ENV[$i]}")'"
+        else
+            echo "    --env '$(escape_for_shell "${BUILD_ENV[$i]}")' \\"
+        fi
+    done
     echo ""
     echo "=========================================="
     echo -e "${YELLOW}To actually trigger this build, run:${NC}"

.buildkite/scripts/upload-nightly-wheels.sh

@@ -6,8 +6,14 @@ set -ex
 # manylinux platform tag with auditwheel.
 # Index generation is handled separately by generate-and-upload-nightly-index.sh.
 
-# shellcheck source=lib/manylinux.sh
-source .buildkite/scripts/lib/manylinux.sh
+# auditwheel is Linux-only; macOS wheels already carry a valid tag, so skip the
+# manylinux retag for them.
+WHEEL_PLATFORM="${VLLM_WHEEL_PLATFORM:-linux}"
+
+if [[ "$WHEEL_PLATFORM" == "linux" ]]; then
+  # shellcheck source=lib/manylinux.sh
+  source .buildkite/scripts/lib/manylinux.sh
+fi
 
 BUCKET="vllm-wheels"
 SUBPATH=$BUILDKITE_COMMIT
@@ -27,8 +33,10 @@ wheel="${wheel_files[0]}"
 
 # ========= detect manylinux tag and rename ==========
 
-wheel="$(apply_manylinux_tag "$wheel")"
-echo "Renamed wheel to: $wheel"
+if [[ "$WHEEL_PLATFORM" == "linux" ]]; then
+  wheel="$(apply_manylinux_tag "$wheel")"
+  echo "Renamed wheel to: $wheel"
+fi
 
 # Extract the version from the wheel
 version=$(unzip -p "$wheel" '**/METADATA' | grep '^Version: ' | cut -d' ' -f2)

.buildkite/scripts/upload-rocm-wheels.sh

@@ -113,8 +113,8 @@ $PYTHON .buildkite/scripts/generate-nightly-index.py \
 echo "Uploading indices to $S3_COMMIT_PREFIX"
 aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "$S3_COMMIT_PREFIX"
 
-# Update rocm/nightly/ if on main branch and not a PR
-if [[ "$BUILDKITE_BRANCH" == "main" && "$BUILDKITE_PULL_REQUEST" == "false" ]] || [[ "$NIGHTLY" == "1" ]]; then
+# Only scheduled nightly builds should update the moving nightly index.
+if [[ "${NIGHTLY:-0}" == "1" ]]; then
     echo "Updating rocm/nightly/ index..."
     aws s3 cp --recursive "$INDICES_OUTPUT_DIR/" "s3://$BUCKET/rocm/nightly/"
 fi
@@ -147,7 +147,7 @@ echo ""
 echo "Install command (by commit):"
 echo "  pip install vllm --extra-index-url https://${BUCKET}.s3.amazonaws.com/$ROCM_SUBPATH/"
 echo ""
-if [[ "$BUILDKITE_BRANCH" == "main" ]] || [[ "$NIGHTLY" == "1" ]]; then
+if [[ "${NIGHTLY:-0}" == "1" ]]; then
     echo "Install command (nightly):"
     echo "  pip install vllm --extra-index-url https://${BUCKET}.s3.amazonaws.com/rocm/nightly/"
 fi

.buildkite/scripts/xpu/create-xpu-ecr-manifest.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+set -euo pipefail
+
+REGISTRY="public.ecr.aws/q9t5s3a7"
+REPO="vllm-release-repo"
+ARCH_TAG="${BUILDKITE_COMMIT}-$(uname -m)-xpu"
+PLATFORM_TAG="${BUILDKITE_COMMIT}-xpu"
+
+aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin ${REGISTRY}
+docker manifest rm ${REGISTRY}/${REPO}:${PLATFORM_TAG} || true
+docker manifest create ${REGISTRY}/${REPO}:${PLATFORM_TAG} ${REGISTRY}/${REPO}:${ARCH_TAG} --amend
+docker manifest push ${REGISTRY}/${REPO}:${PLATFORM_TAG}

.buildkite/scripts/xpu/push-nightly-builds-xpu.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+
+set -ex
+
+ORIG_TAG_NAME="$BUILDKITE_COMMIT"
+REPO="vllm/vllm-openai-xpu"
+
+echo "Pushing original XPU tag ${ORIG_TAG_NAME}-xpu to nightly tags in ${REPO}"
+
+aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:"$ORIG_TAG_NAME"-x86_64-xpu
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:"$ORIG_TAG_NAME"-x86_64-xpu ${REPO}:nightly-x86_64
+docker push ${REPO}:nightly-x86_64
+
+docker manifest rm ${REPO}:nightly || true
+docker manifest rm ${REPO}:nightly-"$BUILDKITE_COMMIT" || true
+docker manifest create ${REPO}:nightly ${REPO}:nightly-x86_64 --amend
+docker manifest create ${REPO}:nightly-"$BUILDKITE_COMMIT" ${REPO}:nightly-x86_64 --amend
+docker manifest push ${REPO}:nightly
+docker manifest push ${REPO}:nightly-"$BUILDKITE_COMMIT"

.buildkite/test_areas/attention.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: V1 attention (H100-MI300)
   key: v1-attention-h100-mi300
-  timeout_in_minutes: 30
+  timeout_in_minutes: 85
   device: h100
   source_file_dependencies:
     - vllm/config/attention.py
@@ -12,11 +12,12 @@ steps:
     - vllm/v1/attention
     - tests/v1/attention
   commands:
-    - pytest -v -s v1/attention
+    - pytest -v -s v1/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 2
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 70
+      timeout_in_minutes: 95
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -30,7 +31,7 @@ steps:
 
 - label: V1 attention (B200)
   key: v1-attention-b200
-  timeout_in_minutes: 30
+  timeout_in_minutes: 80
   device: b200-k8s
   source_file_dependencies:
     - vllm/config/attention.py
@@ -38,4 +39,5 @@ steps:
     - vllm/v1/attention
     - tests/v1/attention
   commands:
-    - pytest -v -s v1/attention
+    - pytest -v -s v1/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 2

.buildkite/test_areas/basic_correctness.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Basic Correctness
   key: basic-correctness
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: h200_18gb
   source_file_dependencies:
   - vllm/
@@ -19,6 +19,6 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 50
+      timeout_in_minutes: 70
       depends_on:
       - image-build-amd

.buildkite/test_areas/benchmarks.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Benchmarks CLI Test
   key: benchmarks-cli-test
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
   - vllm/
@@ -13,6 +13,7 @@ steps:
   - pytest -v -s benchmarks/
   mirror:
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
@@ -23,7 +24,7 @@ steps:
   num_gpus: 2
   optional: true
   working_dir: "/vllm-workspace/"
-  timeout_in_minutes: 10
+  timeout_in_minutes: 20
   source_file_dependencies:
   - benchmarks/attention_benchmarks/
   - vllm/v1/attention/

.buildkite/test_areas/compile.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Sequence Parallel Correctness Tests (2 GPUs)
   key: sequence-parallel-correctness-tests-2-gpus
-  timeout_in_minutes: 50
+  timeout_in_minutes: 80
   working_dir: "/vllm-workspace/"
   num_devices: 2
   source_file_dependencies:
@@ -19,7 +19,7 @@ steps:
 
 - label: Sequence Parallel Correctness Tests (2xH100)
   key: sequence-parallel-correctness-tests-2xh100
-  timeout_in_minutes: 50
+  timeout_in_minutes: 75
   working_dir: "/vllm-workspace/"
   device: h100
   optional: true
@@ -30,7 +30,7 @@ steps:
 
 - label: AsyncTP Correctness Tests (2xH100)
   key: asynctp-correctness-tests-2xh100
-  timeout_in_minutes: 50
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
   device: h100
   optional: true
@@ -41,7 +41,7 @@ steps:
 
 - label: AsyncTP Correctness Tests (B200)
   key: asynctp-correctness-tests-b200
-  timeout_in_minutes: 50
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
   device: b200-k8s
   optional: true
@@ -52,7 +52,7 @@ steps:
 
 - label: Distributed Compile Unit Tests (2xH100)
   key: distributed-compile-unit-tests-2xh100
-  timeout_in_minutes: 20
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/"
   device: h100
   num_devices: 2
@@ -66,7 +66,7 @@ steps:
 
 - label: Fusion and Compile Unit Tests (2xB200)
   key: fusion-and-compile-unit-tests-2xb200
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
   device: b200-k8s
   source_file_dependencies:
@@ -96,7 +96,7 @@ steps:
 
 - label: Fusion E2E Quick (H100)
   key: fusion-e2e-quick-h100
-  timeout_in_minutes: 15
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/"
   device: h100
   num_devices: 1
@@ -115,7 +115,7 @@ steps:
 
 - label: Fusion E2E Config Sweep (H100)
   key: fusion-e2e-config-sweep-h100
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/"
   device: h100
   num_devices: 1
@@ -149,7 +149,7 @@ steps:
 
 - label: Fusion E2E TP2 Quick (H100)
   key: fusion-e2e-tp2-quick-h100
-  timeout_in_minutes: 20
+  timeout_in_minutes: 35
   working_dir: "/vllm-workspace/"
   device: h100
   num_devices: 2
@@ -167,7 +167,7 @@ steps:
 
 - label: Fusion E2E TP2 AR-RMS Config Sweep (H100)
   key: fusion-e2e-tp2-ar-rms-config-sweep-h100
-  timeout_in_minutes: 40
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
   device: h100
   num_devices: 2
@@ -207,7 +207,7 @@ steps:
 
 - label: Fusion E2E TP2 (B200)
   key: fusion-e2e-tp2-b200
-  timeout_in_minutes: 20
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/"
   device: b200-k8s
   num_devices: 2

.buildkite/test_areas/cuda.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Platform Tests
   key: platform-tests
-  timeout_in_minutes: 15
+  timeout_in_minutes: 20
   device: h200_18gb
   source_file_dependencies:
   - vllm/envs.py
@@ -18,8 +18,9 @@ steps:
     - pytest -v -s cuda/test_platform_no_cuda_init.py
 
 - label: Cudagraph
+  device: h200_35gb
   key: cudagraph
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   source_file_dependencies:
   - tests/v1/cudagraph
   - vllm/v1/cudagraph_dispatcher.py
@@ -28,4 +29,4 @@ steps:
   commands:
     - pytest -v -s v1/cudagraph/test_cudagraph_dispatch.py
     - pytest -v -s v1/cudagraph/test_cudagraph_mode.py
-    - pytest -v -s v1/cudagraph/test_breakable_cudagraph.py
+    - pytest -v -s v1/cudagraph/test_breakable_cudagraph.py

.buildkite/test_areas/disaggregated.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Distributed NixlConnector PD accuracy (4 GPUs)
   key: distributed-nixlconnector-pd-accuracy-4-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 55
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -15,8 +15,9 @@ steps:
     - bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
   mirror:
     amd:
+      dind: false
       device: mi300_4
-      timeout_in_minutes: 110
+      timeout_in_minutes: 85
       depends_on:
         - image-build-amd
       source_file_dependencies:
@@ -29,7 +30,7 @@ steps:
 
 - label: Distributed FlashInfer NixlConnector PD accuracy (4 GPUs)
   key: distributed-flashinfer-nixlconnector-pd-accuracy-4-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 55
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -39,6 +40,19 @@ steps:
     - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - FLASHINFER=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 
+- label: Push NixlConnector PP prefill PD accuracy (4 GPUs)
+  key: push-nixlconnector-pp-prefill-pd-accuracy-4-gpus
+  timeout_in_minutes: 30
+  working_dir: "/vllm-workspace/tests"
+  num_devices: 4
+  source_file_dependencies:
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
+    - tests/v1/kv_connector/nixl_integration/
+    - tests/v1/kv_connector/nixl_push_integration/
+  commands:
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
+    - bash v1/kv_connector/nixl_push_integration/config_sweep_accuracy_test.sh
+
 - label: DP EP Distributed NixlConnector PD accuracy tests (4 GPUs)
   key: dp-ep-distributed-nixlconnector-pd-accuracy-tests-4-gpus
   timeout_in_minutes: 30
@@ -52,8 +66,9 @@ steps:
     - DP_EP=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
   mirror:
     amd:
+      dind: false
       device: mi300_4
-      timeout_in_minutes: 50
+      timeout_in_minutes: 60
       depends_on:
         - image-build-amd
       source_file_dependencies:
@@ -66,7 +81,7 @@ steps:
 
 - label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (4 GPUs)
   key: crosslayer-kv-layout-distributed-nixlconnector-pd-accuracy-tests-4-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 55
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -77,8 +92,9 @@ steps:
     - CROSS_LAYERS_BLOCKS=True bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
   mirror:
     amd:
+      dind: false
       device: mi300_4
-      timeout_in_minutes: 110
+      timeout_in_minutes: 85
       depends_on:
         - image-build-amd
       source_file_dependencies:
@@ -91,7 +107,7 @@ steps:
 
 - label: Hybrid SSM NixlConnector PD accuracy tests (4 GPUs)
   key: hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus
-  timeout_in_minutes: 25
+  timeout_in_minutes: 60
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -102,8 +118,9 @@ steps:
     - HYBRID_SSM=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
   mirror:
     amd:
+      dind: false
       device: mi300_4
-      timeout_in_minutes: 60
+      timeout_in_minutes: 80
       depends_on:
         - image-build-amd
       source_file_dependencies:
@@ -130,7 +147,7 @@ steps:
 
 - label: MultiConnector (Nixl+Offloading) PD accuracy (2 GPUs)
   key: multiconnector-nixl-offloading-pd-accuracy-2-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -145,7 +162,7 @@ steps:
 
 - label: NixlConnector PD + Spec Decode acceptance (2 GPUs)
   key: nixlconnector-pd-spec-decode-acceptance-2-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: a100
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
@@ -158,8 +175,9 @@ steps:
     - bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
   mirror:
     amd:
+      dind: false
       device: mi300_2
-      timeout_in_minutes: 60
+      timeout_in_minutes: 70
       depends_on:
         - image-build-amd
       source_file_dependencies:
@@ -169,11 +187,11 @@ steps:
         - vllm/platforms/rocm.py
       commands:
         - uv pip install --system -r /vllm-workspace/requirements/kv_connectors_rocm.txt
-        - ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
+        - KV_CACHE_MEMORY_BYTES=8G ATTENTION_BACKEND=TRITON_ATTN bash v1/kv_connector/nixl_integration/config_sweep_spec_decode_test.sh
 
 - label: MultiConnector (Nixl+Offloading) PD edge cases (2 GPUs)
   key: multiconnector-nixl-offloading-pd-edge-cases-2-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -185,3 +203,25 @@ steps:
   commands:
     - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
+
+# P TP 4 - D DPEP 4 test case for DSv4-Flash
+- label: DSv4-Flash Disaggregated DP EP
+  key: dsv4-flash-disaggregated
+  timeout_in_minutes: 60
+  device: h200
+  optional: true
+  working_dir: "/vllm-workspace/tests"
+  num_devices: 8
+  env:
+    ENABLE_HMA_FLAG: "1"
+    DP_EP: "1"
+    GPU_MEMORY_UTILIZATION: "0.85"
+    PREFILLER_TP_SIZE: "4"
+    DECODER_TP_SIZE: "4"
+    PREFILL_BLOCK_SIZE: "256"
+    DECODE_BLOCK_SIZE: "256"
+    MODEL_NAMES: "deepseek-ai/DeepSeek-V4-Flash"
+    VLLM_SERVE_EXTRA_ARGS: "--trust-remote-code,--kv-cache-dtype,fp8"
+  commands:
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
+    - bash v1/kv_connector/nixl_integration/run_accuracy_test.sh

.buildkite/test_areas/distributed.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Distributed Comm Ops
   key: distributed-comm-ops
-  timeout_in_minutes: 20
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -18,7 +18,7 @@ steps:
 
 - label: Distributed DP Tests (2 GPUs)
   key: distributed-dp-tests-2-gpus
-  timeout_in_minutes: 20
+  timeout_in_minutes: 35
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -39,6 +39,7 @@ steps:
   - DP_SIZE=2 pytest -v -s entrypoints/openai/test_multi_api_servers.py
   mirror:
     amd:
+      dind: false
       device: mi300_2
       depends_on:
       - image-build-amd
@@ -55,7 +56,7 @@ steps:
 
 - label: Distributed Compile + RPC Tests (2 GPUs)
   key: distributed-compile-rpc-tests-2-gpus
-  timeout_in_minutes: 20
+  timeout_in_minutes: 65
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -78,7 +79,7 @@ steps:
 
 - label: Distributed Torchrun + Shutdown Tests (2 GPUs)
   key: distributed-torchrun-shutdown-tests-2-gpus
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -133,7 +134,7 @@ steps:
 
 - label: Distributed DP Tests (4 GPUs)
   key: distributed-dp-tests-4-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -154,7 +155,7 @@ steps:
 
 - label: Distributed Compile + Comm (4 GPUs)
   key: distributed-compile-comm-4-gpus
-  timeout_in_minutes: 30
+  timeout_in_minutes: 70
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -176,7 +177,7 @@ steps:
 
 - label: Distributed Tests (8xH100)
   key: distributed-tests-8xh100
-  timeout_in_minutes: 10
+  timeout_in_minutes: 20
   device: h100
   num_devices: 8
   working_dir: "/vllm-workspace/tests"
@@ -212,7 +213,7 @@ steps:
 
 - label: Distributed Tests (2xH100-2xMI300)
   key: distributed-tests-2xh100-2xmi300
-  timeout_in_minutes: 15
+  timeout_in_minutes: 30
   device: h100
   optional: true
   working_dir: "/vllm-workspace/"
@@ -233,7 +234,7 @@ steps:
   num_devices: 2
   commands:
     - pytest -v -s tests/distributed/test_context_parallel.py
-    - pytest -v -s tests/distributed/test_nccl_symm_mem_allreduce.py
+    - pytest -v -s tests/distributed/test_nccl_symm_mem.py
     - pytest -v -s tests/v1/distributed/test_dbo.py
     - pytest -v -s tests/distributed/test_mnnvl_alltoall.py
 
@@ -259,7 +260,7 @@ steps:
 
 - label: Pipeline + Context Parallelism (4 GPUs)
   key: pipeline-context-parallelism-4-gpus
-  timeout_in_minutes: 60
+  timeout_in_minutes: 55
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -274,7 +275,7 @@ steps:
 
 - label: RayExecutorV2 (4 GPUs)
   key: rayexecutorv2-4-gpus
-  timeout_in_minutes: 60
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:

.buildkite/test_areas/docker.yaml

@@ -3,7 +3,7 @@ depends_on:
   - image-build-cpu
 steps:
 - label: Docker Build Metadata
-  timeout_in_minutes: 10
+  timeout_in_minutes: 20
   device: cpu-small
   source_file_dependencies:
     - .buildkite/release-pipeline.yaml

.buildkite/test_areas/e2e_integration.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: DeepSeek V2-Lite Sync EPLB Accuracy (4xH100)
   key: deepseek-v2-lite-sync-eplb-accuracy-4xh100
-  timeout_in_minutes: 60
+  timeout_in_minutes: 25
   device: h100
   optional: true
   num_devices: 4
@@ -14,7 +14,7 @@ steps:
 
 - label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (4xH100)
   key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-4xh100
-  timeout_in_minutes: 60
+  timeout_in_minutes: 25
   device: h100
   optional: true
   num_devices: 4
@@ -24,7 +24,7 @@ steps:
 
 - label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (2xB200)
   key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-2xb200
-  timeout_in_minutes: 60
+  timeout_in_minutes: 20
   device: b200-k8s
   optional: true
   num_devices: 2
@@ -34,7 +34,7 @@ steps:
 
 - label: Qwen3-30B-A3B-FP8 DP4 Async EPLB Accuracy
   key: qwen3-30b-a3b-fp8-dp4-async-eplb-accuracy
-  timeout_in_minutes: 60
+  timeout_in_minutes: 25
   device: h100
   optional: true
   num_devices: 4
@@ -44,7 +44,7 @@ steps:
 
 - label: DeepSeek V2-Lite Prefetch Offload Accuracy (H100)
   key: deepseek-v2-lite-prefetch-offload-accuracy-h100
-  timeout_in_minutes: 60
+  timeout_in_minutes: 20
   device: h100
   optional: true
   num_devices: 1

.buildkite/test_areas/engine.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Engine
   key: engine
-  timeout_in_minutes: 15
+  timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
   - vllm/compilation/
@@ -29,13 +29,13 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 60
+      timeout_in_minutes: 50
       depends_on:
       - image-build-amd
 
 - label: Engine (1 GPU)
   key: engine-1-gpu
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   source_file_dependencies:
     - vllm/v1/engine/
     - tests/v1/engine/
@@ -45,13 +45,13 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 40
+      timeout_in_minutes: 55
       depends_on:
       - image-build-amd
 
 - label: e2e Scheduling (1 GPU)
   key: e2e-scheduling-1-gpu
-  timeout_in_minutes: 30
+  timeout_in_minutes: 35
   device: h200_18gb
   source_file_dependencies:
     - vllm/v1/
@@ -60,15 +60,15 @@ steps:
     - pytest -v -s v1/e2e/general/test_async_scheduling.py
   mirror:
     amd:
-      device: mi250_1
-      timeout_in_minutes: 60
+      device: mi325_1
+      timeout_in_minutes: 70
       depends_on:
       - image-build-amd
 
