Apply pre-commit formatting and use torch.accelerator API

- Apply ruff, clang-format formatting fixes
- Replace torch.cuda.set_device/device_count/synchronize with
  torch.accelerator equivalents per project convention

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
Signed-off-by: Alexander Matveev <alexm-redhat@dgx-b200-02.mgmt.accl-001.lab.rdu2.dc.redhat.com>

Signed-off-by:  <>

.buildkite/ci_config.yaml

@@ -8,6 +8,7 @@ run_all_patterns:
   - "CMakeLists.txt"
   - "requirements/common.txt"
   - "requirements/cuda.txt"
+  - "requirements/kv_connectors.txt"
   - "requirements/build/cuda.txt"
   - "requirements/test/cuda.txt"
   - "setup.py"

.buildkite/ci_config_rocm.yaml

@@ -0,0 +1,23 @@
+name: vllm_rocm_ci
+job_dirs:
+  - ".buildkite/hardware_tests"
+run_all_patterns:
+  - "docker/Dockerfile.rocm"
+  - "docker/Dockerfile.rocm_base"
+  - "docker/ci-rocm.hcl"
+  - "docker/docker-bake-rocm.hcl"
+  - ".buildkite/hardware_tests/amd.yaml"
+  - ".buildkite/scripts/ci-bake-rocm.sh"
+  - ".buildkite/scripts/hardware_ci/run-amd-test.py"
+  - ".buildkite/scripts/hardware_ci/run-amd-test.sh"
+  - "CMakeLists.txt"
+  - "requirements/common.txt"
+  - "requirements/rocm.txt"
+  - "requirements/build/rocm.txt"
+  - "requirements/test/rocm.txt"
+  - "setup.py"
+  - "csrc/"
+  - "cmake/"
+run_all_exclude_patterns:
+  - "csrc/cpu/"
+  - "cmake/cpu_extension.cmake"

.buildkite/hardware_tests/amd.yaml

@@ -1,22 +1,73 @@
-group: Hardware - AMD Build 
+group: Hardware - AMD Build
 steps:
-  - label: "AMD: :docker: build image"
-    key: image-build-amd
+  # 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
+  # differ ci_base is rebuilt and pushed automatically.
+  - label: "AMD: :docker: ensure ci_base"
+    key: ensure-ci-base-amd
     depends_on: []
     device: amd_cpu
     no_plugin: true
     commands:
-    - >
-      docker build
-      --build-arg max_jobs=16
-      --build-arg REMOTE_VLLM=1
-      --build-arg ARG_PYTORCH_ROCM_ARCH='gfx90a;gfx942;gfx950'
-      --build-arg VLLM_BRANCH=$BUILDKITE_COMMIT
-      --tag "rocm/vllm-ci:${BUILDKITE_COMMIT}"
-      -f docker/Dockerfile.rocm
-      --target test
-      --no-cache
-      --progress plain .
-    - docker push "rocm/vllm-ci:${BUILDKITE_COMMIT}"
+      - bash .buildkite/scripts/ci-bake-rocm.sh ci-base-rocm-ci-with-deps
     env:
       DOCKER_BUILDKIT: "1"
+      VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
+      PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
+      REMOTE_VLLM: "1"
+      VLLM_BRANCH: "$BUILDKITE_COMMIT"
+    retry:
+      automatic:
+        - exit_status: -1  # Agent was lost
+          limit: 1
+        - exit_status: -10  # Agent was lost
+          limit: 1
+
+  - label: "AMD: :docker: build test image and artifacts"
+    key: image-build-amd
+    depends_on:
+      - ensure-ci-base-amd
+    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
+        '
+    env:
+      DOCKER_BUILDKIT: "1"
+      VLLM_BAKE_FILE: "docker/docker-bake-rocm.hcl"
+      PYTORCH_ROCM_ARCH: "gfx90a;gfx942;gfx950"
+      IMAGE_TAG: "rocm/vllm-ci:$BUILDKITE_COMMIT"
+      REMOTE_VLLM: "1"
+      VLLM_BRANCH: "$BUILDKITE_COMMIT"
+    retry:
+      automatic:
+        - exit_status: -1  # Agent was lost
+          limit: 1
+        - exit_status: -10  # Agent was lost
+          limit: 1