 - label: e2e Core (1 GPU)
   device: h200_35gb
   key: e2e-core-1-gpu
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   source_file_dependencies:
     - vllm/v1/
     - tests/v1/e2e/general/
@@ -76,8 +76,8 @@ steps:
     - pytest -v -s v1/e2e/general --ignore v1/e2e/general/test_async_scheduling.py
   mirror:
     amd:
-      device: mi250_1
-      timeout_in_minutes: 35
+      device: mi325_1
+      timeout_in_minutes: 60
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -87,7 +87,7 @@ steps:
 
 - label: V1 e2e (2 GPUs)
   key: v1-e2e-2-gpus
-  timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
+  timeout_in_minutes: 25 # TODO: Fix timeout after we have more confidence in the test stability
   optional: true
   num_devices: 2
   source_file_dependencies:
@@ -114,13 +114,14 @@ steps:
     - pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "tensor_parallelism"
   mirror:
     amd:
+      dind: false
       device: mi300_2
       depends_on:
       - image-build-amd
 
 - label: V1 e2e (4 GPUs)
   key: v1-e2e-4-gpus
-  timeout_in_minutes: 60 # TODO: Fix timeout after we have more confidence in the test stability
+  timeout_in_minutes: 20 # TODO: Fix timeout after we have more confidence in the test stability
   optional: true
   num_devices: 4
   source_file_dependencies:
@@ -148,7 +149,7 @@ steps:
 
 - label: V1 e2e (4xH100)
   key: v1-e2e-4xh100
-  timeout_in_minutes: 60
+  timeout_in_minutes: 35
   device: h100
   num_devices: 4
   optional: true

.buildkite/test_areas/entrypoints.yaml

@@ -3,8 +3,9 @@ depends_on:
   - image-build
 steps:
 - label: Entrypoints Unit Tests
+  device: h200_35gb
   key: entrypoints-unit-tests
-  timeout_in_minutes: 10
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/entrypoints
@@ -15,8 +16,9 @@ steps:
   - pytest -v -s entrypoints/weight_transfer
 
 - label: Entrypoints Integration (LLM)
+  device: h200_35gb
   key: entrypoints-integration-llm
-  timeout_in_minutes: 40
+  timeout_in_minutes: 60
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
@@ -29,21 +31,25 @@ steps:
   mirror:
     amd:
       device: mi325_1
+      # TODO(akaratza): Test after Torch >= 2.12 bump
+      soft_fail: true
       depends_on:
       - image-build-amd
 
 - label: Entrypoints Integration (API Server)
   key: entrypoints-integration-api-server
   device: h200_35gb
-  timeout_in_minutes: 130
+  timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
   - tests/entrypoints/serve
+  - tests/entrypoints/scale_out
   commands:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - pytest -v -s entrypoints/serve --ignore=entrypoints/serve/dev/rpc
   - PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/serve/dev/rpc
+  - pytest -v -s entrypoints/scale_out
   mirror:
     amd:
       device: mi325_1
@@ -51,8 +57,9 @@ steps:
       - image-build-amd
 
 - label: Entrypoints Integration (API Server OpenAI - Part 1)
+  device: h200_35gb
   key: entrypoints-integration-api-server-openai-part-1
-  timeout_in_minutes: 50
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
@@ -64,13 +71,14 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 80
+      timeout_in_minutes: 65
       depends_on:
       - image-build-amd
 
 - label: Entrypoints Integration (API Server OpenAI - Part 2)
+  device: h200_35gb
   key: entrypoints-integration-api-server-openai-part-2
-  timeout_in_minutes: 50
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
@@ -88,6 +96,7 @@ steps:
       - image-build-amd
 
 - label: Entrypoints Integration (API Server Generate)
+  device: h200_35gb
   key: entrypoints-integration-api-server-generate
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
@@ -105,11 +114,12 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 60
+      timeout_in_minutes: 65
       depends_on:
       - image-build-amd
 
 - label: Entrypoints Integration (Responses API)
+  device: h200_35gb
   key: entrypoints-integration-responses-api
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
@@ -122,7 +132,7 @@ steps:
 - label: Entrypoints Integration (Speech to Text)
   device: h200_35gb
   key: entrypoints-integration-speech_to_text
-  timeout_in_minutes: 50
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
@@ -134,7 +144,7 @@ steps:
 - label: Entrypoints Integration (Multimodal)
   device: h200_35gb
   key: entrypoints-integration-multimodal
-  timeout_in_minutes: 50
+  timeout_in_minutes: 45
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
@@ -144,6 +154,7 @@ steps:
   - pytest -v -s entrypoints/multimodal
 
 - label: Entrypoints Integration (Pooling)
+  device: h200_35gb
   key: entrypoints-integration-pooling
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
@@ -156,7 +167,7 @@ steps:
 
 - label: OpenAI API Correctness
   key: openai-api-correctness
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: h200_18gb
   source_file_dependencies:
   - csrc/

.buildkite/test_areas/expert_parallelism.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: EPLB Algorithm
   key: eplb-algorithm
-  timeout_in_minutes: 15
+  timeout_in_minutes: 20
   device: h200_18gb
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
@@ -16,6 +16,7 @@ steps:
   - pytest -v -s distributed/test_eplb_utils.py
   mirror:
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
@@ -27,7 +28,7 @@ steps:
 
 - label: EPLB Execution # 17min
   key: eplb-execution
-  timeout_in_minutes: 27
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
@@ -39,7 +40,7 @@ steps:
 
 - label: Elastic EP Scaling Test
   key: elastic-ep-scaling-test
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   device: h100
   working_dir: "/vllm-workspace/tests"
   num_devices: 4

.buildkite/test_areas/kernels.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: vLLM IR Tests
   key: vllm-ir-tests
-  timeout_in_minutes: 10
+  timeout_in_minutes: 35
   device: h200_18gb
   working_dir: "/vllm-workspace/"
   source_file_dependencies:
@@ -15,19 +15,21 @@ steps:
     - pytest -v -s tests/kernels/ir
 
 - label: Kernels Core Operation Test
+  device: h200_35gb
   key: kernels-core-operation-test
-  timeout_in_minutes: 75
+  timeout_in_minutes: 120
   source_file_dependencies:
   - csrc/
   - tests/kernels/core
   - tests/kernels/test_concat_mla_q.py
   - tests/kernels/test_fused_qk_norm_rope_gate.py
   commands:
-    - pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py  kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py
+    - pytest -v -s kernels/core --ignore=kernels/core/test_minimax_reduce_rms.py kernels/test_concat_mla_q.py kernels/test_fused_qk_norm_rope_gate.py --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 3
 
 - label: Kernels MiniMax Reduce RMS Test (2 GPUs)
   key: kernels-minimax-reduce-rms-test-2-gpus
-  timeout_in_minutes: 15
+  timeout_in_minutes: 20
   num_devices: 2
   device: h100
   source_file_dependencies:
@@ -41,7 +43,7 @@ steps:
 
 - label: Deepseek V4 Kernel Test (H100)
   key: deepseek-v4-kernel-test-h100
-  timeout_in_minutes: 15
+  timeout_in_minutes: 30
   device: h100
   source_file_dependencies:
   - csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
@@ -54,7 +56,7 @@ steps:
 
 - label: Deepseek V4 Kernel Test (B200)
   key: deepseek-v4-kernel-test-b200
-  timeout_in_minutes: 15
+  timeout_in_minutes: 20
   device: b200-k8s
   source_file_dependencies:
   - csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
@@ -65,7 +67,7 @@ steps:
 
 - label: Kernels Attention Test %N
   key: kernels-attention-test
-  timeout_in_minutes: 35
+  timeout_in_minutes: 65
   source_file_dependencies:
   - csrc/attention/
   - vllm/v1/attention
@@ -79,7 +81,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 55
+      timeout_in_minutes: 90
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -106,7 +108,7 @@ steps:
 
 - label: Kernels Quantization Test %N
   key: kernels-quantization-test
-  timeout_in_minutes: 90
+  timeout_in_minutes: 60
   source_file_dependencies:
   - csrc/quantization/
   - vllm/model_executor/layers/quantization
@@ -131,7 +133,7 @@ steps:
 
 - label: Kernels MoE Test %N
   key: kernels-moe-test
-  timeout_in_minutes: 25
+  timeout_in_minutes: 50
   source_file_dependencies:
   - csrc/quantization/cutlass_w8a8/moe/
   - csrc/moe/
@@ -147,7 +149,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 50
+      timeout_in_minutes: 65
       source_file_dependencies:
       - csrc/quantization/cutlass_w8a8/moe/
       - csrc/moe/
@@ -162,8 +164,9 @@ steps:
       - image-build-amd
 
 - label: Kernels Mamba Test
+  device: h200_35gb
   key: kernels-mamba-test
-  timeout_in_minutes: 45
+  timeout_in_minutes: 40
   source_file_dependencies:
   - csrc/mamba/
   - tests/kernels/mamba
@@ -172,19 +175,19 @@ steps:
     - pytest -v -s kernels/mamba
 
 - label: Kernels KDA Test
-  timeout_in_minutes: 20
+  timeout_in_minutes: 25
   device: h200_18gb
   source_file_dependencies:
-  - vllm/model_executor/layers/fla/ops/kda.py
-  - vllm/model_executor/layers/fla/ops/chunk_delta_h.py
-  - vllm/model_executor/layers/fla/ops/l2norm.py
+  - vllm/third_party/flash_linear_attention/ops/kda.py
+  - vllm/third_party/flash_linear_attention/ops/chunk_delta_h.py
+  - vllm/third_party/flash_linear_attention/ops/l2norm.py
   - tests/kernels/test_kda.py
   commands:
     - pytest -v -s kernels/test_kda.py
 
 - label: Kernels DeepGEMM Test (H100)
   key: kernels-deepgemm-test-h100
-  timeout_in_minutes: 45
+  timeout_in_minutes: 35
   device: h100
   num_devices: 1
   source_file_dependencies:
@@ -211,7 +214,7 @@ steps:
 
 - label: Kernels (B200)
   key: kernels-b200
-  timeout_in_minutes: 30
+  timeout_in_minutes: 80
   working_dir: "/vllm-workspace/"
   device: b200-k8s
   # optional: true
@@ -231,6 +234,15 @@ steps:
   - vllm/v1/attention/backends/mla/flashinfer_mla.py
   - vllm/v1/attention/selector.py
   - vllm/platforms/cuda.py
+  - vllm/model_executor/kernels/linear/cute_dsl/ll_bf16.py
+  - vllm/model_executor/kernels/linear/cute_dsl/_ll_bf16_dotprod.py
+  - vllm/model_executor/kernels/linear/cute_dsl/_ll_bf16_splitk.py
+  - vllm/cute_utils/
+  - vllm/model_executor/layers/mamba/ops/gdn_chunk_cutedsl/
+  - vllm/model_executor/layers/fused_moe/router/bf16x3_router_gemm_cutedsl.py
+  - tests/kernels/mamba/test_gdn_prefill_cutedsl.py
+  - tests/kernels/test_bf16x3_router_gemm_cutedsl.py
+  - tests/kernels/test_ll_bf16_gemm.py
   - tests/kernels/test_top_k_per_row.py
   commands:
     - nvidia-smi
@@ -259,24 +271,28 @@ steps:
     - pytest -v -s tests/kernels/moe/test_flashinfer_moe.py
     - pytest -v -s tests/kernels/moe/test_trtllm_nvfp4_moe.py
     - pytest -v -s tests/kernels/moe/test_cutedsl_moe.py
+    - pytest -v -s tests/kernels/mamba/test_gdn_prefill_cutedsl.py
+    - pytest -v -s tests/kernels/test_bf16x3_router_gemm_cutedsl.py
+    - pytest -v -s tests/kernels/test_ll_bf16_gemm.py
     # e2e
     - pytest -v -s tests/models/quantization/test_nvfp4.py
 
 - label: Kernels Helion Test
   key: kernels-helion-test
-  timeout_in_minutes: 30
+  timeout_in_minutes: 115
   device: h100
   source_file_dependencies:
   - vllm/utils/import_utils.py
   - tests/kernels/helion/
   commands:
     - pip install helion==1.1.0
-    - pytest -v -s kernels/helion/
+    - pytest -v -s kernels/helion/ --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 2
 
  
 - label: Kernels FP8 MoE Test (1xH100)
   key: kernels-fp8-moe-test-1xh100
-  timeout_in_minutes: 90
+  timeout_in_minutes: 40
   device: h100
   num_devices: 1
   optional: true
@@ -293,7 +309,7 @@ steps:
 
 - label: Kernels FP8 MoE Test (2xH100)
   key: kernels-fp8-moe-test-2xh100
-  timeout_in_minutes: 90
+  timeout_in_minutes: 45
   device: h100
   num_devices: 2
   optional: true
@@ -303,7 +319,7 @@ steps:
 
 - label: Kernels Fp4 MoE Test (B200)
   key: kernels-fp4-moe-test-b200
-  timeout_in_minutes: 60
+  timeout_in_minutes: 25
   device: b200-k8s
   num_devices: 1
   optional: true
@@ -316,7 +332,7 @@ steps:
 
 - label: Kernels FusedMoE Layer Test (2 H100s)
   key: kernels-fusedmoe-layer-test-2-h100s
-  timeout_in_minutes: 90
+  timeout_in_minutes: 30
   device: h100
   num_devices: 2
   source_file_dependencies:

.buildkite/test_areas/lm_eval.yaml

@@ -5,7 +5,7 @@ steps:
 - label: LM Eval Small Models
   device: h200_35gb
   key: lm-eval-small-models
-  timeout_in_minutes: 75
+  timeout_in_minutes: 45
   source_file_dependencies:
   - csrc/
   - vllm/model_executor/layers/quantization
@@ -54,9 +54,9 @@ steps:
     - export VLLM_USE_DEEP_GEMM=0  # We found Triton is faster than DeepGEMM for H100
     - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-large-hopper.txt --tp-size=4
 
-- label: LM Eval Small Models (2xB200)
-  key: lm-eval-small-models-2xb200
-  timeout_in_minutes: 120
+- label: LM Eval Small Models (1xB200)
+  key: lm-eval-small-models-1xb200
+  timeout_in_minutes: 50
   device: b200-k8s
   optional: true
   source_file_dependencies:
@@ -65,9 +65,10 @@ steps:
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
 
-- label: LM Eval Small Models (2xL4)
-  key: lm-eval-small-models-tp
-  timeout_in_minutes: 10
+- label: LM Eval Small Models Distributed (2xB200)
+  key: lm-eval-small-models-distributed-2xb200
+  timeout_in_minutes: 120
+  device: b200-k8s
   num_devices: 2
   optional: true
   source_file_dependencies:
@@ -77,9 +78,31 @@ steps:
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small-tp.txt
 
+- label: LM Eval PCP (4xB200)
+  key: lm-eval-pcp-4xb200
+  timeout_in_minutes: 360
+  device: b200-k8s
+  num_devices: 4
+  optional: true
+  source_file_dependencies:
+  - csrc/
+  - tests/evals/gsm8k/configs/GLM-5.2-NVFP4-TP2-PCP2-EP.yaml
+  - tests/evals/gsm8k/configs/GLM-5.2-NVFP4-TP1-PCP4-EP.yaml
+  - tests/evals/gsm8k/configs/models-pcp.txt
+  - vllm/model_executor/layers/quantization
+  - vllm/config/parallel.py
+  - vllm/distributed/parallel_state.py
+  - vllm/model_executor/layers/attention/mla_attention.py
+  - vllm/model_executor/layers/attention/pcp.py
+  - vllm/v1/worker/gpu/model_runner.py
+  - vllm/v1/worker/gpu/pcp_manager.py
+  autorun_on_main: true
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-pcp.txt
+
 - label: LM Eval Large Models EP (2xB200)
   key: lm-eval-large-models-ep-2xb200
-  timeout_in_minutes: 120
+  timeout_in_minutes: 60
   device: b200-k8s
   optional: true
   num_devices: 2
@@ -91,7 +114,7 @@ steps:
 
 - label: LM Eval Qwen3.5 Models (2xB200)
   key: lm-eval-qwen3-5-models-2xb200
-  timeout_in_minutes: 120
+  timeout_in_minutes: 45
   device: b200-k8s
   optional: true
   num_devices: 2
@@ -102,13 +125,13 @@ steps:
   - vllm/transformers_utils/configs/qwen3_5_moe.py
   - vllm/model_executor/models/qwen3_next.py
   - vllm/model_executor/models/qwen3_next_mtp.py
-  - vllm/model_executor/layers/fla/ops/
+  - vllm/third_party/flash_linear_attention/ops/
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-qwen35-blackwell.txt
 
 - label: LM Eval Large Models (8xH200)
   key: lm-eval-large-models-8xh200
-  timeout_in_minutes: 60
+  timeout_in_minutes: 50
   device: h200
   optional: true
   num_devices: 8
@@ -116,8 +139,9 @@ steps:
     - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-h200.txt
   mirror:
     amd:
+      dind: false
       device: mi300_8
-      timeout_in_minutes: 180
+      timeout_in_minutes: 60
       depends_on:
       - image-build-amd
       commands:
@@ -149,9 +173,9 @@ steps:
   commands:
     - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/moe-refactor-dp-ep/config-b200.txt
 
-- label: LM Eval Humming (A100 - TEMPORARY)
-  key: lm-eval-humming-a100
-  timeout_in_minutes: 30
+- label: LM Eval Humming f16 (A100 - TEMPORARY)
+  key: lm-eval-humming-f16-a100
+  timeout_in_minutes: 75
   device: a100
   optional: true
   num_devices: 1
@@ -159,13 +183,29 @@ steps:
   - vllm/model_executor/layers/quantization/humming.py
   - vllm/model_executor/layers/quantization/utils/humming_utils.py
   - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
-  - vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
 
-- label: LM Eval Humming (H100 - TEMPORARY)
-  key: lm-eval-humming-h100
-  timeout_in_minutes: 30
+- label: LM Eval Humming Act int8 (A100 - TEMPORARY)
+  key: lm-eval-humming-act-a100
+  timeout_in_minutes: 45
+  device: a100
+  optional: true
+  num_devices: 1
+  source_file_dependencies:
+  - vllm/model_executor/layers/quantization/humming.py
+  - vllm/model_executor/layers/quantization/utils/humming_utils.py
+  - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
+
+- label: LM Eval Humming f16 (H100 - TEMPORARY)
+  key: lm-eval-humming-f16-h100
+  timeout_in_minutes: 70
   device: h100
   optional: true
   num_devices: 1
@@ -173,14 +213,30 @@ steps:
   - vllm/model_executor/layers/quantization/humming.py
   - vllm/model_executor/layers/quantization/utils/humming_utils.py
   - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
-  - vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
-  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
 
-- label: LM Eval Humming (B200 - TEMPORARY)
-  key: lm-eval-humming-b200
-  timeout_in_minutes: 30
+- label: LM Eval Humming Act fp8/int8 (H100 - TEMPORARY)
+  key: lm-eval-humming-act-h100
+  timeout_in_minutes: 70
+  device: h100
+  optional: true
+  num_devices: 1
+  source_file_dependencies:
+  - vllm/model_executor/layers/quantization/humming.py
+  - vllm/model_executor/layers/quantization/utils/humming_utils.py
+  - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
+
+- label: LM Eval Humming f16 (B200 - TEMPORARY)
+  key: lm-eval-humming-f16-b200
+  timeout_in_minutes: 50
   device: b200-k8s
   optional: true
   num_devices: 1
@@ -188,14 +244,30 @@ steps:
   - vllm/model_executor/layers/quantization/humming.py
   - vllm/model_executor/layers/quantization/utils/humming_utils.py
   - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
-  - vllm/model_executor/layers/fused_moe/oracle/mxfp4.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config.txt
+
+- label: LM Eval Humming Act fp8/int8 (B200 - TEMPORARY)
+  key: lm-eval-humming-act-b200
+  timeout_in_minutes: 50
+  device: b200-k8s
+  optional: true
+  num_devices: 1
+  source_file_dependencies:
+  - vllm/model_executor/layers/quantization/humming.py
+  - vllm/model_executor/layers/quantization/utils/humming_utils.py
+  - vllm/model_executor/layers/fused_moe/experts/fused_humming_moe.py
+  - vllm/model_executor/layers/fused_moe/oracle/
+  - vllm/model_executor/kernels/linear/
+  commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-fp8.txt
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=evals/gsm8k/configs/humming/config-act-int8.txt
 
 - label: LM Eval TurboQuant KV Cache
   key: lm-eval-turboquant-kv-cache
-  timeout_in_minutes: 75
+  timeout_in_minutes: 55
   device: h200_18gb
   source_file_dependencies:
   - vllm/model_executor/layers/quantization/turboquant/
@@ -207,7 +279,7 @@ steps:
 
 - label: GPQA Eval (GPT-OSS) (2xH100)
   key: gpqa-eval-gpt-oss-2xh100
-  timeout_in_minutes: 120
+  timeout_in_minutes: 35
   device: h100
   optional: true
   num_devices: 2
@@ -221,7 +293,7 @@ steps:
 
 - label: GPQA Eval (GPT-OSS) (2xB200)
   key: gpqa-eval-gpt-oss-2xb200
-  timeout_in_minutes: 120
+  timeout_in_minutes: 30
   device: b200-k8s
   optional: true
   num_devices: 2
@@ -235,7 +307,7 @@ steps:
 
 - label: GPQA Eval (GPT-OSS) (DGX Spark)
   key: gpqa-eval-gpt-oss-spark
-  timeout_in_minutes: 120
+  timeout_in_minutes: 35
   device: dgx-spark
   optional: true
   num_devices: 1
@@ -249,9 +321,50 @@ steps:
     - uv pip install --system 'gpt-oss[eval]==0.0.5'
     - pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-spark.txt
 
+- label: LM Eval KV-Offload (1xH200)
+  key: kv-offload-small
+  timeout_in_minutes: 30
+  device: h200_35gb
+  source_file_dependencies:
+  - vllm/distributed/kv_transfer/kv_connector/v1/offloading/
+  - vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
+  - vllm/v1/kv_offload/
+  - vllm/v1/simple_kv_offload/
+  - tests/evals/gsm8k/test_gsm8k_offloading.py
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "nemotron-h-8b or gemma-4-e4b-it"
+
+- label: LM Eval KV-Offload (2xH100)
+  key: kv-offload-medium
+  timeout_in_minutes: 30
+  device: h100
+  num_devices: 2
+  source_file_dependencies:
+  - vllm/distributed/kv_transfer/kv_connector/v1/offloading/
+  - vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
+  - vllm/v1/kv_offload/
+  - vllm/v1/simple_kv_offload/
+  - tests/evals/gsm8k/test_gsm8k_offloading.py
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "qwen3.5-35b"
+
+- label: LM Eval KV-Offload (4xH100)
+  key: kv-offload-large
+  timeout_in_minutes: 40
+  device: h100
+  num_devices: 4
+  source_file_dependencies:
+  - vllm/distributed/kv_transfer/kv_connector/v1/offloading/
+  - vllm/distributed/kv_transfer/kv_connector/v1/simple_cpu_offload_connector.py
+  - vllm/v1/kv_offload/
+  - vllm/v1/simple_kv_offload/
+  - tests/evals/gsm8k/test_gsm8k_offloading.py
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_offloading.py -k "deepseek-v4-flash"
+
 - label: MRCR Eval Small Models
   device: h200_35gb
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   source_file_dependencies:
   - tests/evals/mrcr/
   commands:

.buildkite/test_areas/lora.yaml

@@ -5,7 +5,7 @@ steps:
 - label: LoRA %N
   device: h200_35gb
   key: lora
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   source_file_dependencies:
   - vllm/lora
   - tests/lora
@@ -16,7 +16,7 @@ steps:
     amd:
       device: mi325_1
       working_dir: "/vllm-workspace/tests"
-      timeout_in_minutes: 60
+      timeout_in_minutes: 65
       source_file_dependencies:
       - vllm/lora
       - tests/lora
@@ -27,7 +27,7 @@ steps:
 
 - label: LoRA TP (Distributed)
   key: lora-tp-distributed
-  timeout_in_minutes: 30
+  timeout_in_minutes: 60
   num_devices: 4
   source_file_dependencies:
   - vllm/lora

.buildkite/test_areas/misc.yaml

@@ -5,7 +5,7 @@ steps:
 - label: V1 Spec Decode
   device: h200_35gb
   key: v1-spec-decode
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   source_file_dependencies:
     - vllm/config/
     - vllm/distributed/
@@ -23,14 +23,15 @@ steps:
     - pytest -v -s -m 'not slow_test' v1/spec_decode
   mirror:
     amd:
+      dind: false
       device: mi300_1
-      timeout_in_minutes: 65
+      timeout_in_minutes: 75
       depends_on:
       - image-build-amd
 
 - label: V1 Sample + Logits
   key: v1-sample-logits
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: h200_18gb
   source_file_dependencies:
     - vllm/config/
@@ -63,8 +64,9 @@ steps:
       - image-build-amd
 
 - label: V1 Core + KV + Metrics
+  device: h200_35gb
   key: v1-core-kv-metrics
-  timeout_in_minutes: 30
+  timeout_in_minutes: 80
   source_file_dependencies:
     - vllm/config/
     - vllm/distributed/
@@ -89,6 +91,7 @@ steps:
     - tests/v1/simple_kv_offload
     - tests/v1/worker
     - tests/v1/kv_connector/unit
+    - tests/v1/ec_connector/unit
     - tests/v1/metrics
     - tests/entrypoints/openai/correctness/test_lmeval.py
   commands:
@@ -101,14 +104,15 @@ steps:
     - pytest -v -s v1/simple_kv_offload
     - pytest -v -s v1/worker
     - pytest -v -s -m 'not cpu_test' v1/kv_connector/unit
+    - pytest -v -s -m 'not cpu_test' v1/ec_connector/unit
     - pytest -v -s -m 'not cpu_test' v1/metrics
     # Integration test for streaming correctness (requires special branch).
-    - pip install -U git+https://github.com/robertgshaw2-redhat/lm-evaluation-harness.git@streaming-api
+    - pip install -U git+https://github.com/vllm-project/lm-evaluation-harness.git@streaming-api
     - pytest -v -s entrypoints/openai/correctness/test_lmeval.py::test_lm_eval_accuracy_v1_engine
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 60
+      timeout_in_minutes: 75
       depends_on:
       - image-build-amd
 
@@ -172,7 +176,7 @@ steps:
 
 - label: Regression
   key: regression
-  timeout_in_minutes: 20
+  timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
   - vllm/config/
@@ -188,14 +192,14 @@ steps:
   - vllm/v1/
   - tests/test_regression
   commands:
-  - pip install modelscope
+  - pip install 'modelscope<1.38'
   - pytest -v -s test_regression.py
   working_dir: "/vllm-workspace/tests" # optional
 
 - label: Examples
   device: h200_35gb
   key: examples
-  timeout_in_minutes: 45
+  timeout_in_minutes: 40
   working_dir: "/vllm-workspace/examples"
   source_file_dependencies:
   - vllm/entrypoints
@@ -237,7 +241,7 @@ steps:
 
 - label: Metrics, Tracing (2 GPUs)
   key: metrics-tracing-2-gpus
-  timeout_in_minutes: 20
+  timeout_in_minutes: 25
   num_devices: 2
   source_file_dependencies:
   - vllm/config/
@@ -281,7 +285,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 20
+      timeout_in_minutes: 45
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -292,7 +296,7 @@ steps:
 - label: Async Engine, Inputs, Utils, Worker
   device: h200_35gb
   key: async-engine-inputs-utils-worker
-  timeout_in_minutes: 50
+  timeout_in_minutes: 25
   source_file_dependencies:
   - vllm/assets/
   - vllm/config/
@@ -319,7 +323,7 @@ steps:
   key: async-engine-inputs-utils-worker-config-cpu
   depends_on:
   - image-build-cpu
-  timeout_in_minutes: 30
+  timeout_in_minutes: 65
   source_file_dependencies:
   - vllm/assets/
   - vllm/config/
@@ -351,6 +355,7 @@ steps:
   - tests/test_outputs.py
   - tests/test_pooling_params.py
   - tests/test_ray_env.py
+  - tests/test_sampling_params.py
   - tests/multimodal
   - tests/renderers
   - tests/standalone_tests/lazy_imports.py
@@ -368,6 +373,7 @@ steps:
   - pytest -v -s test_outputs.py
   - pytest -v -s test_pooling_params.py
   - pytest -v -s test_ray_env.py
+  - pytest -v -s test_sampling_params.py
   - pytest -v -s -m 'cpu_test' multimodal
   - pytest -v -s renderers
   - pytest -v -s reasoning
@@ -379,7 +385,7 @@ steps:
 
 - label: Batch Invariance (A100)
   key: batch-invariance-a100
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   device: a100
   source_file_dependencies:
     - vllm/v1/attention
@@ -393,7 +399,7 @@ steps:
 
 - label: Batch Invariance (H100)
   key: batch-invariance-h100
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   device: h100
   source_file_dependencies:
     - vllm/v1/attention
@@ -409,7 +415,7 @@ steps:
 
 - label: Batch Invariance (B200)
   key: batch-invariance-b200
-  timeout_in_minutes: 30
+  timeout_in_minutes: 35
   device: b200-k8s
   source_file_dependencies:
     - vllm/v1/attention
@@ -428,7 +434,7 @@ steps:
 - label: Acceptance Length Test (Large Models) # optional
   device: h200_35gb
   key: acceptance-length-test-large-models
-  timeout_in_minutes: 25
+  timeout_in_minutes: 20
   gpu: h100
   optional: true
   num_gpus: 1

.buildkite/test_areas/model_executor.yaml

@@ -3,13 +3,16 @@ depends_on:
   - image-build
 steps:
 - label: Model Executor
+  device: h200_35gb
   key: model-executor
-  timeout_in_minutes: 35
+  timeout_in_minutes: 45
   source_file_dependencies:
   - vllm/engine/arg_utils.py
   - vllm/config/model.py
   - vllm/model_executor
+  - vllm/model_executor/warmup
   - tests/model_executor
+  - tests/model_executor/test_jit_warmup.py
   - tests/entrypoints/openai/completion/test_tensorizer_entrypoint.py
   commands:
     - apt-get update && apt-get install -y curl libsodium23
@@ -25,6 +28,7 @@ steps:
     - pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py --timeout=900 --timeout-method=thread
   mirror:
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
@@ -32,7 +36,9 @@ steps:
       - vllm/engine/arg_utils.py
       - vllm/config/model.py
       - vllm/model_executor
+      - vllm/model_executor/warmup
       - tests/model_executor
+      - tests/model_executor/test_jit_warmup.py
       - tests/entrypoints/openai/completion/test_tensorizer_entrypoint.py
       - vllm/_aiter_ops.py
       - vllm/platforms/rocm.py

.buildkite/test_areas/model_runner_v2.yaml

@@ -5,7 +5,7 @@ steps:
 - label: Model Runner V2 Core Tests
   device: h200_35gb
   key: model-runner-v2-core-tests
-  timeout_in_minutes: 45
+  timeout_in_minutes: 35
   source_file_dependencies:
   - vllm/v1/worker/gpu/
   - vllm/v1/worker/gpu_worker.py
@@ -18,9 +18,7 @@ steps:
   - set -x
   - export VLLM_USE_V2_MODEL_RUNNER=1
   - pytest -v -s v1/engine/test_llm_engine.py -k "not test_engine_metrics"
-  # This requires eager until we sort out CG correctness issues.
-  # TODO: remove ENFORCE_EAGER here after https://github.com/vllm-project/vllm/pull/32936 is merged.
-  - ENFORCE_EAGER=1 pytest -v -s v1/e2e/general/test_async_scheduling.py -k "not ngram"
+  - pytest -v -s v1/e2e/general/test_async_scheduling.py -k "not ngram"
   - pytest -v -s v1/e2e/general/test_context_length.py
   - pytest -v -s v1/e2e/general/test_min_tokens.py
   # Temporary hack filter to exclude ngram spec decoding based tests.
@@ -29,7 +27,7 @@ steps:
 - label: Model Runner V2 Examples
   device: h200_35gb
   key: model-runner-v2-examples
-  timeout_in_minutes: 45
+  timeout_in_minutes: 35
   working_dir: "/vllm-workspace/examples"
   source_file_dependencies:
     - vllm/v1/worker/gpu/
@@ -65,7 +63,7 @@ steps:
 
 - label: Model Runner V2 Distributed (2 GPUs)
   key: model-runner-v2-distributed-2-gpus
-  timeout_in_minutes: 45
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -86,7 +84,7 @@ steps:
 
 - label: Model Runner V2 Pipeline Parallelism (4 GPUs)
   key: model-runner-v2-pipeline-parallelism-4-gpus
-  timeout_in_minutes: 60
+  timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:

.buildkite/test_areas/models_basic.yaml

@@ -4,9 +4,8 @@ depends_on:
 steps:
 - label: Basic Models Tests (Initialization)
   key: basic-models-tests-initialization
-  timeout_in_minutes: 45
+  timeout_in_minutes: 25
   device: h200_18gb
-  torch_nightly: true
   source_file_dependencies:
   - vllm/
   - tests/models/test_initialization.py
@@ -14,13 +13,11 @@ steps:
   commands:
     # Run a subset of model initialization tests
     - pytest -v -s models/test_initialization.py::test_can_initialize_small_subset
-  mirror:
-    torch_nightly: {}
 
 - label: Basic Models Tests (Extra Initialization) %N
   device: h200_35gb
   key: basic-models-tests-extra-initialization
-  timeout_in_minutes: 45
+  timeout_in_minutes: 100
   source_file_dependencies:
   - vllm/model_executor/models/
   - tests/models/test_initialization.py
@@ -30,21 +27,19 @@ steps:
     # subset of supported models (the complement of the small subset in the above
     # test.) Also run if model initialization test file is modified
     - pytest -v -s models/test_initialization.py -k 'not test_can_initialize_small_subset' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
-  parallelism: 2
-  mirror:
-    torch_nightly: {}
+  parallelism: 4
 
 - label: Basic Models Tests (Other)
   device: h200_35gb
   key: basic-models-tests-other
-  timeout_in_minutes: 45
+  timeout_in_minutes: 35
   source_file_dependencies:
   - vllm/
   - tests/models/test_terratorch.py
-  - tests/models/test_transformers.py
+  - tests/models/transformers/test_backend.py
   - tests/models/test_registry.py
   commands:
-    - pytest -v -s models/test_terratorch.py models/test_transformers.py models/test_registry.py
+    - pytest -v -s models/test_terratorch.py models/transformers/test_backend.py models/test_registry.py
   mirror:
     amd:
       device: mi325_1
@@ -55,11 +50,12 @@ steps:
   key: basic-models-test-other-cpu
   depends_on:
   - image-build-cpu
-  timeout_in_minutes: 10
+  timeout_in_minutes: 20
   source_file_dependencies:
   - vllm/
   - tests/models/test_utils.py
   - tests/models/test_vision.py
+  - tests/models/transformers/fusers/
   device: cpu-small
   commands:
-    - pytest -v -s models/test_utils.py models/test_vision.py
+    - pytest -v -s models/test_utils.py models/test_vision.py models/transformers/fusers/

.buildkite/test_areas/models_distributed.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Distributed Model Tests (2 GPUs)
   key: distributed-model-tests-2-gpus
-  timeout_in_minutes: 50
+  timeout_in_minutes: 60
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -17,7 +17,7 @@ steps:
   - TARGET_TEST_SUITE=L4 pytest basic_correctness/ -v -s -m 'distributed(num_gpus=2)'
   - CUDA_VISIBLE_DEVICES=0,1 pytest -v -s model_executor/model_loader/test_sharded_state_loader.py -m '(not slow_test)'
   # Avoid importing model tests that cause CUDA reinitialization error
-  - pytest models/test_transformers.py -v -s -m 'distributed(num_gpus=2)'
+  - pytest models/transformers/test_backend.py -v -s -m 'distributed(num_gpus=2)'
   - pytest models/language -v -s -m 'distributed(num_gpus=2)'
   - pytest models/multimodal/generation/test_phi4siglip.py -v -s -m 'distributed(num_gpus=2)'
   - pytest models/multimodal -v -s -m 'distributed(num_gpus=2)' --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_phi4siglip.py

.buildkite/test_areas/models_language.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Language Models Tests (Standard)
   key: language-models-tests-standard
-  timeout_in_minutes: 25
+  timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
   - vllm/
@@ -14,15 +14,16 @@ steps:
     - pip freeze | grep -E 'torch'
     - pytest -v -s models/language -m 'core_model and (not slow_test)'
   mirror:
-    torch_nightly: {}
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
 
 - label: Language Models Tests (Extra Standard) %N
+  device: h200_35gb
   key: language-models-tests-extra-standard
-  timeout_in_minutes: 45
+  timeout_in_minutes: 40
   source_file_dependencies:
   - vllm/model_executor/models/
   - tests/models/language/pooling/test_embedding.py
@@ -35,8 +36,8 @@ steps:
     - pytest -v -s models/language -m 'core_model and slow_test' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
   parallelism: 2
   mirror:
-    torch_nightly: {}
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
@@ -51,10 +52,10 @@ steps:
       - tests/models/language/pooling/test_classification.py
       - vllm/_aiter_ops.py
       - vllm/platforms/rocm.py
-
 - label: Language Models Tests (Hybrid) %N
+  device: h200_35gb
   key: language-models-tests-hybrid
-  timeout_in_minutes: 75
+  timeout_in_minutes: 65
   source_file_dependencies:
   - vllm/
   - tests/models/language/generation
@@ -63,14 +64,13 @@ steps:
     # Note: also needed to run plamo2 model in vLLM
     - uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
     - uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
-    # Shard hybrid language model tests
-    - pytest -v -s models/language/generation -m hybrid_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
+    # Shard the hybrid language model tests that are numerically stable on Hopper.
+    - pytest -v -s models/language/generation -m hybrid_model -k 'not granite-4.0-tiny-preview' --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
   parallelism: 2
   mirror:
-    torch_nightly: {}
     amd:
       device: mi325_1
-      timeout_in_minutes: 90
+      timeout_in_minutes: 70
       depends_on:
       - image-build-amd
       commands:
@@ -78,10 +78,24 @@ steps:
       - uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
       - pytest -v -s models/language/generation -m hybrid_model --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
 
+# Granite 4 hybrid generation is sensitive to hardware-specific Triton SSD
+# autotuning (https://github.com/vllm-project/vllm/issues/25194). Keep this one
+# correctness test on L4 until its H200 output matches the Transformers reference.
+- label: Language Models Tests (Granite L4 Compatibility)
+  key: language-models-tests-granite-l4-compatibility
+  timeout_in_minutes: 65
+  source_file_dependencies:
+  - vllm/
+  - tests/models/language/generation
+  commands:
+    - uv pip install --system --no-build-isolation 'git+https://github.com/state-spaces/mamba@v2.3.0'
+    - uv pip install --system --no-build-isolation 'git+https://github.com/Dao-AILab/causal-conv1d@v1.6.0'
+    - pytest -v -s models/language/generation -m hybrid_model -k 'granite-4.0-tiny-preview'
+
 - label: Language Models Test (Extended Generation) # 80min
   device: h200_35gb
   key: language-models-test-extended-generation
-  timeout_in_minutes: 110
+  timeout_in_minutes: 65
   optional: true
   source_file_dependencies:
   - vllm/
@@ -95,7 +109,7 @@ steps:
 
 - label: Language Models Test (PPL)
   key: language-models-test-ppl
-  timeout_in_minutes: 110
+  timeout_in_minutes: 30
   device: h200_18gb
   optional: true
   source_file_dependencies:
@@ -104,10 +118,10 @@ steps:
   commands:
     - pytest -v -s models/language/generation_ppl_test
 
-- label: Language Models Test (Extended Pooling)  # 36min
+- label: Language Models Test (Extended Pooling)
   device: h200_35gb
   key: language-models-test-extended-pooling
-  timeout_in_minutes: 50
+  timeout_in_minutes: 120
   optional: true
   source_file_dependencies:
   - vllm/
@@ -117,13 +131,13 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 100
+      timeout_in_minutes: 120
       depends_on:
       - image-build-amd
 
 - label: Language Models Test (MTEB)
   key: language-models-test-mteb
-  timeout_in_minutes: 110
+  timeout_in_minutes: 45
   device: h200_18gb
   optional: true
   source_file_dependencies:

.buildkite/test_areas/models_multimodal.yaml

@@ -10,7 +10,6 @@ steps:
   - vllm/
   - tests/models/multimodal
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen2"
     - pytest -v -s models/multimodal/generation/test_ultravox.py -m core_model
   mirror:
@@ -21,14 +20,14 @@ steps:
 
 - label: "Multi-Modal Models (Standard) 2: qwen3 + gemma"
   key: multi-modal-models-standard-2-qwen3-gemma
-  timeout_in_minutes: 45
+  timeout_in_minutes: 50
   device: h200_18gb
   source_file_dependencies:
   - vllm/
   - tests/models/multimodal
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "qwen3 or gemma"
+    - pytest -v -s models/multimodal/generation/test_mm_prefix_lm.py -m core_model
     - pytest -v -s models/multimodal/generation/test_qwen2_5_vl.py -m core_model
   mirror:
     amd:
@@ -39,12 +38,11 @@ steps:
 - label: "Multi-Modal Models (Standard) 3: llava + qwen2_vl"
   device: h200_35gb
   key: multi-modal-models-standard-3-llava-qwen2-vl
-  timeout_in_minutes: 45
+  timeout_in_minutes: 40
   source_file_dependencies:
   - vllm/
   - tests/models/multimodal
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation/test_common.py -m core_model -k "not qwen2 and not qwen3 and not gemma"
     - pytest -v -s models/multimodal/generation/test_qwen2_vl.py -m core_model
   mirror:
@@ -56,13 +54,12 @@ steps:
 - label: "Multi-Modal Models (Standard) 4: other + whisper"
   device: h200_35gb
   key: multi-modal-models-standard-4-other-whisper
-  timeout_in_minutes: 45
+  timeout_in_minutes: 50
   source_file_dependencies:
   - vllm/
   - tests/models/multimodal
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
-    - pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py  --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/generation/test_vit_cudagraph.py --ignore models/multimodal/processing
+    - pytest -v -s models/multimodal -m core_model --ignore models/multimodal/generation/test_common.py --ignore models/multimodal/generation/test_ultravox.py --ignore models/multimodal/generation/test_qwen2_5_vl.py --ignore models/multimodal/generation/test_qwen2_vl.py --ignore models/multimodal/generation/test_whisper.py --ignore models/multimodal/generation/test_mm_prefix_lm.py --ignore models/multimodal/generation/test_memory_leak.py --ignore models/multimodal/generation/test_vit_cudagraph.py --ignore models/multimodal/processing
     - pytest -v -s models/multimodal/generation/test_vit_cudagraph.py -m core_model
     - pytest models/multimodal/generation/test_memory_leak.py -m core_model
     - cd .. && VLLM_WORKER_MULTIPROC_METHOD=spawn pytest -v -s tests/models/multimodal/generation/test_whisper.py -m core_model  # Otherwise, mp_method="spawn" doesn't work
@@ -72,36 +69,35 @@ steps:
       depends_on:
       - image-build-amd
 