.buildkite/hardware_tests/cpu.yaml

@@ -12,28 +12,35 @@ steps:
   - vllm/_custom_ops.py
   - tests/kernels/attention/test_cpu_attn.py
   - tests/kernels/moe/test_cpu_fused_moe.py
+  - tests/kernels/moe/test_cpu_quant_fused_moe.py
   - tests/kernels/test_onednn.py
   - 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
   commands:
     - |
-      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
+      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/test_onednn.py
-      pytest -x -v -s tests/kernels/test_awq_int4_to_int8.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"
 
-- label: CPU-Compatibility Tests
-  depends_on: []
-  device: intel_cpu
-  no_plugin: true
-  source_file_dependencies:
-  - cmake/cpu_extension.cmake
-  - setup.py
-  - vllm/platforms/cpu.py
-  commands:
-    - |
-      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
-      bash .buildkite/scripts/hardware_ci/run-cpu-compatibility-test.sh"
+# Note: SDE can't be downloaded from CI host because of AWS WAF
+# - label: CPU-Compatibility Tests
+#   depends_on: []
+#   device: intel_cpu
+#   no_plugin: true
+#   source_file_dependencies:
+#   - cmake/cpu_extension.cmake
+#   - setup.py
+#   - vllm/platforms/cpu.py
+#   commands:
+#     - |
+#       bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
+#       bash .buildkite/scripts/hardware_ci/run-cpu-compatibility-test.sh"
 
 - label: CPU-Language Generation and Pooling Model Tests
   depends_on: []
@@ -50,22 +57,41 @@ steps:
       pytest -x -v -s tests/models/language/generation -m cpu_model
       pytest -x -v -s tests/models/language/pooling -m cpu_model"
 
+- label: CPU-ModelRunnerV2 Tests
+  depends_on: []
+  device: intel_cpu
+  no_plugin: true
+  soft_fail: true
+  source_file_dependencies:
+  - vllm/v1/worker/cpu/
+  - vllm/v1/worker/gpu/
+  - vllm/v1/sample/ops/topk_topp_triton.py
+  - vllm/v1/sample/ops/topk_topp_sampler.py
+  - tests/v1/sample/test_topk_topp_sampler.py
+  commands:
+    - |
+      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
+      uv pip install git+https://github.com/triton-lang/triton-cpu.git@270e696d
+      VLLM_USE_V2_MODEL_RUNNER=1 pytest -x -v -s tests/models/language/generation/test_granite.py -m cpu_model
+      # TODO: move to CPU-Kernel Tests once triton-cpu has a pre-built wheel
+      pytest -x -v -s tests/v1/sample/test_topk_topp_sampler.py::TestTritonTopkTopp"
+
 - label: CPU-Quantization Model Tests
   depends_on: []
   device: intel_cpu
   no_plugin: true
   source_file_dependencies:
   - csrc/cpu/
-  - vllm/model_executor/layers/quantization/cpu_wna16.py
-  - vllm/model_executor/layers/quantization/gptq_marlin.py
+  - vllm/model_executor/layers/quantization/auto_gptq.py
   - vllm/model_executor/layers/quantization/compressed_tensors/schemes/compressed_tensors_w8a8_int8.py
-  - vllm/model_executor/layers/quantization/kernels/scaled_mm/cpu.py
-  - vllm/model_executor/layers/quantization/kernels/mixed_precision/cpu.py
+  - vllm/model_executor/kernels/linear/mixed_precision/cpu.py
+  - vllm/model_executor/kernels/linear/scaled_mm/cpu.py
+  - vllm/model_executor/layers/fused_moe/experts/cpu_moe.py
   - tests/quantization/test_compressed_tensors.py
   - tests/quantization/test_cpu_wna16.py
   commands:
     - |
-      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 20m "
+      bash .buildkite/scripts/hardware_ci/run-cpu-test.sh 45m "
       pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs
       pytest -x -v -s tests/quantization/test_cpu_wna16.py"
       

.buildkite/hardware_tests/intel.yaml

@@ -8,10 +8,3 @@ steps:
     commands: 
     - bash .buildkite/scripts/hardware_ci/run-hpu-test.sh
 