-- label: Multi-Modal Processor (CPU)
+- label: Multi-Modal Processor (CPU) %N
   key: multi-modal-processor-cpu
   depends_on:
   - image-build-cpu
-  timeout_in_minutes: 60
+  timeout_in_minutes: 125
   source_file_dependencies:
   - vllm/
   - tests/models/multimodal
   - tests/models/registry.py
   device: cpu-medium
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
-    - pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py
+    - pytest -v -s models/multimodal/processing --ignore models/multimodal/processing/test_tensor_schema.py --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --shard-id=$$BUILDKITE_PARALLEL_JOB
+  parallelism: 4
 
 - label: Multi-Modal Processor # 44min
   key: multi-modal-processor
-  timeout_in_minutes: 60
+  timeout_in_minutes: 65
   device: h200_18gb
   source_file_dependencies:
   - vllm/
   - tests/models/multimodal
   - tests/models/registry.py
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/processing/test_tensor_schema.py
 
 - label: Multi-Modal Accuracy Eval (Small Models) # 50min
   device: h200_35gb
   key: multi-modal-accuracy-eval-small-models
-  timeout_in_minutes: 70
+  timeout_in_minutes: 30
   working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
   source_file_dependencies:
   - vllm/multimodal/
@@ -111,6 +107,7 @@ steps:
   - pytest -s -v test_lm_eval_correctness.py --config-list-file=configs/models-mm-small.txt --tp-size=1
   mirror:
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd
@@ -122,6 +119,7 @@ steps:
       - vllm/model_executor/model_loader/
 
 - label: Multi-Modal Models (Extended Generation 1)
+  device: h200_35gb
   key: multi-modal-models-extended-generation-1
   optional: true
   source_file_dependencies:
@@ -129,7 +127,6 @@ steps:
   - tests/models/multimodal/generation
   - tests/models/multimodal/test_mapping.py
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation -m 'not core_model' --ignore models/multimodal/generation/test_common.py
     - pytest -v -s models/multimodal/test_mapping.py
   mirror:
@@ -146,7 +143,6 @@ steps:
   - vllm/
   - tests/models/multimodal/generation
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=0) and not core_model'
 
 - label: Multi-Modal Models (Extended Generation 3)
@@ -157,7 +153,6 @@ steps:
   - vllm/
   - tests/models/multimodal/generation
   commands:
-    - pip install git+https://github.com/TIGER-AI-Lab/Mantis.git
     - pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=1) and not core_model'
 
 - label: Multi-Modal Models (Extended Pooling)
@@ -172,7 +167,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 60
+      timeout_in_minutes: 75
       depends_on:
       - image-build-amd
       source_file_dependencies:

.buildkite/test_areas/plugins.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Plugin Tests (2 GPUs)
   key: plugin-tests-2-gpus
-  timeout_in_minutes: 60
+  timeout_in_minutes: 35
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
@@ -37,6 +37,11 @@ steps:
   - pytest -v -s plugins_tests/test_stats_logger_plugins.py
   - pip uninstall dummy_stat_logger -y
   # end stat_logger plugins test
+  # begin endpoint plugins test
+  - pip install -e ./plugins/vllm_add_dummy_endpoint_plugin
+  - pytest -v -s plugins_tests/test_endpoint_plugins.py
+  - pip uninstall vllm_add_dummy_endpoint_plugin -y
+  # end endpoint plugins test
   # other tests continue here:
   - pytest -v -s plugins_tests/test_scheduler_plugins.py
   - pip install -e ./plugins/vllm_add_dummy_model

.buildkite/test_areas/pytorch.yaml

@@ -5,7 +5,7 @@ steps:
 - label: PyTorch Compilation Unit Tests
   device: h200_35gb
   key: pytorch-compilation-unit-tests
-  timeout_in_minutes: 10
+  timeout_in_minutes: 90
   source_file_dependencies:
     - vllm/__init__.py
     - vllm/_aiter_ops.py
@@ -78,7 +78,7 @@ steps:
 
 - label: PyTorch Compilation Passes Unit Tests
   key: pytorch-compilation-passes-unit-tests
-  timeout_in_minutes: 20
+  timeout_in_minutes: 45
   source_file_dependencies:
     - vllm/__init__.py
     - vllm/_aiter_ops.py
@@ -109,14 +109,16 @@ steps:
   - pytest -s -v compile/passes --ignore compile/passes/distributed
   mirror:
     amd:
+      dind: false
       device: mi300_1
-      timeout_in_minutes: 180
+      timeout_in_minutes: 65
       depends_on:
       - image-build-amd
 
 - label: PyTorch Fullgraph Smoke Test
+  device: h200_35gb
   key: pytorch-fullgraph-smoke-test
-  timeout_in_minutes: 35
+  timeout_in_minutes: 90
   source_file_dependencies:
   - vllm/__init__.py
   - vllm/_aiter_ops.py
@@ -148,11 +150,46 @@ steps:
   # as it is a heavy test that is covered in other steps.
   # Use `find` to launch multiple instances of pytest so that
   # they do not suffer from https://github.com/vllm-project/vllm/issues/28965
-  - "find compile/fullgraph/ -name 'test_*.py' -not -name 'test_full_graph.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
+  - "find compile/fullgraph/ -name 'test_*.py' -not -name 'test_full_cudagraph.py' -not -name 'test_full_graph.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
+
+# Hopper-only DeepSeek-V2-Lite cases in this file require two 29.3-GiB model
+# instances and cannot fit a 35GB MIG slice. L4 retains the original coverage:
+# those SM90 cases skip while the architecture-compatible cases still run.
+- label: PyTorch Fullgraph CUDAGraph (L4 Compatibility)
+  key: pytorch-fullgraph-cudagraph-l4-compatibility
+  timeout_in_minutes: 60
+  source_file_dependencies:
+  - vllm/__init__.py
+  - vllm/_aiter_ops.py
+  - vllm/_custom_ops.py
+  - vllm/compilation/
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/env_override.py
+  - vllm/envs.py
+  - vllm/forward_context.py
+  - vllm/inputs/
+  - vllm/ir/
+  - vllm/kernels/
+  - vllm/logger.py
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/plugins/
+  - vllm/sampling_params.py
+  - vllm/sequence.py
+  - vllm/transformers_utils/
+  - vllm/triton_utils/
+  - vllm/utils/
+  - vllm/v1/
+  - tests/compile
+  commands:
+  - pytest -s -v compile/fullgraph/test_full_cudagraph.py
 
 - label: PyTorch Fullgraph
   key: pytorch-fullgraph
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   device: h200_18gb
   source_file_dependencies:
   - vllm/__init__.py
@@ -197,6 +234,7 @@ steps:
   - bash standalone_tests/pytorch_nightly_dependency.sh
   mirror:
     amd:
+      dind: false
       device: mi300_1
       depends_on:
       - image-build-amd

.buildkite/test_areas/quantization.yaml

@@ -3,8 +3,11 @@ depends_on:
   - image-build
 steps:
 - label: Quantization
+  device: h200_35gb
   key: quantization
-  timeout_in_minutes: 90
+  timeout_in_minutes: 75
+  env:
+    VLLM_USE_V2_MODEL_RUNNER: "0"
   source_file_dependencies:
   - csrc/
   - vllm/model_executor/layers/quantization
@@ -19,11 +22,15 @@ steps:
   # TODO(jerryzh168): resolve the above comment
   - uv pip install --system torchao==0.17.0 --index-url https://download.pytorch.org/whl/cu130
   - uv pip install --system conch-triton-kernels
-  - VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
+  # The SM90-only checkpoint currently contains a removed weight_chan_scale
+  # parameter. It was not exercised by the previous L4 job.
+  - VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py -k 'not test_compressed_tensors_w4a8_fp8' --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 8
 
 - label: Quantized Fusions
+  device: h200_35gb
   key: quantized-fusions
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   source_file_dependencies:
   - tests/fusion
   - vllm/model_executor/layers/fusion
@@ -35,7 +42,7 @@ steps:
 
 - label: Quantized MoE Test (B200)
   key: quantized-moe-test-b200
-  timeout_in_minutes: 60
+  timeout_in_minutes: 120
   working_dir: "/vllm-workspace/"
   device: b200-k8s
   source_file_dependencies:
@@ -52,10 +59,14 @@ steps:
     - pytest -s -v tests/quantization/test_blackwell_moe.py
 
 - label: Quantized Models Test
+  device: h200_35gb
   key: quantized-models-test
-  timeout_in_minutes: 60
+  timeout_in_minutes: 65
+  env:
+    VLLM_USE_V2_MODEL_RUNNER: "0"
   source_file_dependencies:
   - vllm/model_executor/layers/quantization
   - tests/models/quantization
   commands:
-    - pytest -v -s models/quantization
+    - pytest -v -s models/quantization --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
+  parallelism: 3

.buildkite/test_areas/rust_frontend.yaml

@@ -3,11 +3,16 @@ depends_on:
   - image-build
 steps:
 - label: Rust Frontend OpenAI Coverage
-  timeout_in_minutes: 90
+  timeout_in_minutes: 30
   device: h200_18gb
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - rust/
+  - build_rust.sh
+  - tools/build_rust.py
+  - rust-toolchain.toml
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   - vllm/benchmarks/
   - vllm/entrypoints/openai/
   - vllm/entrypoints/serve/
@@ -15,84 +20,116 @@ steps:
   - tests/utils.py
   - tests/benchmarks/test_serve_cli.py
   - tests/entrypoints/openai/chat_completion/test_chat_completion.py
-  # - tests/entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py
+  - tests/entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py
 
   # - tests/entrypoints/openai/completion/test_prompt_validation.py
   - tests/entrypoints/openai/completion/test_shutdown.py
-  # - tests/entrypoints/openai/test_return_token_ids.py
-  # - tests/entrypoints/openai/test_uds.py
+  - tests/entrypoints/openai/test_return_token_ids.py
+  - tests/entrypoints/openai/test_uds.py
   - tests/v1/sample/test_logprobs_e2e.py
   commands:
+  - . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
   - export VLLM_USE_RUST_FRONTEND=1
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - pytest -v -s benchmarks/test_serve_cli.py -k "not insecure and not (test_bench_serve and not test_bench_serve_chat)"
   - pytest -v -s entrypoints/openai/chat_completion/test_chat_completion.py -k "not test_invalid_json_schema and not test_invalid_regex"
-  # - pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not invalid"
+  - pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not multiple"
 
   # - pytest -v -s entrypoints/openai/completion/test_prompt_validation.py -k "not prompt_embeds"
   - pytest -v -s entrypoints/openai/completion/test_shutdown.py -k "not engine_failure and not test_abort_timeout_exits_quickly"
-  # - pytest -v -s entrypoints/openai/test_return_token_ids.py
-  # - pytest -v -s entrypoints/openai/test_uds.py
+  # test_comparison streams differently: Rust emits a separate first (prompt_token_ids) chunk and
+  # finish chunk without logprobs, while the test reads `logprobs.tokens` on every chunk.
+  - pytest -v -s entrypoints/openai/test_return_token_ids.py -k "not test_comparison"
+  - pytest -v -s entrypoints/openai/test_uds.py
   - pytest -v -s v1/sample/test_logprobs_e2e.py -k "test_prompt_logprobs_e2e_server"
 
 - label: Rust Frontend Serve/Admin Coverage
-  timeout_in_minutes: 60
+  timeout_in_minutes: 25
   device: h200_18gb
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - rust/
+  - build_rust.sh
+  - tools/build_rust.py
+  - rust-toolchain.toml
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   - vllm/entrypoints/openai/
   - vllm/entrypoints/serve/
   - vllm/v1/engine/
   - tests/utils.py
-  # - tests/entrypoints/serve/dev/rpc/test_collective_rpc.py
-  - tests/entrypoints/serve/disagg/test_serving_tokens.py
+  - tests/entrypoints/serve/dev/rpc/test_collective_rpc.py
+  - tests/entrypoints/scale_out/token_in_token_out/test_serving_tokens.py
   - tests/entrypoints/serve/instrumentator/test_basic.py
   - tests/entrypoints/serve/instrumentator/test_metrics.py
   # - tests/entrypoints/serve/dev/test_sleep.py
+  - tests/entrypoints/serve/tokenize/test_tokenization.py
   commands:
+  - . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
   - export VLLM_USE_RUST_FRONTEND=1
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  # - pytest -v -s entrypoints/serve/dev/rpc/test_collective_rpc.py
+  - PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/serve/dev/rpc/test_collective_rpc.py
+  # server_load can be flaky under the Rust frontend; keep it excluded for now.
   - pytest -v -s entrypoints/serve/instrumentator/test_basic.py -k "not show_version and not server_load"
-  - pytest -v -s entrypoints/serve/disagg/test_serving_tokens.py -k "not stream and not lora and not test_generate_logprobs and not stop_string_workflow"
+  # test_generate_logprobs expects Python-style top_logprobs truncation (dedup sampled + cap at max(k, 1)).
+  - pytest -v -s entrypoints/scale_out/token_in_token_out/test_serving_tokens.py -k "not stream and not lora and not test_generate_logprobs and not stop_string_workflow"
   - pytest -v -s entrypoints/serve/instrumentator/test_metrics.py -k "text and not show and not run_batch and not test_metrics_counts and not test_metrics_exist"
   # - pytest -v -s entrypoints/serve/dev/test_sleep.py
+  # /tokenizer_info is not implemented in the Rust frontend (the CLI flag is accepted as a no-op).
+  - pytest -v -s entrypoints/serve/tokenize/test_tokenization.py -k "not tokenizer_info"
 
 - label: Rust Frontend Core Correctness
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: h200_18gb
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - rust/
+  - build_rust.sh
+  - tools/build_rust.py
+  - rust-toolchain.toml
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   - vllm/entrypoints/openai/
   - tests/utils.py
   - tests/entrypoints/openai/correctness/test_lmeval.py
   commands:
+  - . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
   - export VLLM_USE_RUST_FRONTEND=1
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - pytest -s entrypoints/openai/correctness/test_lmeval.py::test_lm_eval_accuracy_v1_engine
 
 - label: Rust Frontend Tool Use
-  timeout_in_minutes: 60
+  device: h200_35gb
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - rust/
+  - build_rust.sh
+  - tools/build_rust.py
+  - rust-toolchain.toml
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   - vllm/entrypoints/openai/
   - vllm/tool_parsers/
   - tests/utils.py
   - tests/tool_use/
   commands:
+  - . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
   - export VLLM_USE_RUST_FRONTEND=1
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - pytest -v -s tool_use --ignore=tool_use/mistral --models llama3.2 -k "not test_response_format_with_tool_choice_required and not test_parallel_tool_calls_false and not test_tool_call_and_choice"
 
 - label: Rust Frontend Distributed
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   num_devices: 4
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - rust/
+  - build_rust.sh
+  - tools/build_rust.py
+  - rust-toolchain.toml
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   - vllm/distributed/
   - vllm/engine/
   - vllm/executor/
@@ -103,6 +140,7 @@ steps:
   - tests/v1/distributed/test_hybrid_lb_dp.py
   - tests/v1/distributed/test_internal_lb_dp.py
   commands:
+  - . /vllm-workspace/.buildkite/scripts/rust-coverage.sh && rust_coverage_start rust-e2e
   - export VLLM_USE_RUST_FRONTEND=1
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - export NCCL_CUMEM_HOST_ENABLE=0

.buildkite/test_areas/rust_frontend_cargo.yaml

@@ -4,7 +4,7 @@ steps:
 - label: Rust Frontend Cargo Style + Clippy
   key: rust-frontend-cargo-style-clippy
   depends_on: []
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: cpu-medium
   no_plugin: true
   source_file_dependencies:
@@ -18,7 +18,7 @@ steps:
 - label: Rust Frontend Cargo Tests
   key: rust-frontend-cargo-tests
   depends_on: []
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: cpu-medium
   no_plugin: true
   source_file_dependencies:
@@ -26,5 +26,7 @@ steps:
   - rust-toolchain.toml
   - .buildkite/test_areas/rust_frontend_cargo.yaml
   - .buildkite/scripts/run-rust-frontend-cargo-ci.sh
+  - .buildkite/scripts/rust-coverage.sh
+  - codecov.yml
   commands:
   - .buildkite/scripts/run-rust-frontend-cargo-ci.sh test

.buildkite/test_areas/samplers.yaml

@@ -5,7 +5,7 @@ steps:
 - label: Samplers Test
   device: h200_35gb
   key: samplers-test
-  timeout_in_minutes: 75
+  timeout_in_minutes: 40
   source_file_dependencies:
   - vllm/model_executor/layers
   - vllm/sampling_metadata.py
@@ -19,7 +19,7 @@ steps:
     - VLLM_USE_FLASHINFER_SAMPLER=1 pytest -v -s samplers
   mirror:
     amd:
-      device: mi250_1
+      device: mi325_1
       depends_on:
       - image-build-amd
       commands:

.buildkite/test_areas/spec_decode.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Spec Decode Eagle
   key: spec-decode-eagle
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   device: h200_18gb
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -15,7 +15,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 45
+      timeout_in_minutes: 60
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -29,7 +29,7 @@ steps:
 
 - label: Spec Decode Eagle Nightly B200
   key: spec-decode-eagle-nightly-b200
-  timeout_in_minutes: 30
+  timeout_in_minutes: 25
   device: b200-k8s
   optional: true
   source_file_dependencies:
@@ -41,7 +41,7 @@ steps:
 
 - label: Spec Decode Speculators + MTP
   key: spec-decode-speculators-mtp
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: h200_18gb
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -82,7 +82,7 @@ steps:
   
 - label: Spec Decode Ngram + Suffix
   key: spec-decode-ngram-suffix
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: h200_18gb
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -93,7 +93,9 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 65
+      timeout_in_minutes: 55
+      # TODO(akaratza): Test after Torch >= 2.12 bump
+      soft_fail: true
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -107,7 +109,7 @@ steps:
 
 - label: Spec Decode Draft Model
   key: spec-decode-draft-model
-  timeout_in_minutes: 30
+  timeout_in_minutes: 45
   device: h200_18gb
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -118,7 +120,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
-      timeout_in_minutes: 50
+      timeout_in_minutes: 55
       depends_on:
       - image-build-amd
       source_file_dependencies:
@@ -132,7 +134,7 @@ steps:
 
 - label: Spec Decode Draft Model Nightly B200
   key: spec-decode-draft-model-nightly-b200
-  timeout_in_minutes: 30
+  timeout_in_minutes: 40
   device: b200-k8s
   optional: true
   source_file_dependencies:
@@ -144,7 +146,7 @@ steps:
 
 - label: Speculators Correctness
   key: speculators-correctness
-  timeout_in_minutes: 60
+  timeout_in_minutes: 30
   device: h100
   optional: true
   num_devices: 1
@@ -157,7 +159,7 @@ steps:
     - pytest -v -s v1/spec_decode/test_speculators_correctness.py -m slow_test
 
 - label: Spec Decode MTP hybrid (B200)
-  timeout_in_minutes: 30
+  timeout_in_minutes: 20
   device: b200-k8s
   optional: true
   source_file_dependencies:

.buildkite/test_areas/weight_loading.yaml

@@ -4,7 +4,7 @@ depends_on:
 steps:
 - label: Weight Loading Multiple GPU  # 33min
   key: weight-loading-multiple-gpu
-  timeout_in_minutes: 45
+  timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   optional: true
@@ -15,6 +15,7 @@ steps:
     - bash weight_loading/run_model_weight_loading_test.sh -c weight_loading/models.txt
   mirror:
     amd:
+      dind: false
       device: mi300_2
       depends_on:
       - image-build-amd

.github/CODEOWNERS

@@ -47,6 +47,7 @@
 
 # Rust Frontend
 /rust/ @BugenZhao @njhill
+/rust/src/bench @esmeetu
 /build_rust.sh @BugenZhao @njhill
 /rust-toolchain.toml @BugenZhao @njhill
 /.buildkite/test_areas/rust* @BugenZhao @njhill
@@ -119,7 +120,7 @@
 
 # Transformers modeling backend
 /vllm/model_executor/models/transformers @hmellor
-/tests/models/test_transformers.py @hmellor
+/tests/models/transformers @hmellor
 
 # Docs
 /docs/mkdocs @hmellor
@@ -172,7 +173,7 @@ mkdocs.yaml @hmellor
 # Kernels
 /vllm/v1/attention/ops/chunked_prefill_paged_decode.py @tdoublep
 /vllm/v1/attention/ops/triton_unified_attention.py @tdoublep
-/vllm/model_executor/layers/fla @ZJY0516 @vadiklyutiy
+/vllm/third_party/flash_linear_attention @ZJY0516 @vadiklyutiy
 
 # ROCm related: specify owner with write access to notify AMD folks for careful code review
 /vllm/**/*rocm* @tjtanaa @dllehr-amd

.github/workflows/issue_autolabel.yml

@@ -323,11 +323,11 @@ jobs:
             // {users} will be replaced with @mentions
             const ccConfig = {
               rocm: {
-                users: ['hongxiayang', 'tjtanaa', 'vllmellm'],
+                users: ['hongxiayang', 'tjtanaa', 'vllmellm', 'giuseppegrossi'],
                 message: 'CC {users} for ROCm-related issue',
               },
               mistral: {
-                users: ['patrickvonplaten', 'juliendenize', 'andylolu2'],
+                users: ['patrickvonplaten', 'juliendenize', 'andylolu2', 'NickLucche'],
                 message: 'CC {users} for Mistral-related issue',
               },
               // Add more label -> user mappings here

.github/workflows/macos-smoke-test.yml

@@ -27,7 +27,7 @@ jobs:
     timeout-minutes: 30
 
     steps:
-      - uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
+      - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
 
       - uses: astral-sh/setup-uv@37802adc94f370d6bfd71619e3f0bf239e1f3b78 # v7.6.0
         with:

.github/workflows/pre-commit.yml

@@ -28,7 +28,8 @@ jobs:
             pull_number: context.payload.pull_request.number,
           });
 
-          const hasReadyLabel = pr.labels.some(l => l.name === 'ready');
+          const readyLabels = ['ready', 'ready-run-all-tests'];
+          const hasReadyLabel = pr.labels.some(l => readyLabels.includes(l.name));
           const hasVerifiedLabel = pr.labels.some(l => l.name === 'verified');
 
           const { data: mergedPRs } = await github.rest.search.issuesAndPullRequests({
@@ -40,7 +41,7 @@ jobs:
           if (hasReadyLabel || hasVerifiedLabel || mergedCount >= 4) {
             core.info(`Check passed: verified label=${hasVerifiedLabel}, ready label=${hasReadyLabel}, 4+ merged PRs=${mergedCount >= 4}`);
           } else {
-            core.setFailed(`PR must have the 'verified' or 'ready' (which also triggers tests) label or the author must have at least 4 merged PRs (found ${mergedCount}).`);
+            core.setFailed(`PR must have the 'verified', 'ready', or 'ready-run-all-tests' label (the ready labels also trigger tests) or the author must have at least 4 merged PRs (found ${mergedCount}).`);
           }
 
   pre-commit:
@@ -48,7 +49,7 @@ jobs:
     if: always() && (needs.pre-run-check.result == 'success' || needs.pre-run-check.result == 'skipped')
     runs-on: [self-hosted, linux, x64, vllm-runners]
     steps:
-    - uses: actions/checkout@8e8c483db84b4bee98b60c0593521ed34d9990e8 # v6.0.1
+    - uses: actions/checkout@9c091bb21b7c1c1d1991bb908d89e4e9dddfe3e0 # v7.0.0
     - uses: actions/setup-python@83679a892e2d95755f2dac6acb0bfd1e9ac5d548 # v6.1.0
       with:
         python-version: "3.12"

.gitignore

@@ -18,6 +18,9 @@ vllm/third_party/deep_gemm/
 # fmha_sm100 vendored package built from source
 vllm/third_party/fmha_sm100/
 
+# tml-fa4 vendored package built from source
+vllm/third_party/tml_fa4/
+
 # triton jit
 .triton
 
@@ -254,3 +257,4 @@ vllm/grpc/vllm_engine_pb2.pyi
 
 # Ignore generated cpu headers 
 csrc/cpu/cpu_attn_dispatch_generated.h
+rust-coverage-tools/

.pre-commit-config.yaml

@@ -30,7 +30,7 @@ repos:
   - id: markdownlint-cli2
     language_version: lts
     args: [--fix]
-    exclude: ^CLAUDE\.md$
+    exclude: (^|/)CLAUDE\.md$
 - repo: https://github.com/rhysd/actionlint
   rev: v1.7.7
   hooks:
@@ -131,6 +131,19 @@ repos:
         --python-version, "3.12",
       ]
       files: ^requirements/(common|xpu|test/xpu)\.(in|txt)$
+    - id: pip-compile
+      alias: pip-compile-cpu
+      name: pip-compile-cpu
+      args: [
+        requirements/test/cuda.in,
+        -o, requirements/test/cpu.txt,
+        --index-strategy, unsafe-best-match,
+        --torch-backend, cpu,
+        --python-platform, x86_64-manylinux_2_28,
+        --python-version, "3.12",
+      ]
+      files: ^requirements/(common|cpu|test/(cuda|cpu))\.(in|txt)$
+      exclude: ^requirements/test/cuda\.txt$
     - id: pip-compile
       alias: pip-compile-docs
       name: pip-compile-docs
@@ -197,7 +210,7 @@ repos:
     name: Check SPDX headers
     entry: python tools/pre_commit/check_spdx_header.py
     language: python
-    types: [python]
+    types_or: [python, rust, proto]
   - id: check-root-lazy-imports
     name: Check root lazy imports
     entry: python tools/pre_commit/check_init_lazy_imports.py

.yapfignore

@@ -1,2 +0,0 @@
-collect_env.py
-vllm/model_executor/layers/fla/ops/*.py

AGENTS.md

@@ -29,6 +29,7 @@ Do not open one-off PRs for tiny edits (single typo, isolated style change, one
 - PR descriptions for AI-assisted work **must** include:
     - Why this is not duplicating an existing PR.
     - Test commands run and results.
+    - Model evaluation results when the change affects output, accuracy, or serving.
     - Clear statement that AI assistance was used.
 
 ### Fail-closed behavior
@@ -66,23 +67,38 @@ VLLM_USE_PRECOMPILED=1 uv pip install -e . --torch-backend=auto
 uv pip install -e . --torch-backend=auto
 ```
 
-### Running tests
+### Tests
 
 > Requires [Environment setup](#environment-setup) and [Installing dependencies](#installing-dependencies).
 
 ```bash
-# Install test dependencies.
-# requirements/test/cuda.txt is pinned to x86_64; on other platforms, use the
-# unpinned source file instead:
-uv pip install -r requirements/test/cuda.in    # resolves for current platform
-# Or on x86_64:
-uv pip install -r requirements/test/cuda.txt
+# Install test dependencies (use cuda.in on non-x86_64):
+uv pip install -r requirements/test/cuda.in
 
-# Run a specific test file (use .venv/bin/python directly;
-# `source activate` does not persist in non-interactive shells):
+# Run a specific test file:
 .venv/bin/python -m pytest tests/path/to/test_file.py -v
 ```
 
+When adding tests:
+
+- **Design before you write.** Answer four questions first: what is the module
+  for, what is its I/O contract, what failure am I guarding against, and what is
+  the cheapest level that catches it (unit over integration over e2e)?
+- **Reuse before create.** Extend existing test files, `conftest.py` fixtures, and
+  helpers; add a new file only when no nearby suite fits.
+- **Test behavior with intent.** Assert observable outcomes through public APIs;
+  state why in the name or docstring. Skip trivial wiring; flaky tests are worse
+  than no tests.
+- **Keep it minimal.** One behavior per test and the smallest setup that
+  triggers it; if the test diff dwarfs the code change, cut scope.
+- **No one-off kernel benchmarks in `tests/`.** Put kernel perf work in
+  `benchmarks/kernels/`; prove correctness in existing pytest suites.
+- **Run model evals for model-affecting changes.** Search `tests/evals/` or use
+  `vllm bench` and include results in the PR — do not wait for reviewers to ask.
+
+For model-specific requirements, see
+[`docs/contributing/model/tests.md`](docs/contributing/model/tests.md).
+
 ### Running linters
 
 > Requires [Environment setup](#environment-setup).
@@ -107,23 +123,18 @@ Use [Google-style docstrings](https://google.github.io/styleguide/pyguide.html#3
 
 ### Coding style guidelines
 
-Follow these rules for all code changes in this repository:
-
-- Try to match existing code style.
-- Code should be self-documenting and self-explanatory.
-- Keep comments and docstrings minimal and concise.
+- Match existing code style
+- Minimize use of comments. Eliminate comments which are redundant, preferring legible and self-documenting code. When used, keep docstrings and comments brief and direct.
 - Assume the reader is familiar with vLLM.
 
 ### Commit messages
 
-Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`). For example:
+Add attribution using commit trailers such as `Co-authored-by:` (other projects use `Assisted-by:` or `Generated-by:`):
 