-  - label: "Intel GPU Test"
-    depends_on: []
-    soft_fail: true
-    device: intel_gpu
-    no_plugin: true
-    commands: 
-    - bash .buildkite/scripts/hardware_ci/run-xpu-test.sh

.buildkite/image_build/image_build.yaml

@@ -13,6 +13,60 @@ steps:
         - exit_status: -10  # Agent was lost
           limit: 2
 
+  - label: ":docker: :smoking: Non-root smoke tests"
+    key: image-build-smoke-test
+    depends_on:
+      - image-build
+    commands:
+    # Smoke 1: the default (root) image must still be importable
+    # under a non-root UID via `--user 2000:0`. Validates the `vllm` passwd
+    # entry + group-0-writable /home/vllm + uv path cleanup from #31959.
+    # Uses `import vllm` rather than `vllm serve --help` because the latter
+    # instantiates `VllmConfig` which requires a GPU attached to the
+    # container.
+    - docker run --rm --user 2000:0 --entrypoint python3 "$IMAGE_TAG" -c "import vllm; print(vllm.__version__)"
+    # Smoke 2: assert the non-root enabling invariants are baked
+    # into the image. Runs as UID 2000:0 via a shell so we can verify
+    # filesystem perms + passwd/group file state + wrapper presence without
+    # triggering vLLM's GPU-requiring config-init path. The opt-in
+    # `vllm-openai-nonroot` target adds only `USER vllm`, `WORKDIR
+    # /home/vllm`, and an `ENTRYPOINT` override on top of these invariants;
+    # its build correctness is reviewed at the Dockerfile level. Wrapper
+    # logic is covered separately by the pre-commit hook
+    # `test-nonroot-entrypoint` (see .pre-commit-config.yaml).
+    - |
+      docker run --rm --user 2000:0 --entrypoint /bin/sh "$IMAGE_TAG" -ec '
+        if ! getent passwd 2000 | grep -q ^vllm:; then
+          echo FAIL: UID 2000 != vllm
+          exit 1
+        fi
+        if ! id -gn 2>/dev/null | grep -qx root; then
+          echo FAIL: GID 0 not root group
+          exit 1
+        fi
+        touch /home/vllm/.smoke && rm /home/vllm/.smoke
+        touch /opt/uv/cache/.smoke && rm /opt/uv/cache/.smoke
+        if ! test -x /usr/local/bin/vllm-nonroot-entrypoint.sh; then
+          echo FAIL: wrapper missing
+          exit 1
+        fi
+        if ! test -w /etc/passwd; then
+          echo FAIL: /etc/passwd not group-writable
+          exit 1
+        fi
+        if ! test -w /etc/group; then
+          echo FAIL: /etc/group not group-writable
+          exit 1
+        fi
+        echo non-root invariants OK
+      '
+    retry:
+      automatic:
+        - exit_status: -1  # Agent was lost
+          limit: 2
+        - exit_status: -10  # Agent was lost
+          limit: 2
+
   - label: ":docker: Build CPU image"
     key: image-build-cpu
     depends_on: []
@@ -56,3 +110,21 @@ steps:
           limit: 2
         - exit_status: -10  # Agent was lost
           limit: 2
+
+  - label: ":docker: Build arm64 image"
+    key: arm64-image-build
+    depends_on: []
+    source_file_dependencies:
+      - ".buildkite/image_build/image_build.yaml"
+      - ".buildkite/image_build/image_build_arm64.sh"
+      - "docker/Dockerfile"
+    commands:
+    - .buildkite/image_build/image_build_arm64.sh $REGISTRY $REPO $BUILDKITE_COMMIT
+    env:
+      DOCKER_BUILDKIT: "1"
+    retry:
+      automatic:
+        - exit_status: -1  # Agent was lost
+          limit: 2
+        - exit_status: -10  # Agent was lost
+          limit: 2

.buildkite/image_build/image_build_arm64.sh

@@ -0,0 +1,37 @@
+#!/bin/bash
+set -e
+
+if [[ $# -lt 3 ]]; then
+  echo "Usage: $0 <registry> <repo> <commit>"
+  exit 1
+fi
+
+REGISTRY=$1
+REPO=$2
+BUILDKITE_COMMIT=$3
+
+# authenticate with AWS ECR
+aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$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
+  echo "Image found"
+  exit 0
+fi
+
+# build (Grace/GH200 is the arm64 GPU target; sm_90)
+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" \
+  --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/image_build/image_build_hpu.sh

@@ -11,7 +11,7 @@ REPO=$2
 BUILDKITE_COMMIT=$3
 
 # authenticate with AWS ECR
-aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
+aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY" || true
 
 # skip build if image already exists
 if [[ -z $(docker manifest inspect "$REGISTRY"/"$REPO":"$BUILDKITE_COMMIT"-hpu) ]]; then

.buildkite/image_build/image_build_xpu.sh

@@ -11,8 +11,8 @@ REPO=$2
 BUILDKITE_COMMIT=$3
 
 # authenticate with AWS ECR
-aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$REGISTRY"
-aws ecr get-login-password --region us-east-1 | docker login --username AWS --password-stdin 936637512419.dkr.ecr.us-east-1.amazonaws.com
+aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin "$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

.buildkite/intel_jobs/basic_correctness.yaml

@@ -0,0 +1,22 @@
+group: Basic Correctness
+depends_on:
+  - image-build-xpu
+steps:
+- label: XPU Sleep Mode
+  timeout_in_minutes: 30
+  device: intel_gpu
+  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/basic_correctness/test_cumem.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'cd tests &&
+      export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
+      pytest -v -s basic_correctness/test_mem.py::test_end_to_end'

.buildkite/intel_jobs/expert_parallelism_intel.yaml

@@ -0,0 +1,23 @@
+group: Expert Parallelism
+depends_on: 
+  - image-build-xpu
+steps:
+- label: EPLB Algorithm
+  key: eplb-algorithm
+  timeout_in_minutes: 45
+  device: intel_gpu
+  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/eplb
+  - tests/distributed/test_eplb_algo.py
+  - tests/distributed/test_eplb_utils.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'cd tests &&
+      pytest -v -s distributed/test_eplb_algo.py'

.buildkite/intel_jobs/lora_intel.yaml

@@ -18,17 +18,18 @@ steps:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
+      export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       pytest -v -s lora/test_layers.py &&
       pytest -v -s lora/test_lora_checkpoints.py &&
-      (pytest -v -s lora/test_lora_functions.py --deselect="tests/lora/test_lora_functions.py::test_lora_functions_sync" --deselect="tests/lora/test_lora_functions.py::test_lora_functions_async" || true) &&
+      pytest -v -s lora/test_lora_functions.py &&
       pytest -v -s lora/test_lora_huggingface.py &&
       pytest -v -s lora/test_lora_manager.py &&
       pytest -v -s lora/test_lora_utils.py &&
       pytest -v -s lora/test_peft_helper.py &&
       pytest -v -s lora/test_resolver.py &&
       pytest -v -s lora/test_utils.py &&
-      (pytest -v -s lora/test_add_lora.py --deselect="tests/lora/test_add_lora.py::test_add_lora" || true) &&
-      (pytest -v -s lora/test_worker.py --deselect="tests/lora/test_worker.py::test_worker_apply_lora" || true)'
+      pytest -v -s lora/test_add_lora.py  &&
+      pytest -v -s lora/test_worker.py'
 
 - label: LoRA Fused/MoE Kernels
   timeout_in_minutes: 45
@@ -46,8 +47,9 @@ steps:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
+      export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       pytest -v -s lora/test_fused_moe_lora_kernel.py && 
-      pytest -v -s lora/test_moe_lora_align_sum.py'
+      pytest -v -s lora/test_moe_lora_align_sum.py --deselect="tests/lora/test_moe_lora_align_sum.py::test_moe_lora_align_block_size_mixed_base_and_lora[1]"'
 
 - label: LoRA Punica Kernels
   timeout_in_minutes: 45
@@ -65,8 +67,9 @@ steps:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       '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[shrink-0-xpu:0-dtype0-2-2049-64-32-32]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype1-2-64000-32-4-4]" --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]" --deselect="tests/lora/test_punica_ops.py::test_kernels_hidden_size[expand-0-xpu:0-dtype1-1-102656-32-4-4]"'
+      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]"'
 