 ```text
 Your commit message here
 
-Co-authored-by: GitHub Copilot
-Co-authored-by: Claude
-Co-authored-by: gemini-code-assist
+Co-authored-by: Agent Name Here
 Signed-off-by: Your Name <your.email@example.com>
 ```
 

CMakeLists.txt

@@ -70,6 +70,15 @@ endif()
 #
 set(TORCH_SUPPORTED_VERSION_CUDA "2.11.0")
 set(TORCH_SUPPORTED_VERSION_ROCM "2.11.0")
+# TORCH_NIGHTLY=1 builds run against unpinned nightly wheels, so the supported-
+# version check would always warn. Only treat it as a nightly build when the
+# value is exactly "1" (the bootstrap exports TORCH_NIGHTLY=0 by default, which
+# must NOT suppress the warning for normal builds).
+if (DEFINED ENV{TORCH_NIGHTLY} AND "$ENV{TORCH_NIGHTLY}" STREQUAL "1")
+  set(TORCH_NIGHTLY_BUILD TRUE)
+else()
+  set(TORCH_NIGHTLY_BUILD FALSE)
+endif()
 
 #
 # Try to find python package with an executable that exactly matches
@@ -140,6 +149,21 @@ if(Python_VERSION VERSION_GREATER_EQUAL "3.11")
     WITH_SOABI)
 endif()
 
+#
+# fs_io extension (pure CXX; must stay above the non-CUDA device branch
+# so CPU builds define the target before the early return).
+# GIL-releasing filesystem helpers for FileSystemTierManager.
+#
+if(Python_VERSION VERSION_GREATER_EQUAL "3.11")
+  define_extension_target(
+    fs_io_C
+    DESTINATION vllm
+    LANGUAGE CXX
+    SOURCES csrc/fs_io.cpp
+    USE_SABI 3.11
+    WITH_SOABI)
+endif()
+
 #
 # Forward the non-CUDA device extensions to external CMake scripts.
 #
@@ -160,7 +184,7 @@ endif()
 if (NOT HIP_FOUND AND NOT PYTORCH_FOUND_HIP AND CUDA_FOUND)
   set(VLLM_GPU_LANG "CUDA")
 
-  if (NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
+  if (NOT TORCH_NIGHTLY_BUILD AND NOT Torch_VERSION VERSION_EQUAL ${TORCH_SUPPORTED_VERSION_CUDA})
     message(WARNING "Pytorch version ${TORCH_SUPPORTED_VERSION_CUDA} "
       "expected for CUDA build, saw ${Torch_VERSION} instead.")
   endif()
@@ -173,7 +197,7 @@ elseif(HIP_FOUND OR PYTORCH_FOUND_HIP)
   enable_language(HIP)
 
   # ROCm 5.X and 6.X
-  if (ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
+  if (NOT TORCH_NIGHTLY_BUILD AND ROCM_VERSION_DEV_MAJOR GREATER_EQUAL 5 AND
       Torch_VERSION VERSION_LESS ${TORCH_SUPPORTED_VERSION_ROCM})
     message(WARNING "Pytorch version >= ${TORCH_SUPPORTED_VERSION_ROCM} "
       "expected for ROCm build, saw ${Torch_VERSION} instead.")
@@ -335,9 +359,7 @@ endif()
 if(VLLM_GPU_LANG STREQUAL "HIP")
   set(VLLM_EXT_SRC
     "csrc/torch_bindings.cpp"
-    "csrc/custom_quickreduce.cu"
-    "csrc/cuda_view.cu"
-    "csrc/libtorch_stable/cuda_utils_kernels.cu")
+    "csrc/custom_quickreduce.cu")
 
   message(STATUS "Enabling C extension.")
   define_extension_target(
@@ -365,7 +387,10 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
   #
   set(VLLM_STABLE_EXT_SRC
     "csrc/libtorch_stable/torch_bindings.cpp"
+    "csrc/libtorch_stable/cuda_view.cu"
+    "csrc/libtorch_stable/cuda_utils_kernels.cu"
     "csrc/libtorch_stable/activation_kernels.cu"
+    "csrc/libtorch_stable/ngram_embedding_kernels.cu"
     "csrc/libtorch_stable/quantization/activation_kernels.cu"
     "csrc/libtorch_stable/quantization/w8a8/int8/scaled_quant.cu"
     "csrc/libtorch_stable/quantization/w8a8/fp8/common.cu"
@@ -384,9 +409,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
     "csrc/libtorch_stable/sampler.cu"
     "csrc/libtorch_stable/topk.cu"
     "csrc/libtorch_stable/mamba/selective_scan_fwd.cu"
-    "csrc/libtorch_stable/attention/paged_attention_v1.cu"
-    "csrc/libtorch_stable/attention/paged_attention_v2.cu"
-    "csrc/libtorch_stable/cache_kernels.cu"
     "csrc/libtorch_stable/cache_kernels.cu"
     "csrc/libtorch_stable/cache_kernels_fused.cu"
     "csrc/libtorch_stable/custom_all_reduce.cu"
@@ -444,8 +466,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
     FetchContent_MakeAvailable(cutlass)
 
     list(APPEND VLLM_STABLE_EXT_SRC
-      "csrc/libtorch_stable/cuda_view.cu"
-      "csrc/libtorch_stable/cuda_utils_kernels.cu"
       "csrc/libtorch_stable/cutlass_extensions/common.cpp"
       "csrc/libtorch_stable/quantization/w8a8/cutlass/scaled_mm_entry.cu"
       "csrc/libtorch_stable/quantization/fp4/nvfp4_quant_entry.cu"
@@ -1076,14 +1096,15 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
     USE_SABI 3
     WITH_SOABI)
 
+  # Set TORCH_TARGET_VERSION for stable ABI compatibility.
+  # This ensures we only use C-shim APIs available in PyTorch 2.11.
+  # _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
+  # which is currently set to 2.11.
+  target_compile_definitions(_C_stable_libtorch PRIVATE
+    TORCH_TARGET_VERSION=0x020B000000000000ULL)
+
   # Needed to use cuda/hip APIs from C-shim
   if(VLLM_GPU_LANG STREQUAL "CUDA")
-    # Set TORCH_TARGET_VERSION for stable ABI compatibility.
-    # This ensures we only use C-shim APIs available in PyTorch 2.11.
-    # _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
-    # which is currently set to 2.11.
-    target_compile_definitions(_C_stable_libtorch PRIVATE
-      TORCH_TARGET_VERSION=0x020B000000000000ULL)
     target_compile_definitions(_C_stable_libtorch PRIVATE USE_CUDA)
     if(COOPERATIVE_TOPK_ARCHS)
       target_compile_definitions(_C_stable_libtorch PRIVATE
@@ -1093,12 +1114,6 @@ if(VLLM_GPU_LANG STREQUAL "CUDA" OR VLLM_GPU_LANG STREQUAL "HIP")
     target_compile_definitions(_C_stable_libtorch PRIVATE
       CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
   elseif(VLLM_GPU_LANG STREQUAL "HIP")
-    # Set TORCH_TARGET_VERSION for stable ABI compatibility.
-    # This ensures we only use C-shim APIs available in PyTorch 2.10.
-    # _C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
-    # which is currently set to 2.10.
-    target_compile_definitions(_C_stable_libtorch PRIVATE
-      TORCH_TARGET_VERSION=0x020A000000000000ULL)
     target_compile_definitions(_C_stable_libtorch PRIVATE USE_ROCM)
   endif()
 
@@ -1306,25 +1321,20 @@ define_extension_target(
   USE_SABI 3
   WITH_SOABI)
 
+# Set TORCH_TARGET_VERSION for stable ABI compatibility.
+# This ensures we only use C-shim APIs available in PyTorch 2.11.
+# _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
+# which is currently set to 2.11.
+target_compile_definitions(_moe_C_stable_libtorch PRIVATE
+  TORCH_TARGET_VERSION=0x020B000000000000ULL)
+
 # Needed to use cuda/hip APIs from C-shim
 if(VLLM_GPU_LANG STREQUAL "CUDA")
-  # Set TORCH_TARGET_VERSION for stable ABI compatibility.
-  # This ensures we only use C-shim APIs available in PyTorch 2.11.
-  # _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
-  # which is currently set to 2.11.
-  target_compile_definitions(_moe_C_stable_libtorch PRIVATE
-    TORCH_TARGET_VERSION=0x020B000000000000ULL)
   target_compile_definitions(_moe_C_stable_libtorch PRIVATE USE_CUDA)
   # Needed by CUTLASS kernels
   target_compile_definitions(_moe_C_stable_libtorch PRIVATE
     CUTLASS_ENABLE_DIRECT_CUDA_DRIVER_CALL=1)
 elseif(VLLM_GPU_LANG STREQUAL "HIP")
-  # Set TORCH_TARGET_VERSION for stable ABI compatibility.
-  # This ensures we only use C-shim APIs available in PyTorch 2.10.
-  # _moe_C_stable_libtorch is abi compatible with PyTorch >= TORCH_TARGET_VERSION
-  # which is currently set to 2.10.
-  target_compile_definitions(_moe_C_stable_libtorch PRIVATE
-    TORCH_TARGET_VERSION=0x020A000000000000ULL)
   target_compile_definitions(_moe_C_stable_libtorch PRIVATE USE_ROCM)
 endif()
 
@@ -1354,6 +1364,7 @@ if(VLLM_GPU_LANG STREQUAL "HIP")
   set(VLLM_ROCM_EXT_SRC
     "csrc/rocm/torch_bindings.cpp"
     "csrc/rocm/skinny_gemms.cu"
+    "csrc/rocm/skinny_gemms_int4.cu"
     "csrc/rocm/attention.cu")
 
   set(VLLM_ROCM_HAS_GFX1100 OFF)
@@ -1397,6 +1408,7 @@ if (VLLM_GPU_LANG STREQUAL "CUDA")
     include(cmake/external_projects/fmha_sm100.cmake)
     include(cmake/external_projects/flashmla.cmake)
     include(cmake/external_projects/qutlass.cmake)
+    include(cmake/external_projects/tml_fa4.cmake)
 
     # vllm-flash-attn should be last as it overwrites some CMake functions
     include(cmake/external_projects/vllm_flash_attn.cmake)

README.md

@@ -48,7 +48,7 @@ vLLM is flexible and easy to use with:
 - Tool calling and reasoning parsers
 - OpenAI-compatible API server, plus Anthropic Messages API and gRPC support
 - Efficient multi-LoRA support for dense and MoE layers
-- Support for NVIDIA GPUs, AMD GPUs, and x86/ARM/PowerPC CPUs. Additionally, diverse hardware plugins such as Google TPUs, Intel Gaudi, IBM Spyre, Huawei Ascend, Rebellions NPU, Apple Silicon, MetaX GPU, and more.
+- Support for NVIDIA GPUs, AMD GPUs, Intel GPUs, and x86/ARM/PowerPC CPUs. Additionally, diverse hardware plugins such as Google TPUs, Intel Gaudi, IBM Spyre, Huawei Ascend, Rebellions NPU, Apple Silicon, MetaX GPU, and more.
 
 vLLM seamlessly supports 200+ model architectures on Hugging Face, including:
 

benchmarks/attention_benchmarks/benchmark.py

@@ -75,7 +75,11 @@ def run_mla_benchmark(config: BenchmarkConfig, **kwargs) -> BenchmarkResult:
     from mla_runner import run_mla_benchmark as run_mla
 
     return run_mla(
-        config.backend, config, prefill_backend=config.prefill_backend, **kwargs
+        config.backend,
+        config,
+        prefill_backend=config.prefill_backend,
+        sparse_mla_force_mqa=config.sparse_mla_force_mqa,
+        **kwargs,
     )
 
 
@@ -592,6 +596,30 @@ def main():
         default="profile",
         help="Output file name for ncu profile (default: 'profile').",
     )
+    parser.add_argument(
+        "--torch-profile",
+        action="store_true",
+        default=False,
+        help="Collect a PyTorch profiler Chrome trace for each benchmark run.",
+    )
+    parser.add_argument(
+        "--torch-profile-dir",
+        default=None,
+        help="Directory for PyTorch profiler traces.",
+    )
+    parser.add_argument(
+        "--torch-profile-iters",
+        type=int,
+        default=3,
+        help="Number of forward passes to record per PyTorch profiler trace.",
+    )
+    parser.add_argument(
+        "--sparse-mla-mha-variants",
+        nargs="+",
+        default=None,
+        choices=["dense_mha", "mqa"],
+        help="Sparse MLA variants to run in mha_vs_mqa mode. Defaults to both.",
+    )
 
     # Parameter sweep (use YAML config for advanced sweeps)
     parser.add_argument(
@@ -641,6 +669,7 @@ def main():
 
         # Prefill backends (e.g., ["fa3", "fa4"])
         args.prefill_backends = yaml_config.get("prefill_backends", None)
+        args.prefill_backend = yaml_config.get("prefill_backend", None)
 
         # FP8 output benchmark knobs; CLI wins.
         if args.fp8_output_scale is None:
@@ -683,6 +712,9 @@ def main():
             args.num_q_heads = model.get("num_q_heads", args.num_q_heads)
             args.num_kv_heads = model.get("num_kv_heads", args.num_kv_heads)
             args.block_size = model.get("block_size", args.block_size)
+            args.max_model_len = model.get(
+                "max_model_len", getattr(args, "max_model_len", None)
+            )
             # MLA-specific dimensions
             args.kv_lora_rank = model.get("kv_lora_rank", args.kv_lora_rank)
             args.qk_nope_head_dim = model.get("qk_nope_head_dim", args.qk_nope_head_dim)
@@ -701,6 +733,21 @@ def main():
             args.cuda_graphs = yaml_config["cuda_graphs"]
         if "ncu_profile" in yaml_config:
             args.ncu_profile = yaml_config["ncu_profile"]
+        if "torch_profile" in yaml_config:
+            args.torch_profile = yaml_config["torch_profile"]
+        if "torch_profile_dir" in yaml_config:
+            args.torch_profile_dir = yaml_config["torch_profile_dir"]
+        if "torch_profile_iters" in yaml_config:
+            args.torch_profile_iters = yaml_config["torch_profile_iters"]
+        args.sparse_mla_topk_pattern = yaml_config.get(
+            "sparse_mla_topk_pattern", "random"
+        )
+        args.sparse_mla_dense_mha_max_seq_len = yaml_config.get(
+            "sparse_mla_dense_mha_max_seq_len", None
+        )
+        args.sparse_mla_mha_variants = yaml_config.get(
+            "sparse_mla_mha_variants", args.sparse_mla_mha_variants
+        )
 
         # Parameter sweep configuration
         if "parameter_sweep" in yaml_config:
@@ -842,8 +889,6 @@ def main():
                         num_kv_heads=args.num_kv_heads,
                         block_size=args.block_size,
                         device=args.device,
-                        repeats=args.repeats,
-                        warmup_iters=args.warmup_iters,
                         profile_memory=args.profile_memory,
                         kv_cache_dtype=args.kv_cache_dtype,
                         use_cuda_graphs=args.cuda_graphs,
@@ -1063,6 +1108,133 @@ def main():
                     f"\n  [yellow]Prefill always faster for batch_size={bs}[/]"
                 )
 
+    # Handle MHA vs MQA comparison mode for sparse MLA
+    elif hasattr(args, "mode") and args.mode == "mha_vs_mqa":
+        console.print("[yellow]Mode: MHA vs MQA comparison for sparse MLA[/]")
+
+        sparse_mla_topk_pattern = getattr(args, "sparse_mla_topk_pattern", "random")
+        dense_mha_max_seq_len = getattr(args, "sparse_mla_dense_mha_max_seq_len", None)
+        prefill_backend = getattr(args, "prefill_backend", None)
+        if prefill_backend:
+            console.print(f"Prefill backend: {prefill_backend}")
+        available_variants = [
+            ("dense_mha", False, "dense"),
+            ("mqa", True, "auto"),
+        ]
+        requested_variants = getattr(args, "sparse_mla_mha_variants", None)
+        if requested_variants is not None:
+            valid_variants = {label for label, _, _ in available_variants}
+            invalid_variants = sorted(set(requested_variants) - valid_variants)
+            if invalid_variants:
+                raise ValueError(
+                    "Invalid sparse_mla_mha_variants entries: "
+                    f"{invalid_variants}. Valid variants are: "
+                    f"{sorted(valid_variants)}"
+                )
+            requested_variant_set = set(requested_variants)
+            variants = [
+                variant
+                for variant in available_variants
+                if variant[0] in requested_variant_set
+            ]
+        else:
+            variants = available_variants
+        formatter = ResultsFormatter(console)
+        total = 0
+        for spec in args.batch_specs:
+            q_len = max(request.q_len for request in parse_batch_spec(spec))
+            for variant_label, _, _ in variants:
+                if (
+                    variant_label == "dense_mha"
+                    and dense_mha_max_seq_len is not None
+                    and q_len > dense_mha_max_seq_len
+                ):
+                    continue
+                total += len(backends)
+
+        with tqdm(total=total, desc="Benchmarking") as pbar:
+            for spec in args.batch_specs:
+                q_len = max(request.q_len for request in parse_batch_spec(spec))
+                for backend in backends:
+                    for variant_label, force_mqa, mha_mode in variants:
+                        if (
+                            variant_label == "dense_mha"
+                            and dense_mha_max_seq_len is not None
+                            and q_len > dense_mha_max_seq_len
+                        ):
+                            continue
+                        config = BenchmarkConfig(
+                            backend=f"{backend}_{variant_label}",
+                            batch_spec=spec,
+                            num_layers=args.num_layers,
+                            head_dim=args.head_dim,
+                            num_q_heads=args.num_q_heads,
+                            num_kv_heads=args.num_kv_heads,
+                            block_size=args.block_size,
+                            device=args.device,
+                            max_model_len=getattr(args, "max_model_len", None),
+                            kv_cache_dtype=args.kv_cache_dtype,
+                            profile_memory=args.profile_memory,
+                            use_cuda_graphs=args.cuda_graphs,
+                            ncu_profile=args.ncu_profile,
+                            torch_profile=args.torch_profile,
+                            torch_profile_dir=args.torch_profile_dir,
+                            torch_profile_iters=args.torch_profile_iters,
+                            warmup_ms=args.warmup_ms,
+                            kv_lora_rank=getattr(args, "kv_lora_rank", None),
+                            qk_nope_head_dim=getattr(args, "qk_nope_head_dim", None),
+                            qk_rope_head_dim=getattr(args, "qk_rope_head_dim", None),
+                            v_head_dim=getattr(args, "v_head_dim", None),
+                            sparse_mla_force_mqa=force_mqa,
+                            sparse_mla_mha_mode=mha_mode,
+                            sparse_mla_dense_mha_max_seq_len=dense_mha_max_seq_len,
+                            sparse_mla_topk_pattern=sparse_mla_topk_pattern,
+                            prefill_backend=prefill_backend,
+                        )
+
+                        # run_mla_benchmark needs the real backend name
+                        from mla_runner import run_mla_benchmark as run_mla
+
+                        run_label = f"{backend}_{variant_label} {spec}"
+                        pbar.set_postfix_str(run_label)
+
+                        try:
+                            result = run_mla(
+                                backend,
+                                config,
+                                prefill_backend=prefill_backend,
+                                sparse_mla_force_mqa=force_mqa,
+                            )
+                        except Exception as e:
+                            result = BenchmarkResult(
+                                config=config,
+                                mean_time=float("inf"),
+                                median_time=float("inf"),
+                                std_time=0,
+                                min_time=float("inf"),
+                                max_time=float("inf"),
+                                error=str(e),
+                            )
+
+                        all_results.append(result)
+                        if args.output_csv:
+                            formatter.save_csv(all_results, args.output_csv)
+                        if args.output_json:
+                            formatter.save_json(all_results, args.output_json)
+
+                        if not result.success:
+                            console.print(
+                                f"[red]Error {backend}_{variant_label} "
+                                f"{spec}: {result.error}[/]"
+                            )
+
+                        pbar.update(1)
+
+        # Display results with variant labels as separate "backends"
+        console.print("\n[bold green]MHA vs MQA Results:[/]")
+        variant_backends = [f"{b}_{v}" for b in backends for v, _, _ in variants]
+        formatter.print_table(all_results, variant_backends)
+
     # Handle model parameter sweep mode
     elif hasattr(args, "model_parameter_sweep") and args.model_parameter_sweep:
         # Model parameter sweep

benchmarks/attention_benchmarks/common.py

@@ -4,8 +4,10 @@
 """Common utilities for attention benchmarking."""
 
 import csv
+import gc
 import json
 import math
+from collections.abc import Sequence
 from dataclasses import asdict, dataclass
 from pathlib import Path
 from typing import Any
@@ -44,10 +46,13 @@ def run_do_bench(
     kwargs: dict[str, Any] = {"return_mode": "all"}
     if use_cuda_graphs:
         result = triton.testing.do_bench_cudagraph(benchmark_fn, **kwargs)
+        gc.collect()
+        torch.accelerator.empty_cache()
     else:
         if warmup_ms is not None:
             kwargs["warmup"] = warmup_ms
         result = triton.testing.do_bench(benchmark_fn, **kwargs)
+    torch.accelerator.synchronize()
     return result
 
 
@@ -91,42 +96,6 @@ except ImportError:
     AttentionLayerBase = object  # Fallback
 
 
-class MockKVBProj:
-    """Mock KV projection layer for MLA prefill mode.
-
-    Mimics ColumnParallelLinear behavior for kv_b_proj in MLA backends.
-    Projects kv_c_normed to [qk_nope_head_dim + v_head_dim] per head.
-    """
-
-    def __init__(self, num_heads: int, qk_nope_head_dim: int, v_head_dim: int):
-        self.num_heads = num_heads
-        self.qk_nope_head_dim = qk_nope_head_dim
-        self.v_head_dim = v_head_dim
-        self.out_dim = qk_nope_head_dim + v_head_dim
-        self.weight = torch.empty(0, dtype=torch.bfloat16)
-
-    def __call__(self, x: torch.Tensor) -> tuple[torch.Tensor]:
-        """
-        Project kv_c_normed to output space.
-
-        Args:
-            x: Input tensor [num_tokens, kv_lora_rank]
-
-        Returns:
-            Tuple containing output tensor
-                [num_tokens, num_heads, qk_nope_head_dim + v_head_dim]
-        """
-        num_tokens = x.shape[0]
-        result = torch.randn(
-            num_tokens,
-            self.num_heads,
-            self.out_dim,
-            device=x.device,
-            dtype=x.dtype,
-        )
-        return (result,)  # Return as tuple to match ColumnParallelLinear API
-
-
 class MockIndexer:
     """Mock Indexer for sparse MLA backends.
 
@@ -158,6 +127,60 @@ class MockIndexer:
         )
         self.topk_indices_buffer[:num_tokens] = indices
 
+    def fill_indices(
+        self,
+        num_tokens: int,
+        max_kv_len: int,
+        pattern: str = "random",
+        requests: Sequence[Any] | None = None,
+    ):
+        if pattern == "random":
+            self.fill_random_indices(num_tokens, max_kv_len)
+            return
+        if pattern == "prefix":
+            indices = torch.arange(
+                self.topk_tokens,
+                dtype=torch.int32,
+                device=self.topk_indices_buffer.device,
+            )
+            indices = (indices % max_kv_len).expand(num_tokens, -1)
+            self.topk_indices_buffer[:num_tokens] = indices
+            return
+        if pattern == "sliding_window":
+            if requests is None:
+                start = max(max_kv_len - self.topk_tokens, 0)
+                indices = torch.arange(
+                    start,
+                    start + self.topk_tokens,
+                    dtype=torch.int32,
+                    device=self.topk_indices_buffer.device,
+                )
+                indices = indices.clamp(max=max_kv_len - 1).expand(num_tokens, -1)
+                self.topk_indices_buffer[:num_tokens] = indices
+                return
+
+            rows = []
+            offsets = torch.arange(
+                self.topk_tokens,
+                dtype=torch.int32,
+                device=self.topk_indices_buffer.device,
+            ) - (self.topk_tokens - 1)
+            for request in requests:
+                q_len = request.q_len
+                kv_len = request.kv_len
+                context_len = kv_len - q_len
+                positions = torch.arange(
+                    context_len,
+                    kv_len,
+                    dtype=torch.int32,
+                    device=self.topk_indices_buffer.device,
+                )
+                row_indices = positions[:, None] + offsets[None, :]
+                rows.append(row_indices.clamp(min=0, max=kv_len - 1))
+            self.topk_indices_buffer[:num_tokens] = torch.cat(rows, dim=0)
+            return
+        raise ValueError(f"Unknown sparse MLA topk pattern: {pattern}")
+
 
 class MockLayer(AttentionLayerBase):
     """Mock attention layer with scale parameters and impl.
@@ -252,10 +275,14 @@ class BenchmarkConfig:
     num_kv_heads: int
     block_size: int
     device: str
+    max_model_len: int | None = None
     dtype: torch.dtype = torch.float16
     profile_memory: bool = False
-    use_cuda_graphs: bool = False
+    use_cuda_graphs: bool = True
     ncu_profile: bool = False
+    torch_profile: bool = False
+    torch_profile_dir: str | None = None
+    torch_profile_iters: int = 3
     warmup_ms: int | None = None
 
     # "auto" or "fp8"
@@ -271,6 +298,10 @@ class BenchmarkConfig:
     # Backend-specific tuning
     num_kv_splits: int | None = None  # CUTLASS MLA
     reorder_batch_threshold: int | None = None  # FlashAttn MLA, FlashMLA
+    sparse_mla_force_mqa: bool = False  # Force MQA path for sparse MLA
+    sparse_mla_mha_mode: str = "auto"  # "auto" or "dense"
+    sparse_mla_dense_mha_max_seq_len: int | None = None
+    sparse_mla_topk_pattern: str = "random"  # "random", "prefix", "sliding_window"
     num_splits: int | None = None  # FlashAttention split-K (0=auto, 1=disabled)
 
 

benchmarks/attention_benchmarks/configs/mla_sparse_mha_vs_mqa.yaml

@@ -0,0 +1,474 @@
+# Sparse MLA benchmark: forward_mha vs forward_mqa
+#
+# Usage:
+#   python benchmark.py --config configs/mla_sparse_mha_vs_mqa.yaml
+#
+# Heatmap grid:
+#   - batch_size: 1, 2, 4, 8, 16, 32
+#   - seq_len: 32, 64, 128, 256, 512, 1024, 2048
+#   - q_len: powers of two through seq_len
+#
+# Specs with q_len < seq_len include context; the q_len == seq_len diagonal
+# covers pure prefill.
+# The model shape below is the DP case. For the TP8 run, manually change
+# model.num_q_heads from 128 to 16 before rerunning this benchmark.
+
+mode: mha_vs_mqa
+
+model:
+  name: "deepseek-v3"
+  num_layers: 60
+  num_q_heads: 128
+  num_kv_heads: 1
+  head_dim: 576
+  kv_lora_rank: 512
+  qk_nope_head_dim: 128
+  qk_rope_head_dim: 64
+  v_head_dim: 128
+  block_size: 128
+  max_model_len: 2048
+
+batch_specs:
+  # Batch size 1
+  # seq_len = 32
+  - "1q1s32"
+  - "1q2s32"
+  - "1q4s32"
+  - "1q8s32"
+  - "1q16s32"
+  - "1q32"
+  # seq_len = 64
+  - "1q1s64"
+  - "1q2s64"
+  - "1q4s64"
+  - "1q8s64"
+  - "1q16s64"
+  - "1q32s64"
+  - "1q64"
+  # seq_len = 128
+  - "1q1s128"
+  - "1q2s128"
+  - "1q4s128"
+  - "1q8s128"
+  - "1q16s128"
+  - "1q32s128"
+  - "1q64s128"
+  - "1q128"
+  # seq_len = 256
+  - "1q1s256"
+  - "1q2s256"
+  - "1q4s256"
+  - "1q8s256"
+  - "1q16s256"
+  - "1q32s256"
+  - "1q64s256"
+  - "1q128s256"
+  - "1q256"
+  # seq_len = 512
+  - "1q1s512"
+  - "1q2s512"
+  - "1q4s512"
+  - "1q8s512"
+  - "1q16s512"
+  - "1q32s512"
+  - "1q64s512"
+  - "1q128s512"
+  - "1q256s512"
+  - "1q512"
+  # seq_len = 1024
+  - "1q1s1024"
+  - "1q2s1024"
+  - "1q4s1024"
+  - "1q8s1024"
+  - "1q16s1024"
+  - "1q32s1024"
+  - "1q64s1024"
+  - "1q128s1024"
+  - "1q256s1024"
+  - "1q512s1024"
+  - "1q1024"
+  # seq_len = 2048
+  - "1q1s2048"
+  - "1q2s2048"
+  - "1q4s2048"
+  - "1q8s2048"
+  - "1q16s2048"
+  - "1q32s2048"
+  - "1q64s2048"
+  - "1q128s2048"
+  - "1q256s2048"
+  - "1q512s2048"
+  - "1q1024s2048"
+  - "1q2048"
+
+  # Batch size 2
+  # seq_len = 32
+  - "2q1s32"
+  - "2q2s32"
+  - "2q4s32"
+  - "2q8s32"
+  - "2q16s32"
+  - "2q32"
+  # seq_len = 64
+  - "2q1s64"
+  - "2q2s64"
+  - "2q4s64"
+  - "2q8s64"
+  - "2q16s64"
+  - "2q32s64"
+  - "2q64"
+  # seq_len = 128
+  - "2q1s128"
+  - "2q2s128"
+  - "2q4s128"
+  - "2q8s128"
+  - "2q16s128"
+  - "2q32s128"
+  - "2q64s128"
+  - "2q128"
+  # seq_len = 256
+  - "2q1s256"
+  - "2q2s256"
+  - "2q4s256"
+  - "2q8s256"
+  - "2q16s256"
+  - "2q32s256"
+  - "2q64s256"
+  - "2q128s256"
+  - "2q256"
+  # seq_len = 512
+  - "2q1s512"
+  - "2q2s512"
+  - "2q4s512"
+  - "2q8s512"
+  - "2q16s512"
+  - "2q32s512"
+  - "2q64s512"
+  - "2q128s512"
+  - "2q256s512"
+  - "2q512"
+  # seq_len = 1024
+  - "2q1s1024"
+  - "2q2s1024"
+  - "2q4s1024"
+  - "2q8s1024"
+  - "2q16s1024"
+  - "2q32s1024"
+  - "2q64s1024"
+  - "2q128s1024"
+  - "2q256s1024"
+  - "2q512s1024"
+  - "2q1024"
+  # seq_len = 2048
+  - "2q1s2048"
+  - "2q2s2048"
+  - "2q4s2048"
+  - "2q8s2048"
+  - "2q16s2048"
+  - "2q32s2048"
+  - "2q64s2048"
+  - "2q128s2048"
+  - "2q256s2048"
+  - "2q512s2048"
+  - "2q1024s2048"
+  - "2q2048"
+
+  # Batch size 4
+  # seq_len = 32
+  - "4q1s32"
+  - "4q2s32"
+  - "4q4s32"
+  - "4q8s32"
+  - "4q16s32"
+  - "4q32"
+  # seq_len = 64
+  - "4q1s64"
+  - "4q2s64"
+  - "4q4s64"
+  - "4q8s64"
+  - "4q16s64"
+  - "4q32s64"
+  - "4q64"
+  # seq_len = 128
+  - "4q1s128"
+  - "4q2s128"
+  - "4q4s128"
+  - "4q8s128"
+  - "4q16s128"
+  - "4q32s128"
+  - "4q64s128"
+  - "4q128"
+  # seq_len = 256
+  - "4q1s256"
+  - "4q2s256"
+  - "4q4s256"
+  - "4q8s256"
+  - "4q16s256"
+  - "4q32s256"
+  - "4q64s256"
+  - "4q128s256"
+  - "4q256"
+  # seq_len = 512
+  - "4q1s512"
+  - "4q2s512"
+  - "4q4s512"
+  - "4q8s512"
+  - "4q16s512"
+  - "4q32s512"
+  - "4q64s512"
+  - "4q128s512"
+  - "4q256s512"
+  - "4q512"
+  # seq_len = 1024
+  - "4q1s1024"
+  - "4q2s1024"
+  - "4q4s1024"
+  - "4q8s1024"
+  - "4q16s1024"
+  - "4q32s1024"
+  - "4q64s1024"
+  - "4q128s1024"
+  - "4q256s1024"
+  - "4q512s1024"
+  - "4q1024"
+  # seq_len = 2048
+  - "4q1s2048"
+  - "4q2s2048"
+  - "4q4s2048"
+  - "4q8s2048"
+  - "4q16s2048"
+  - "4q32s2048"
+  - "4q64s2048"
+  - "4q128s2048"
+  - "4q256s2048"
+  - "4q512s2048"
+  - "4q1024s2048"
+  - "4q2048"
+
+  # Batch size 8
+  # seq_len = 32
+  - "8q1s32"
+  - "8q2s32"
+  - "8q4s32"
+  - "8q8s32"
+  - "8q16s32"
+  - "8q32"
+  # seq_len = 64
+  - "8q1s64"
+  - "8q2s64"
+  - "8q4s64"
+  - "8q8s64"
+  - "8q16s64"
+  - "8q32s64"
+  - "8q64"
+  # seq_len = 128
+  - "8q1s128"
+  - "8q2s128"
+  - "8q4s128"
+  - "8q8s128"
+  - "8q16s128"
+  - "8q32s128"
+  - "8q64s128"
+  - "8q128"
+  # seq_len = 256
+  - "8q1s256"
+  - "8q2s256"
+  - "8q4s256"
+  - "8q8s256"
+  - "8q16s256"
+  - "8q32s256"
+  - "8q64s256"
+  - "8q128s256"
+  - "8q256"
+  # seq_len = 512
+  - "8q1s512"
+  - "8q2s512"
+  - "8q4s512"
+  - "8q8s512"
+  - "8q16s512"
+  - "8q32s512"
+  - "8q64s512"
+  - "8q128s512"
+  - "8q256s512"
+  - "8q512"
+  # seq_len = 1024
+  - "8q1s1024"
+  - "8q2s1024"
+  - "8q4s1024"
+  - "8q8s1024"
+  - "8q16s1024"
+  - "8q32s1024"
+  - "8q64s1024"
+  - "8q128s1024"
+  - "8q256s1024"
+  - "8q512s1024"
+  - "8q1024"
+  # seq_len = 2048
+  - "8q1s2048"
+  - "8q2s2048"
+  - "8q4s2048"
+  - "8q8s2048"
+  - "8q16s2048"
+  - "8q32s2048"
+  - "8q64s2048"
+  - "8q128s2048"
+  - "8q256s2048"
+  - "8q512s2048"
+  - "8q1024s2048"
+  - "8q2048"
+
+  # Batch size 16
+  # seq_len = 32
+  - "16q1s32"
+  - "16q2s32"
+  - "16q4s32"
+  - "16q8s32"
+  - "16q16s32"
+  - "16q32"
+  # seq_len = 64
+  - "16q1s64"
+  - "16q2s64"
+  - "16q4s64"
+  - "16q8s64"
+  - "16q16s64"
+  - "16q32s64"
+  - "16q64"
+  # seq_len = 128
+  - "16q1s128"
+  - "16q2s128"
+  - "16q4s128"
+  - "16q8s128"
+  - "16q16s128"
+  - "16q32s128"
+  - "16q64s128"
+  - "16q128"
+  # seq_len = 256
+  - "16q1s256"
+  - "16q2s256"
+  - "16q4s256"
+  - "16q8s256"
+  - "16q16s256"
+  - "16q32s256"
+  - "16q64s256"
+  - "16q128s256"
+  - "16q256"
+  # seq_len = 512
+  - "16q1s512"
+  - "16q2s512"
+  - "16q4s512"
+  - "16q8s512"
+  - "16q16s512"
+  - "16q32s512"
+  - "16q64s512"
+  - "16q128s512"
+  - "16q256s512"
+  - "16q512"
+  # seq_len = 1024
+  - "16q1s1024"
+  - "16q2s1024"
+  - "16q4s1024"
+  - "16q8s1024"
+  - "16q16s1024"
+  - "16q32s1024"
+  - "16q64s1024"
+  - "16q128s1024"
+  - "16q256s1024"
+  - "16q512s1024"
+  - "16q1024"
+  # seq_len = 2048
+  - "16q1s2048"
+  - "16q2s2048"
+  - "16q4s2048"
+  - "16q8s2048"
+  - "16q16s2048"
+  - "16q32s2048"
+  - "16q64s2048"
+  - "16q128s2048"
+  - "16q256s2048"
+  - "16q512s2048"
+  - "16q1024s2048"
+  - "16q2048"
+
+  # Batch size 32
+  # seq_len = 32
+  - "32q1s32"
+  - "32q2s32"
+  - "32q4s32"
+  - "32q8s32"
+  - "32q16s32"
+  - "32q32"
+  # seq_len = 64
+  - "32q1s64"
+  - "32q2s64"
+  - "32q4s64"
+  - "32q8s64"
+  - "32q16s64"
+  - "32q32s64"
+  - "32q64"
+  # seq_len = 128
+  - "32q1s128"
+  - "32q2s128"
+  - "32q4s128"
+  - "32q8s128"
+  - "32q16s128"
+  - "32q32s128"
+  - "32q64s128"
+  - "32q128"
+  # seq_len = 256
+  - "32q1s256"
+  - "32q2s256"
+  - "32q4s256"
+  - "32q8s256"
+  - "32q16s256"
+  - "32q32s256"
+  - "32q64s256"
+  - "32q128s256"
+  - "32q256"
+  # seq_len = 512
+  - "32q1s512"
+  - "32q2s512"
+  - "32q4s512"
+  - "32q8s512"
+  - "32q16s512"
+  - "32q32s512"
+  - "32q64s512"
+  - "32q128s512"
+  - "32q256s512"
+  - "32q512"
+  # seq_len = 1024
+  - "32q1s1024"
+  - "32q2s1024"
+  - "32q4s1024"
+  - "32q8s1024"
+  - "32q16s1024"
+  - "32q32s1024"
+  - "32q64s1024"
+  - "32q128s1024"
+  - "32q256s1024"
+  - "32q512s1024"
+  - "32q1024"
+  # seq_len = 2048
+  - "32q1s2048"
+  - "32q2s2048"
+  - "32q4s2048"
+  - "32q8s2048"
+  - "32q16s2048"
+  - "32q32s2048"
+  - "32q64s2048"
+  - "32q128s2048"
+  - "32q256s2048"
+  - "32q512s2048"
+  - "32q1024s2048"
+  - "32q2048"
+
+backends:
+  - FLASHMLA_SPARSE
+
+device: "cuda:0"
+profile_memory: false
+sparse_mla_dense_mha_max_seq_len: 2048
+sparse_mla_topk_pattern: "random"
+
+output:
+  csv: "benchmark_output/mla_sparse_mha_vs_mqa.csv"
+  json: "benchmark_output/mla_sparse_mha_vs_mqa.json"

benchmarks/attention_benchmarks/mla_runner.py

@@ -9,6 +9,8 @@ needing full VllmConfig integration.
 """
 
 import statistics
+import tempfile
+from pathlib import Path
 
 import numpy as np
 import torch
@@ -17,7 +19,6 @@ from common import (
     BenchmarkResult,
     MockHfConfig,
     MockIndexer,
-    MockKVBProj,
     MockLayer,
     run_do_bench,
     run_ncu_profile,
@@ -33,8 +34,59 @@ from vllm.config import (
     VllmConfig,
     set_current_vllm_config,
 )
+from vllm.model_executor.layers.linear import ColumnParallelLinear
 from vllm.v1.attention.backends.mla.prefill.registry import MLAPrefillBackendEnum
 
+
+def _safe_profile_name(value: str) -> str:
+    return "".join(c if c.isalnum() or c in "._-" else "_" for c in value)
+
+
+def _create_kv_b_proj(
+    mla_dims: dict,
+    device: torch.device,
+):
+    kv_b_proj = ColumnParallelLinear(
+        mla_dims["kv_lora_rank"],
+        mla_dims["num_q_heads"]
+        * (mla_dims["qk_nope_head_dim"] + mla_dims["v_head_dim"]),
+        bias=False,
+        params_dtype=torch.bfloat16,
+        quant_config=None,
+        prefix="benchmark.kv_b_proj",
+    ).to(device)
+    with torch.no_grad():
+        kv_b_proj.weight.copy_(torch.randn_like(kv_b_proj.weight))
+    return kv_b_proj
+
+
+def _ensure_single_rank_model_parallel() -> None:
+    import torch.distributed as dist
+
+    from vllm.distributed import (
+        ensure_model_parallel_initialized,
+        init_distributed_environment,
+        model_parallel_is_initialized,
+    )
+
+    if not dist.is_available():
+        return
+    if not dist.is_initialized():
+        with tempfile.NamedTemporaryFile(
+            prefix="vllm_bench_dist_", delete=False
+        ) as init_file:
+            distributed_init_method = f"file://{init_file.name}"
+        init_distributed_environment(
+            world_size=1,
+            rank=0,
+            distributed_init_method=distributed_init_method,
+            local_rank=0,
+            backend="nccl",
+        )
+    if not model_parallel_is_initialized():
+        ensure_model_parallel_initialized(1, 1)
+
+
 # ============================================================================
 # VllmConfig Creation
 # ============================================================================
@@ -66,10 +118,12 @@ def create_minimal_vllm_config(
     block_size: int = 128,
     max_num_seqs: int = 256,
     max_num_batched_tokens: int = 8192,
+    max_model_len: int = 32768,
     mla_dims: dict | None = None,
     index_topk: int | None = None,
     prefill_backend: str | None = None,
     kv_cache_dtype: str = "auto",
+    sparse_mla_force_mqa: bool = False,
 ) -> VllmConfig:
     """
     Create minimal VllmConfig for MLA benchmarks.
@@ -86,6 +140,8 @@ def create_minimal_vllm_config(
         prefill_backend: Prefill backend name (e.g., "fa3", "fa4", "flashinfer",
                         "trtllm"). Configures the attention config to force
                         the specified prefill backend.
+        sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
+                    forward_mqa (even prefill tokens).
 
     Returns:
         VllmConfig for benchmarking
@@ -131,7 +187,7 @@ def create_minimal_vllm_config(
             trust_remote_code=True,
             dtype="bfloat16",
             seed=0,
-            max_model_len=32768,
+            max_model_len=max_model_len,
             quantization=None,
             enforce_eager=False,
             max_logprobs=20,
@@ -163,7 +219,7 @@ def create_minimal_vllm_config(
     scheduler_config = SchedulerConfig(
         max_num_seqs=max_num_seqs,
         max_num_batched_tokens=max(max_num_batched_tokens, max_num_seqs),
-        max_model_len=32768,
+        max_model_len=max_model_len,
         is_encoder_decoder=False,
         enable_chunked_prefill=True,
     )
@@ -192,6 +248,9 @@ def create_minimal_vllm_config(
                 "flash_attn_version"
             ]
 
+    if sparse_mla_force_mqa:
+        vllm_config.attention_config.sparse_mla_force_mqa = True
+
     return vllm_config
 
 
@@ -548,12 +607,7 @@ def _create_backend_impl(
     # Calculate scale
     scale = 1.0 / np.sqrt(mla_dims["qk_nope_head_dim"] + mla_dims["qk_rope_head_dim"])
 
-    # Create mock kv_b_proj layer for prefill mode
-    mock_kv_b_proj = MockKVBProj(
-        num_heads=mla_dims["num_q_heads"],
-        qk_nope_head_dim=mla_dims["qk_nope_head_dim"],
-        v_head_dim=mla_dims["v_head_dim"],
-    )
+    kv_b_proj = _create_kv_b_proj(mla_dims, device)
 
     # Create indexer for sparse backends
     indexer = None
@@ -584,7 +638,7 @@ def _create_backend_impl(
         "qk_rope_head_dim": mla_dims["qk_rope_head_dim"],
         "qk_head_dim": mla_dims["qk_nope_head_dim"] + mla_dims["qk_rope_head_dim"],
         "v_head_dim": mla_dims["v_head_dim"],
-        "kv_b_proj": mock_kv_b_proj,
+        "kv_b_proj": kv_b_proj,
     }
 
     # Add indexer for sparse backends
@@ -785,14 +839,35 @@ def _run_single_benchmark(
     # Fill indexer with random indices for sparse backends
     is_sparse = backend_cfg.get("is_sparse", False)
     if is_sparse and indexer is not None:
-        indexer.fill_random_indices(total_q, max_kv_len)
+        indexer.fill_indices(
+            total_q,
+            max_kv_len,
+            getattr(config, "sparse_mla_topk_pattern", "random"),
+        )
 
     # Determine which forward methods to use based on metadata.
-    # Sparse MLA backends always use forward_mqa
-    has_decode = is_sparse or getattr(metadata, "decode", None) is not None
-    has_prefill = not is_sparse and getattr(metadata, "prefill", None) is not None
+    # Non-sparse backends use .decode/.prefill sub-objects.
+    # Sparse backends use num_decode_tokens/num_prefills directly.
+    #
+    # sparse_mla_force_mqa overrides: even for prefill metadata, use MQA.
+    force_mqa = getattr(config, "sparse_mla_force_mqa", False)
+    force_dense_mha = getattr(config, "sparse_mla_mha_mode", "auto") == "dense"
+    if force_mqa:
+        has_decode = True
+        has_prefill = False
+    elif is_sparse:
+        has_decode = metadata.num_decode_tokens > 0
+        has_prefill = metadata.num_prefills > 0
+    else:
+        has_decode = metadata.decode is not None
+        has_prefill = metadata.prefill is not None
     if not has_decode and not has_prefill:
         raise RuntimeError("Metadata has neither decode nor prefill metadata")
+    if is_sparse and force_dense_mha and not has_prefill:
+        raise RuntimeError(
+            "Sparse MLA dense_mha benchmark did not produce prefill metadata. "
+            "Check reorder_batch_threshold/path forcing."
+        )
 
     num_decode = (
         metadata.num_decode_tokens
@@ -871,7 +946,6 @@ def _run_single_benchmark(
                 metadata,
                 prefill_inputs["k_scale"],
                 prefill_fp8_output if fused_output else prefill_inputs["output"],
-                prefill_output_scale if fused_output else None,
             )
             if fused_output:
                 out = prefill_fp8_output
@@ -898,6 +972,48 @@ def _run_single_benchmark(
             throughput_tokens_per_sec=0.0,
         )
 
+    if config.torch_profile:
+        profile_dir = Path(
+            config.torch_profile_dir or "benchmark_outputs/torch_profiles"
+        )
+        profile_dir.mkdir(parents=True, exist_ok=True)
+        trace_name = _safe_profile_name(f"{config.backend}_{config.batch_spec}")
+        trace_path = profile_dir / f"{trace_name}.json"
+        iters = max(config.torch_profile_iters, 1)
+
+        forward_fn()
+        torch.accelerator.synchronize()
+        with torch.profiler.profile(
+            activities=[
+                torch.profiler.ProfilerActivity.CPU,
+                torch.profiler.ProfilerActivity.CUDA,
+            ],
+            record_shapes=True,
+            profile_memory=True,
+            with_stack=False,
+        ) as prof:
+            for _ in range(iters):
+                forward_fn()
+                torch.accelerator.synchronize()
+                prof.step()
+        prof.export_chrome_trace(str(trace_path))
+        print(f"Saved PyTorch profiler trace to {trace_path}")
+        print(
+            prof.key_averages().table(
+                sort_by="cuda_time_total",
+                row_limit=25,
+            )
+        )
+        return BenchmarkResult(
+            config=config,
+            mean_time=0.0,
+            median_time=0.0,
+            std_time=0.0,
+            min_time=0.0,
+            max_time=0.0,
+            throughput_tokens_per_sec=0.0,
+        )
+
     all_ms = run_do_bench(benchmark_fn, config.use_cuda_graphs, config.warmup_ms)
 
     # Convert ms to seconds per layer
@@ -920,6 +1036,7 @@ def _run_mla_benchmark_batched(
     configs_with_params: list[tuple],  # [(config, threshold, num_splits), ...]
     index_topk: int = 2048,
     prefill_backend: str | None = None,
+    sparse_mla_force_mqa: bool = False,
     output_scale: float | None = None,
     fuse_quant_op: bool = False,
 ) -> list[BenchmarkResult]:
@@ -940,6 +1057,8 @@ def _run_mla_benchmark_batched(
         index_topk: Topk value for sparse MLA backends (default 2048)
         prefill_backend: Prefill backend name (e.g., "fa3", "fa4").
             When set, forces the specified FlashAttention version for prefill.
+        sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
+            forward_mqa (even prefill tokens).
 
     Returns:
         List of BenchmarkResult objects
@@ -980,21 +1099,41 @@ def _run_mla_benchmark_batched(
         sum(r.q_len for r in parse_batch_spec(cfg.batch_spec))
         for cfg, *_ in configs_with_params
     )
+    max_model_len = max(
+        max_total_q,
+        max(
+            getattr(cfg, "max_model_len", None) or 32768
+            for cfg, *_ in configs_with_params
+        ),
+    )
 
     # Create and set vLLM config for MLA (reused across all benchmarks)
     vllm_config = create_minimal_vllm_config(
         model_name="deepseek-v3",  # Used only for model path
         block_size=block_size,
         max_num_batched_tokens=max_total_q,
+        max_model_len=max_model_len,
         mla_dims=mla_dims,  # Use custom dims from config or default
         index_topk=index_topk if is_sparse else None,
         prefill_backend=prefill_backend,
         kv_cache_dtype=kv_cache_dtype,
+        sparse_mla_force_mqa=sparse_mla_force_mqa,
     )
 
     results = []
 
+    # Initialize workspace manager (needed by metadata builders)
+    from vllm.v1.worker.workspace import (
+        init_workspace_manager,
+        is_workspace_manager_initialized,
+    )
+
+    if not is_workspace_manager_initialized():
+        init_workspace_manager(device)
+
     with set_current_vllm_config(vllm_config):
+        _ensure_single_rank_model_parallel()
+
         # Create backend impl, layer, builder, and indexer (reused across benchmarks)
         impl, layer, builder_instance, indexer = _create_backend_impl(
             backend_cfg,
@@ -1040,9 +1179,20 @@ def _run_mla_benchmark_batched(
         for config, threshold, num_splits in configs_with_params:
             # Set threshold for this benchmark (FlashAttn/FlashMLA only)
             original_threshold = None
-            if threshold is not None and builder_instance:
+            effective_threshold = threshold
+            force_dense_mha = (
+                is_sparse
+                and getattr(config, "sparse_mla_mha_mode", "auto") == "dense"
+                and not getattr(config, "sparse_mla_force_mqa", False)
+            )
+            if force_dense_mha:
+                # Sparse MLA normally treats q_len <= 1 as decode. Use an
+                # impossible threshold so dense_mha benchmarks actually run
+                # the prefill/MHA path, including q_len=1 short extends.
+                effective_threshold = -1
+            if effective_threshold is not None and builder_instance:
                 original_threshold = builder_instance.reorder_batch_threshold
-                builder_instance.reorder_batch_threshold = threshold
+                builder_instance.reorder_batch_threshold = effective_threshold
 
             # Set num_splits for CUTLASS
             original_num_splits = None
@@ -1090,6 +1240,7 @@ def run_mla_benchmark(
     num_kv_splits: int | None = None,
     index_topk: int = 2048,
     prefill_backend: str | None = None,
+    sparse_mla_force_mqa: bool = False,
     output_scale: float | None = None,
     fuse_quant_op: bool = False,
 ) -> BenchmarkResult | list[BenchmarkResult]:
@@ -1111,6 +1262,8 @@ def run_mla_benchmark(
         index_topk: Topk value for sparse MLA backends (default 2048)
         prefill_backend: Prefill backend name (e.g., "fa3", "fa4").
             When set, forces the specified FlashAttention version for prefill.
+        sparse_mla_force_mqa: If True, forces all sparse MLA tokens through
+            forward_mqa (even prefill tokens).
         output_scale: Static per-tensor FP8 scale for prefill output (None = bf16).
         fuse_quant_op: With output_scale set, fuse the FP8 write into the prefill
             kernel vs a standalone post-quant kernel. See _run_single_benchmark.
@@ -1142,6 +1295,7 @@ def run_mla_benchmark(
         configs_with_params,
         index_topk,
         prefill_backend=prefill_backend,
+        sparse_mla_force_mqa=sparse_mla_force_mqa,
         output_scale=output_scale,
         fuse_quant_op=fuse_quant_op,
     )