 - label: LoRA Punica FP8/XPU Ops
   timeout_in_minutes: 45
@@ -84,6 +87,7 @@ steps:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
+      export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       pytest -v -s lora/test_punica_ops_fp8.py &&
       pytest -v -s lora/test_punica_xpu_ops.py'
 
@@ -103,10 +107,12 @@ 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_qwen35_densemodel_lora.py &&
-      pytest -v -s lora/test_transformers_model.py'
+      pytest -v -s lora/test_transformers_model.py &&
+      pytest -v -s lora/test_chatglm3_tp.py &&
+      pytest -s -v lora/test_minicpmv_tp.py'
 
 - label: LoRA Multimodal
   timeout_in_minutes: 45
@@ -124,6 +130,6 @@ steps:
     - >-
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'cd tests &&
+      export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       pytest -v -s lora/test_default_mm_loras.py && 
-      (pytest -v -s lora/test_qwen3_unembed.py || true) &&
       pytest -v -s lora/test_whisper.py'

.buildkite/intel_jobs/misc_intel.yaml

@@ -38,7 +38,17 @@ steps:
     REPO: "vllm-ci-test-repo"
     VLLM_TEST_DEVICE: "xpu"
   source_file_dependencies:
-    - vllm/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/inputs/
+    - vllm/logger.py
+    - vllm/model_executor/
+    - vllm/platforms/
+    - vllm/sampling_params.py
+    - vllm/transformers_utils/
+    - vllm/utils/
+    - vllm/v1/
     - tests/v1/sample
     - tests/v1/logits_processors
     - tests/v1/test_oracle.py
@@ -49,7 +59,129 @@ steps:
       bash .buildkite/scripts/hardware_ci/run-intel-test.sh
       'export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
       cd tests &&
-      pytest -v -s v1/logits_processors &&
+      pytest -v -s v1/logits_processors --ignore=v1/logits_processors/test_custom_online.py --ignore=v1/logits_processors/test_custom_offline.py &&
       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/test_outputs.py &&
+      pytest -v -s v1/sample/test_topk_topp_sampler.py'
+
+- label: XPU CPU Offload
+  timeout_in_minutes: 60
+  device: intel_gpu
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+    - vllm/
+    - vllm/v1/kv_offload/
+    - vllm/v1/kv_connector/
+    - tests/v1/kv_offload/
+    - tests/v1/kv_connector/unit/test_offloading_connector.py
+  commands:
+    - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'export VLLM_WORKER_MULTIPROC_METHOD=spawn &&
+      cd tests &&
+      pytest -v -s v1/kv_offload &&
+      pytest -v -s v1/kv_connector/unit/test_offloading_connector.py'
+
+- label: Regression
+  key: regression
+  timeout_in_minutes: 30
+  device: intel_gpu
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
+  - tests/test_regression
+  commands:
+  - >-
+      bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+      'pip install modelscope &&
+      cd tests &&
+      pytest -v -s test_regression.py'
+
+- label: Metrics, Tracing (2 GPUs)
+  key: metrics-tracing-2-gpus
+  timeout_in_minutes: 30
+  num_devices: 2
+  device: intel_gpu
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/tracing/
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
+  - tests/v1/tracing
+  commands:
+  - >-
+    bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+    'pip install opentelemetry-sdk\>=1.26.0 opentelemetry-api\>=1.26.0 opentelemetry-exporter-otlp\>=1.26.0 opentelemetry-semantic-conventions-ai\>=0.4.1 &&
+    cd tests &&
+    pytest -v -s v1/tracing'
+
+- label: Async Engine, Inputs, Utils, Worker
+  key: async-engine-inputs-utils-worker
+  timeout_in_minutes: 30
+  device: intel_gpu
+  no_plugin: true
+  working_dir: "."
+  env:
+    REGISTRY: "public.ecr.aws/q9t5s3a7"
+    REPO: "vllm-ci-test-repo"
+    VLLM_TEST_DEVICE: "xpu"
+  source_file_dependencies:
+  - vllm/assets/
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/tokenizers/
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
+  - tests/detokenizer
+  - tests/multimodal
+  - tests/utils_
+  commands:
+  - >-
+    bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+    'cd tests &&
+    pip install av &&
+    pytest -v -s detokenizer &&
+    pytest -v -s -m "not cpu_test" ./multimodal &&
+    pytest -v -s utils_ --ignore=utils_/test_mem_utils.py'