benchmarks/backend_request_func.py

@@ -12,7 +12,7 @@ from dataclasses import dataclass, field
 import aiohttp
 import huggingface_hub.constants
 from tqdm.asyncio import tqdm
-from transformers import AutoTokenizer, PreTrainedTokenizer, PreTrainedTokenizerFast
+from transformers import AutoTokenizer, PythonBackend, TokenizersBackend
 
 # NOTE(simon): do not import vLLM here so the benchmark script
 # can run without vLLM installed.
@@ -609,7 +609,7 @@ def get_tokenizer(
     tokenizer_mode: str = "auto",
     trust_remote_code: bool = False,
     **kwargs,
-) -> PreTrainedTokenizer | PreTrainedTokenizerFast:
+) -> PythonBackend | TokenizersBackend:
     if pretrained_model_name_or_path is not None and not os.path.exists(
         pretrained_model_name_or_path
     ):

benchmarks/kernels/bench_cp_gather_fp8.py

@@ -69,12 +69,11 @@ def make_inputs(total_tokens, num_reqs, block_size):
     # Output workspace
     dst = torch.zeros(total_tokens, HEAD_DIM, dtype=torch.bfloat16, device="cuda")
 
-    seq_lens_t = torch.tensor(seq_lens, dtype=torch.int32, device="cuda")
     workspace_starts_t = torch.tensor(
         workspace_starts, dtype=torch.int32, device="cuda"
     )
 
-    return cache, dst, block_table, seq_lens_t, workspace_starts_t
+    return cache, dst, block_table, workspace_starts_t
 
 
 def bench_scenario(label, num_reqs, total_tokens_list, save_path):
@@ -94,7 +93,7 @@ def bench_scenario(label, num_reqs, total_tokens_list, save_path):
         )
     )
     def bench_fn(total_tokens, provider, num_reqs):
-        cache, dst, block_table, seq_lens_t, ws_starts = make_inputs(
+        cache, dst, block_table, ws_starts = make_inputs(
             total_tokens, num_reqs, BLOCK_SIZE
         )
 
@@ -102,7 +101,7 @@ def bench_scenario(label, num_reqs, total_tokens_list, save_path):
 
         ms, min_ms, max_ms = triton.testing.do_bench_cudagraph(
             lambda: ops.cp_gather_and_upconvert_fp8_kv_cache(
-                cache, dst, block_table, seq_lens_t, ws_starts, num_reqs
+                cache, dst, block_table, ws_starts, num_reqs
             ),
             quantiles=quantiles,
             rep=500,

benchmarks/kernels/benchmark_flydsl_moe_w4a16.py

@@ -17,7 +17,7 @@ from vllm.model_executor.layers.fused_moe.fused_flydsl_moe import fused_flydsl_m
 from vllm.model_executor.layers.quantization.compressed_tensors.compressed_tensors_moe import (  # noqa: E501
     compressed_tensors_moe_w4a16_flydsl,
 )
-from vllm.platforms import current_platform
+from vllm.utils.platform_utils import get_device_name_as_file_name
 
 RoutingBuffers = tuple[
     torch.Tensor,  # sorted_token_ids
@@ -259,7 +259,7 @@ def tune_flydsl_moe_w4a16(
                             )
                             us_best = us
                             tuned_config[str(num_tokens)] = tile_config
-            device_name = current_platform.get_device_name().replace(" ", "_")
+            device_name = get_device_name_as_file_name()
             tuned_config_file_name = (
                 f"E={num_experts},N={inter_dim},device_name={device_name},"
                 f"dtype=int4_w4a16,backend=flydsl.json"

benchmarks/kernels/benchmark_paged_attention.py

@@ -19,13 +19,11 @@ from vllm.utils.torch_utils import (
 logger = init_logger(__name__)
 
 NUM_BLOCKS = 128 * 1024
-PARTITION_SIZE = 512
 PARTITION_SIZE_ROCM = 256
 
 
 @torch.inference_mode()
 def main(
-    version: str,
     num_seqs: int,
     seq_len: int,
     num_query_heads: int,
@@ -82,27 +80,20 @@ def main(
 
     # Prepare for the paged attention kernel.
     output = torch.empty_like(query)
-    if version == "v2":
-        if current_platform.is_rocm():
-            global PARTITION_SIZE
-            if not args.custom_paged_attn and not current_platform.is_navi():
-                PARTITION_SIZE = 1024
-            else:
-                PARTITION_SIZE = PARTITION_SIZE_ROCM
-        num_partitions = (max_seq_len + PARTITION_SIZE - 1) // PARTITION_SIZE
-        tmp_output = torch.empty(
-            size=(num_seqs, num_query_heads, num_partitions, head_size),
-            dtype=output.dtype,
-            device=output.device,
-        )
-        exp_sums = torch.empty(
-            size=(num_seqs, num_query_heads, num_partitions),
-            dtype=torch.float32,
-            device=output.device,
-        )
-        max_logits = torch.empty_like(exp_sums)
+    num_partitions = (max_seq_len + PARTITION_SIZE_ROCM - 1) // PARTITION_SIZE_ROCM
+    tmp_output = torch.empty(
+        size=(num_seqs, num_query_heads, num_partitions, head_size),
+        dtype=output.dtype,
+        device=output.device,
+    )
+    exp_sums = torch.empty(
+        size=(num_seqs, num_query_heads, num_partitions),
+        dtype=torch.float32,
+        device=output.device,
+    )
+    max_logits = torch.empty_like(exp_sums)
 
-    def run_cuda_benchmark(num_iters: int, profile: bool = False) -> float:
+    def run_benchmark(num_iters: int, profile: bool = False) -> float:
         torch.accelerator.synchronize()
         if profile:
             torch.cuda.cudart().cudaProfilerStart()
@@ -112,67 +103,26 @@ def main(
         k_scale = v_scale = torch.tensor(1.0, dtype=torch.float32, device=device)
 
         for _ in range(num_iters):
-            if version == "v1":
-                ops.paged_attention_v1(
-                    output,
-                    query,
-                    key_cache,
-                    value_cache,
-                    num_kv_heads,
-                    scale,
-                    block_tables,
-                    seq_lens,
-                    block_size,
-                    max_seq_len,
-                    alibi_slopes,
-                    kv_cache_dtype,
-                    k_scale,
-                    v_scale,
-                )
-            elif version == "v2":
-                if not args.custom_paged_attn:
-                    ops.paged_attention_v2(
-                        output,
-                        exp_sums,
-                        max_logits,
-                        tmp_output,
-                        query,
-                        key_cache,
-                        value_cache,
-                        num_kv_heads,
-                        scale,
-                        block_tables,
-                        seq_lens,
-                        block_size,
-                        max_seq_len,
-                        alibi_slopes,
-                        kv_cache_dtype,
-                        k_scale,
-                        v_scale,
-                    )
-                else:
-                    ops.paged_attention_rocm(
-                        output,
-                        exp_sums,
-                        max_logits,
-                        tmp_output,
-                        query,
-                        key_cache,
-                        value_cache,
-                        num_kv_heads,
-                        scale,
-                        block_tables,
-                        seq_lens,
-                        None,
-                        block_size,
-                        max_seq_len,
-                        alibi_slopes,
-                        kv_cache_dtype,
-                        k_scale,
-                        v_scale,
-                    )
-            else:
-                raise ValueError(f"Invalid version: {version}")
+            ops.paged_attention_rocm(
+                output,
+                exp_sums,
+                max_logits,
+                tmp_output,
+                query,
+                key_cache,
+                value_cache,
+                num_kv_heads,
+                scale,
+                block_tables,
+                seq_lens,
+                None,
+                block_size,
+                max_seq_len,
+                alibi_slopes,
+                kv_cache_dtype,
+                k_scale,
+                v_scale,
+            )
         torch.accelerator.synchronize()
 
         end_time = time.perf_counter()
@@ -182,7 +132,6 @@ def main(
 
     # Warmup.
     print("Warming up...")
-    run_benchmark = run_cuda_benchmark
     run_benchmark(num_iters=3, profile=False)
 
     # Benchmark.
@@ -195,12 +144,13 @@ def main(
 
 if __name__ == "__main__":
     logger.warning(
-        "This script benchmarks the paged attention kernel. "
+        "This script benchmarks the ROCm paged attention kernel. "
         "By default this is no longer used in vLLM inference."
     )
+    if not current_platform.is_rocm():
+        raise RuntimeError("This benchmark requires the ROCm platform.")
 
     parser = FlexibleArgumentParser(description="Benchmark the paged attention kernel.")
-    parser.add_argument("--version", type=str, choices=["v1", "v2"], default="v2")
     parser.add_argument("--batch-size", type=int, default=8)
     parser.add_argument("--seq-len", type=int, default=4096)
     parser.add_argument("--num-query-heads", type=int, default=64)
@@ -208,7 +158,7 @@ if __name__ == "__main__":
     parser.add_argument(
         "--head-size",
         type=int,
-        choices=[64, 80, 96, 112, 120, 128, 192, 256],
+        choices=[64, 128],
         default=128,
     )
     parser.add_argument("--block-size", type=int, choices=[16, 32], default=16)
@@ -224,11 +174,7 @@ if __name__ == "__main__":
         choices=["auto", "fp8", "fp8_e5m2", "fp8_e4m3"],
         default="auto",
         help="Data type for kv cache storage. If 'auto', will use model "
-        "data type. CUDA 11.8+ supports fp8 (=fp8_e4m3) and fp8_e5m2. "
-        "ROCm (AMD GPU) supports fp8 (=fp8_e4m3)",
-    )
-    parser.add_argument(
-        "--custom-paged-attn", action="store_true", help="Use custom paged attention"
+        "data type. ROCm (AMD GPU) supports fp8 (=fp8_e4m3)",
     )
     args = parser.parse_args()
     print(args)
@@ -236,7 +182,6 @@ if __name__ == "__main__":
     if args.num_query_heads % args.num_kv_heads != 0:
         raise ValueError("num_query_heads must be divisible by num_kv_heads")
     main(
-        version=args.version,
         num_seqs=args.batch_size,
         seq_len=args.seq_len,
         num_query_heads=args.num_query_heads,

benchmarks/kernels/benchmark_rdna_hybrid_w4a16_gemm.py

@@ -0,0 +1,201 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+"""
+Benchmark the RDNAHybridW4A16LinearKernel across decode and prefill shapes.
+
+Usage:
+    python benchmark_int4_gemm.py
+    python benchmark_int4_gemm.py --models Qwen/Qwen3-4B
+    python benchmark_int4_gemm.py --group-size 128
+"""
+
+import argparse
+import copy
+import itertools
+import os
+
+import torch
+
+from vllm.triton_utils import triton
+
+# ---------------------------------------------------------------------------
+# Weight shapes: [K, N], TP_SPLIT_DIM
+# ---------------------------------------------------------------------------
+WEIGHT_SHAPES = {
+    "Qwen/Qwen3-4B": [
+        ([2560, 3840], 1),  # qkv_proj
+        ([2560, 2560], 0),  # o_proj
+        ([2560, 19456], 1),  # gate_up_proj
+        ([9728, 2560], 0),  # down_proj
+    ],
+    "Qwen/Qwen2.5-7B-Instruct": [
+        ([3584, 4608], 1),
+        ([3584, 3584], 0),
+        ([3584, 37888], 1),
+        ([18944, 3584], 0),
+    ],
+    "trymirai/SmolLM2-1.7B-Instruct-AWQ": [
+        ([2048, 6144], 1),  # qkv_proj
+        ([2048, 2048], 0),  # o_proj
+        ([2048, 16384], 1),  # gate_up_proj
+        ([8192, 2048], 0),  # down_proj
+    ],
+    "RedHatAI/Qwen3-8B-quantized.w4a16": [
+        ([4096, 6144], 1),  # qkv_proj
+        ([4096, 4096], 0),  # o_proj
+        ([4096, 24576], 1),  # gate_up_proj
+        ([12288, 4096], 0),  # down_proj
+    ],
+}
+
+
+# ---------------------------------------------------------------------------
+# Weight packing
+# ---------------------------------------------------------------------------
+def prepare_hybrid_weights(K, N, group_size, device="cuda"):
+    """Create random weights for benchmarking.
+
+    Returns (w_q_skinny, w_s_skinny, w_fp16, w_zp). The triton path derives
+    its int32 view from w_q_skinny, so no separate int32 buffer is returned.
+    """
+    num_groups = K // group_size
+
+    # Random packed weights — actual values don't matter for throughput
+    w_q_skinny_i32 = torch.randint(
+        0, 2**31, (N, K // 8), dtype=torch.int32, device=device
+    )
+    w_q_skinny = w_q_skinny_i32.view(torch.int8).contiguous()
+    w_s_skinny = torch.randn(N, num_groups, dtype=torch.float16, device=device) * 0.01
+
+    # Raw per-group zero-points for asymmetric benchmarks
+    w_zp = torch.randint(0, 16, (N, num_groups), dtype=torch.int32, device=device).to(
+        torch.float16
+    )
+
+    # FP16 baseline for F.linear
+    w_fp16 = torch.randn(N, K, dtype=torch.float16, device=device) * 0.01
+
+    return w_q_skinny, w_s_skinny, w_fp16, w_zp
+
+
+# ---------------------------------------------------------------------------
+# Benchmark
+# ---------------------------------------------------------------------------
+PROVIDERS = ["torch-fp16", "hybrid-w4a16", "hybrid-w4a16-zp"]
+
+
+@triton.testing.perf_report(
+    triton.testing.Benchmark(
+        x_names=["batch_size"],
+        x_vals=[1, 2, 4, 8, 16, 32, 64, 128, 256, 512, 1024, 2048, 4096],
+        x_log=False,
+        line_arg="provider",
+        line_vals=PROVIDERS,
+        line_names=PROVIDERS,
+        ylabel="TFLOP/s (larger is better)",
+        plot_name="FP16 vs Hybrid W4A16",
+        args={},
+    )
+)
+def benchmark(batch_size, provider, N, K, group_size, weights):
+    M = batch_size
+    device = "cuda"
+    dtype = torch.float16
+    a = torch.randn((M, K), device=device, dtype=dtype)
+
+    quantiles = [0.5, 0.2, 0.8]
+
+    if provider == "torch-fp16":
+        w_fp16 = weights["w_fp16"]
+        ms, min_ms, max_ms = triton.testing.do_bench_cudagraph(
+            lambda: torch.nn.functional.linear(a, w_fp16),
+            quantiles=quantiles,
+        )
+    elif provider in ("hybrid-w4a16", "hybrid-w4a16-zp"):
+        from vllm.model_executor.kernels.linear.mixed_precision import (
+            rdna_hybrid_w4a16 as _k,
+        )
+
+        _rdna_hybrid_w4a16_apply_impl = _k._rdna_hybrid_w4a16_apply_impl
+        from vllm.utils.platform_utils import num_compute_units
+
+        w = weights
+        cu_count = num_compute_units()
+        use_zp = provider == "hybrid-w4a16-zp"
+
+        def run():
+            return _rdna_hybrid_w4a16_apply_impl(
+                a,
+                w["w_q_skinny"],
+                w["w_s_skinny"],
+                w["w_zp"] if use_zp else None,
+                None,  # bias
+                cu_count,
+                group_size,
+            )
+
+        ms, min_ms, max_ms = triton.testing.do_bench_cudagraph(
+            run,
+            quantiles=quantiles,
+        )
+    else:
+        return 0.0, 0.0, 0.0
+
+    to_tflops = lambda t_ms: (2 * M * N * K) * 1e-12 / (t_ms * 1e-3)
+    return to_tflops(ms), to_tflops(max_ms), to_tflops(min_ms)
+
+
+def prepare_shapes(args):
+    KN_model_names = []
+    for model, tp_size in itertools.product(args.models, args.tp_sizes):
+        for KN, tp_dim in copy.deepcopy(WEIGHT_SHAPES[model]):
+            KN[tp_dim] //= tp_size
+            KN.append(model)
+            KN_model_names.append(KN)
+    return KN_model_names
+
+
+if __name__ == "__main__":
+    parser = argparse.ArgumentParser(
+        description="Benchmark RDNAHybridW4A16LinearKernel"
+    )
+    parser.add_argument(
+        "--models",
+        nargs="+",
+        type=str,
+        default=["Qwen/Qwen3-4B"],
+        choices=list(WEIGHT_SHAPES.keys()),
+    )
+    parser.add_argument("--tp-sizes", nargs="+", type=int, default=[1])
+    parser.add_argument("--group-size", type=int, default=128)
+    parser.add_argument("--save-path", type=str, default=None)
+    args = parser.parse_args()
+
+    for K, N, model in prepare_shapes(args):
+        group_size = args.group_size
+        print(f"\n{'=' * 70}")
+        print(f"{model}, N={N} K={K}, group_size={group_size}")
+        print(f"{'=' * 70}")
+
+        w_q_skinny, w_s_skinny, w_fp16, w_zp = prepare_hybrid_weights(K, N, group_size)
+
+        weights = {
+            "w_q_skinny": w_q_skinny,
+            "w_s_skinny": w_s_skinny,
+            "w_fp16": w_fp16,
+            "w_zp": w_zp,
+        }
+
+        save_path = args.save_path or f"bench_int4_res_n{N}_k{K}"
+        os.makedirs(save_path, exist_ok=True)
+        benchmark.run(
+            print_data=True,
+            show_plots=False,
+            save_path=save_path,
+            N=N,
+            K=K,
+            group_size=group_size,
+            weights=weights,
+        )
+
+    print("\nBenchmark finished!")

benchmarks/kernels/benchmark_relu_squared.py

@@ -0,0 +1,108 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+# Benchmark ReLUSquaredActivation: custom CUDA kernel vs forward_native, both
+# eager and under torch.compile (Inductor fuses relu+square into one kernel).
+
+import itertools
+
+import torch
+import torch.nn.functional as F
+
+import vllm.model_executor.layers.activation  # noqa: F401
+from vllm.benchmarks.lib.utils import default_vllm_config
+from vllm.triton_utils import triton
+from vllm.utils.argparse_utils import FlexibleArgumentParser
+from vllm.utils.torch_utils import STR_DTYPE_TO_TORCH_DTYPE, set_random_seed
+
+# Capped so the largest tensor stays under 2**31 elements: the shared activation
+# kernel computes the per-token pointer offset (blockIdx.x * d) in 32-bit, which
+# overflows for tensors with >2**32 elements. Realistic token counts are well
+# below this; the kernel-vs-native gap is already clear at these sizes.
+batch_size_range = [1, 16, 128]
+seq_len_range = [1, 16, 64, 1024]
+intermediate_size = [3072, 9728, 12288]
+configs = list(itertools.product(batch_size_range, seq_len_range, intermediate_size))
+
+
+@default_vllm_config()
+def benchmark_relu_squared(
+    batch_size: int,
+    seq_len: int,
+    intermediate_size: int,
+    provider: str,
+    dtype: torch.dtype,
+):
+    device = "cuda"
+    num_tokens = batch_size * seq_len
+    set_random_seed(42)
+    torch.set_default_device(device)
+
+    x = torch.randn(num_tokens, intermediate_size, dtype=dtype, device=device)
+    out = torch.empty_like(x)
+
+    def native(x: torch.Tensor) -> torch.Tensor:
+        return torch.square(F.relu(x))
+
+    # Verify the custom kernel matches the native implementation before timing.
+    ref = native(x)
+    torch.ops._C.relu_squared(out, x)
+    torch.testing.assert_close(out, ref)
+
+    if provider == "custom":
+        # Custom CUDA kernel — single fused kernel.
+        fn = lambda: torch.ops._C.relu_squared(out, x)
+    elif provider == "native":
+        # forward_native, eager — relu and square as separate ops.
+        fn = lambda: native(x)
+    elif provider == "native_compiled":
+        # forward_native under torch.compile — Inductor fuses relu+square.
+        # This is the real production baseline (custom ops are off when
+        # Inductor is enabled), so it is the comparison reviewers care about.
+        compiled = torch.compile(native)
+        compiled(x)  # warm up / trigger compilation before timing
+        fn = lambda: compiled(x)
+
+    ms, min_ms, max_ms = triton.testing.do_bench_cudagraph(
+        fn, quantiles=[0.5, 0.2, 0.8]
+    )
+    return ms, max_ms, min_ms
+
+
+if __name__ == "__main__":
+    parser = FlexibleArgumentParser(
+        description="Benchmark ReLUSquaredActivation: custom kernel vs native."
+    )
+    parser.add_argument(
+        "--dtype",
+        type=str,
+        choices=["half", "bfloat16", "float"],
+        default="bfloat16",
+    )
+    args = parser.parse_args()
+
+    dtype = STR_DTYPE_TO_TORCH_DTYPE[args.dtype]
+
+    perf_report = triton.testing.perf_report(
+        triton.testing.Benchmark(
+            x_names=["batch_size", "seq_len", "intermediate_size"],
+            x_vals=configs,
+            line_arg="provider",
+            line_vals=["custom", "native_compiled", "native"],
+            line_names=[
+                "Custom Kernel",
+                "Native (torch.compile)",
+                "Native (eager)",
+            ],
+            styles=[("blue", "-"), ("green", "-"), ("red", "-")],
+            ylabel="ms",
+            plot_name="relu_squared-eager-performance",
+            args={},
+        )
+    )
+
+    perf_report(
+        lambda batch_size, seq_len, intermediate_size, provider: benchmark_relu_squared(
+            batch_size, seq_len, intermediate_size, provider, dtype
+        )
+    ).run(print_data=True)

benchmarks/kernels/benchmark_w8a8_block_fp8.py

@@ -19,6 +19,7 @@ from vllm.model_executor.layers.quantization.utils.fp8_utils import (
 from vllm.platforms import current_platform
 from vllm.triton_utils import triton
 from vllm.utils.argparse_utils import FlexibleArgumentParser
+from vllm.utils.platform_utils import get_device_name_as_file_name
 
 mp.set_start_method("spawn", force=True)
 
@@ -264,7 +265,7 @@ def save_configs(
     input_type="fp8",
 ) -> None:
     os.makedirs(save_path, exist_ok=True)
-    device_name = current_platform.get_device_name().replace(" ", "_")
+    device_name = get_device_name_as_file_name()
     json_file_name = (
         f"N={N},K={K},device_name={device_name},dtype={input_type}_w8a8,"
         f"block_shape=[{block_n},{block_k}].json"

build_rust.sh

@@ -8,6 +8,8 @@
 set -euo pipefail
 
 REPO_ROOT="$(cd "$(dirname "$0")" && pwd)"
+CARGO_LLVM_COV_VERSION="0.8.7"
+COVERAGE_TOOLS_DIR="$REPO_ROOT/rust-coverage-tools"
 
 # Read the required toolchain from rust-toolchain.toml.
 TOOLCHAIN=$(grep '^channel' "$REPO_ROOT/rust-toolchain.toml" | sed 's/.*= *"\(.*\)"/\1/')
@@ -30,4 +32,39 @@ else
     PROFILE_ARG="--release"
 fi
 
+rm -rf "$COVERAGE_TOOLS_DIR"
+mkdir -p "$COVERAGE_TOOLS_DIR/bin" "$COVERAGE_TOOLS_DIR/lib"
+
+if [[ "${VLLM_RUST_COVERAGE:-0}" == "1" ]]; then
+    # rustc wrapper flags are invisible to Cargo's normal fingerprinting.
+    # Keep instrumented intermediates isolated when local builds switch modes.
+    export CARGO_TARGET_DIR="$REPO_ROOT/rust/target/coverage"
+    rustup component add --toolchain "$TOOLCHAIN" llvm-tools-preview
+    cargo +"$TOOLCHAIN" install \
+        --locked \
+        --version "$CARGO_LLVM_COV_VERSION" \
+        cargo-llvm-cov
+
+    eval "$(
+        cargo +"$TOOLCHAIN" llvm-cov show-env \
+            --manifest-path "$REPO_ROOT/rust/Cargo.toml" \
+            --sh
+    )"
+
+    # Build scripts and proc macros can run during compilation. Their profiles
+    # are unrelated to runtime coverage and would otherwise pollute the tree.
+    export LLVM_PROFILE_FILE=/dev/null
+    export VLLM_RUST_COVERAGE_OBJECTS="$COVERAGE_TOOLS_DIR/objects"
+fi
+
 python3 "$REPO_ROOT/tools/build_rust.py" "$PROFILE_ARG"
+
+if [[ "${VLLM_RUST_COVERAGE:-0}" == "1" ]]; then
+    LLVM_BIN_DIR="$(dirname "$(rustup run "$TOOLCHAIN" rustc \
+        --print target-libdir)")/bin"
+
+    cp "$LLVM_BIN_DIR"/{llvm-cov,llvm-profdata} "$COVERAGE_TOOLS_DIR/bin/"
+    chmod 0755 "$COVERAGE_TOOLS_DIR/bin/"*
+    cp -L "$LLVM_BIN_DIR"/../lib/libLLVM.so* "$COVERAGE_TOOLS_DIR/lib/"
+    chmod 0644 "$COVERAGE_TOOLS_DIR/lib/"*
+fi