.buildkite/intel_jobs/models_multimodal_intel.yaml

@@ -0,0 +1,111 @@
+group: Models - Multimodal
+depends_on: 
+  - image-build-xpu
+steps:
+- label: "Multi-Modal Models (Standard) 1: qwen2"
+  key: multi-modal-models-standard-1-qwen2
+  timeout_in_minutes: 45
+  device: intel_gpu
+  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 &&
+      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
+  device: intel_gpu
+  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 git+https://github.com/TIGER-AI-Lab/Mantis.git &&
+      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: 45
+  device: intel_gpu
+  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 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
+  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 &&
+      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
+  device: intel_gpu
+  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
+  - tests/models/registry.py
+  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 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/test-intel.yaml

@@ -36,9 +36,14 @@ steps:
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --attention-backend=TRITON_ATTN &&
         python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --quantization fp8 &&
         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 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 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"
     depends_on:
       - image-build-xpu
@@ -61,5 +66,24 @@ steps:
         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/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_tree_attention.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.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'
+        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 &&
+        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
+    device: intel_gpu
+    no_plugin: true
+    env:
+      REGISTRY: "public.ecr.aws/q9t5s3a7"
+      REPO: "vllm-ci-test-repo"
+    source_file_dependencies:
+      - vllm/
+      - .buildkite/intel_jobs/test-intel.yaml 
+    commands:
+      - >-
+        bash .buildkite/scripts/hardware_ci/run-intel-test.sh
+        'pip install av &&
+        cd tests &&
+        pytest -v -s entrypoints/multimodal/openai/chat_completion/test_audio_in_video.py &&
+        pytest -v -s benchmarks/test_serve_cli.py'

.buildkite/lm-eval-harness/configs/NVIDIA-Nemotron-3-Nano-30B-A3B-FP8.yaml

@@ -6,9 +6,7 @@ tasks:
     value: 0.7142
   - name: "exact_match,flexible-extract"
     value: 0.4579
-env_vars:
-  VLLM_USE_FLASHINFER_MOE_FP8: "1"
-  VLLM_FLASHINFER_MOE_BACKEND: "throughput"
+moe_backend: "flashinfer_cutlass"
 limit: 1319
 num_fewshot: 5
 max_model_len: 262144

.buildkite/lm-eval-harness/run-lm-eval-chartqa-vllm-vlm-baseline.sh

@@ -2,7 +2,7 @@
 # We can use this script to compute baseline accuracy on chartqa for vllm.
 #
 # Make sure you have lm-eval-harness installed:
-#   pip install "lm-eval[api]>=0.4.11"
+#   pip install "lm-eval[api]>=0.4.12"
 
 usage() {
     echo``

.buildkite/lm-eval-harness/run-lm-eval-gsm-hf-baseline.sh

@@ -2,7 +2,7 @@
 # We can use this script to compute baseline accuracy on GSM for transformers.
 #
 # Make sure you have lm-eval-harness installed:
-#   pip install "lm-eval[api]>=0.4.11"
+#   pip install "lm-eval[api]>=0.4.12"
 
 usage() {
     echo``

.buildkite/lm-eval-harness/run-lm-eval-gsm-vllm-baseline.sh

@@ -3,7 +3,7 @@
 # We use this for fp8, which HF does not support.
 #
 # Make sure you have lm-eval-harness installed:
-#   pip install "lm-eval[api]>=0.4.11"
+#   pip install "lm-eval[api]>=0.4.12"
 
 usage() {
     echo``

.buildkite/lm-eval-harness/run-lm-eval-mmlupro-vllm-baseline.sh

@@ -3,7 +3,7 @@
 # We use this for fp8, which HF does not support.
 #
 # Make sure you have lm-eval-harness installed:
-#   pip install "lm-eval[api]>=0.4.11"
+#   pip install "lm-eval[api]>=0.4.12"
 
 usage() {
     echo``

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

@@ -68,6 +68,10 @@ def launch_lm_eval(eval_config, tp_size):
     if current_platform.is_rocm() and "Nemotron-3" in eval_config["model_name"]:
         model_args += "attention_backend=TRITON_ATTN"
 
+    moe_backend = eval_config.get("moe_backend", None)
+    if moe_backend is not None:
+        model_args += f"moe_backend={moe_backend},"
+
     env_vars = eval_config.get("env_vars", None)
     with scoped_env_vars(env_vars):
         results = lm_eval.simple_evaluate(

.buildkite/performance-benchmarks/tests/latency-tests-arm64-cpu.json

@@ -2,7 +2,6 @@
     {
         "test_name": "latency_llama8B_tp1",
         "environment_variables": {
-            "VLLM_RPC_TIMEOUT": 100000,
             "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
             "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
             "VLLM_CPU_KVCACHE_SPACE": 40

.buildkite/performance-benchmarks/tests/latency-tests-cpu.json

@@ -2,7 +2,6 @@
     {
         "test_name": "latency_llama8B_tp2",
         "environment_variables": {
-            "VLLM_RPC_TIMEOUT": 100000,
 	    "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
 	    "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
 	    "VLLM_CPU_SGL_KERNEL": 1,

.buildkite/performance-benchmarks/tests/serving-tests-arm64-cpu.json

@@ -13,7 +13,6 @@
       200
     ],
     "server_environment_variables": {
-      "VLLM_RPC_TIMEOUT": 100000,
       "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
       "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
       "VLLM_CPU_SGL_KERNEL": 1,

.buildkite/performance-benchmarks/tests/serving-tests-cpu-asr.json

@@ -5,7 +5,6 @@
     ],
     "max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
     "server_environment_variables": {
-      "VLLM_RPC_TIMEOUT": 100000,
       "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120
     },
     "server_parameters": {

.buildkite/performance-benchmarks/tests/serving-tests-cpu-embed.json

@@ -9,7 +9,6 @@
       128
     ],
     "server_environment_variables": {
-      "VLLM_RPC_TIMEOUT": 100000,
       "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
       "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
       "VLLM_CPU_SGL_KERNEL": 1,

.buildkite/performance-benchmarks/tests/serving-tests-cpu-text.json

@@ -5,7 +5,6 @@
     ],
     "max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
     "server_environment_variables": {
-      "VLLM_RPC_TIMEOUT": 100000,
       "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
       "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
       "VLLM_CPU_SGL_KERNEL": 1,
@@ -31,30 +30,9 @@
     }
   },
   "tests": [
-    {
-      "test_name": "serving_llama8B_tp1_sharegpt",
-      "server_parameters": {
-        "tensor_parallel_size": 1
-      },
-      "client_parameters": {
-        "dataset_name": "sharegpt",
-        "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp2_sharegpt",
-      "server_parameters": {
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "dataset_name": "sharegpt",
-        "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
-      }
-    },
     {
       "test_name": "serving_llama8B_tp1_random_128_128",
       "server_parameters": {
-        "tensor_parallel_size": 1
       },
       "client_parameters": {
         "dataset_name": "random",
@@ -62,158 +40,10 @@
         "random-output-len": 128
       }
     },
-    {
-      "test_name": "serving_llama8B_tp2_random_128_128",
-      "server_parameters": {
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp4_random_128_128",
-      "server_parameters": {
-        "tensor_parallel_size": 4
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp1_random_128_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 1
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 2048
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp2_random_128_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 2048
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp4_random_128_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 4
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 2048
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp1_random_2048_128",
-      "server_parameters": {
-        "tensor_parallel_size": 1
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp2_random_2048_128",
-      "server_parameters": {
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp4_random_2048_128",
-      "server_parameters": {
-        "tensor_parallel_size": 4
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp1_random_2048_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 1
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 2048
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp2_random_2048_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 2048
-      }
-    },
-    {
-      "test_name": "serving_llama8B_tp4_random_2048_2048",
-      "server_parameters": {
-        "tensor_parallel_size": 4
-      },
-      "client_parameters": {
-        "dataset_name": "random",
-        "random-input-len": 2048,
-        "random-output-len": 2048
-      }
-    },
     {
       "test_name": "serving_llama8B_int4_tp1_random_128_128",
       "server_parameters": {
-        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
-        "tensor_parallel_size": 1
-      },
-      "client_parameters": {
-        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_int4_tp2_random_128_128",
-      "server_parameters": {
-        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
-        "tensor_parallel_size": 2
-      },
-      "client_parameters": {
-        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_int4_tp4_random_128_128",
-      "server_parameters": {
-        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
-        "tensor_parallel_size": 4
+        "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4"
       },
       "client_parameters": {
         "model": "hugging-quants/Meta-Llama-3.1-8B-Instruct-AWQ-INT4",
@@ -225,8 +55,7 @@
     {
       "test_name": "serving_llama8B_int8_tp1_random_128_128",
       "server_parameters": {
-        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
-        "tensor_parallel_size": 1
+        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8"
       },
       "client_parameters": {
         "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
@@ -236,26 +65,12 @@
       }
     },
     {
-      "test_name": "serving_llama8B_int8_tp2_random_128_128",
+      "test_name": "serving_llama1B_tp1_random_128_128",
       "server_parameters": {
-        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
-        "tensor_parallel_size": 2
+        "model": "meta-llama/Llama-3.2-1B"
       },
       "client_parameters": {
-        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
-        "dataset_name": "random",
-        "random-input-len": 128,
-        "random-output-len": 128
-      }
-    },
-    {
-      "test_name": "serving_llama8B_int8_tp4_random_128_128",
-      "server_parameters": {
-        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
-        "tensor_parallel_size": 4
-      },
-      "client_parameters": {
-        "model": "RedHatAI/Meta-Llama-3.1-8B-Instruct-quantized.w8a8",
+        "model": "meta-llama/Llama-3.2-1B",
         "dataset_name": "random",
         "random-input-len": 128,
         "random-output-len": 128
@@ -264,8 +79,7 @@
     {
       "test_name": "serving_llama3B_tp1_random_128_128",
       "server_parameters": {
-        "model": "meta-llama/Llama-3.2-3B-Instruct",
-        "tensor_parallel_size": 1
+        "model": "meta-llama/Llama-3.2-3B-Instruct"
       },
       "client_parameters": {
         "model": "meta-llama/Llama-3.2-3B-Instruct",
@@ -274,11 +88,22 @@
         "random-output-len": 128
       }
     },
+    {
+      "test_name": "serving_llama70B_tp1_random_128_128",
+      "server_parameters": {
+        "model": "meta-llama/Llama-3.3-70B-Instruct"
+      },
+      "client_parameters": {
+        "model": "meta-llama/Llama-3.3-70B-Instruct",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
     {
       "test_name": "serving_granite2B_tp1_random_128_128",
       "server_parameters": {
-        "model": "ibm-granite/granite-3.2-2b-instruct",
-        "tensor_parallel_size": 1
+        "model": "ibm-granite/granite-3.2-2b-instruct"
       },
       "client_parameters": {
         "model": "ibm-granite/granite-3.2-2b-instruct",
@@ -290,8 +115,7 @@
     {
       "test_name": "serving_qwen1.7B_tp1_random_128_128",
       "server_parameters": {
-        "model": "Qwen/Qwen3-1.7B",
-        "tensor_parallel_size": 1
+        "model": "Qwen/Qwen3-1.7B"
       },
       "client_parameters": {
         "model": "Qwen/Qwen3-1.7B",
@@ -303,8 +127,7 @@
     {
       "test_name": "serving_qwen4B_tp1_random_128_128",
       "server_parameters": {
-        "model": "Qwen/Qwen3-4B",
-        "tensor_parallel_size": 1
+        "model": "Qwen/Qwen3-4B"
       },
       "client_parameters": {
         "model": "Qwen/Qwen3-4B",
@@ -316,8 +139,7 @@
     {
       "test_name": "serving_qwen8B_tp1_random_128_128",
       "server_parameters": {
-        "model": "Qwen/Qwen3-8B",
-        "tensor_parallel_size": 1
+        "model": "Qwen/Qwen3-8B"
       },
       "client_parameters": {
         "model": "Qwen/Qwen3-8B",
@@ -326,11 +148,34 @@
         "random-output-len": 128
       }
     },
+    {
+      "test_name": "serving_qwen14B_tp1_random_128_128",
+      "server_parameters": {
+        "model": "Qwen/Qwen3-14B"
+      },
+      "client_parameters": {
+        "model": "Qwen/Qwen3-14B",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_qwen30B_tp1_random_128_128",
+      "server_parameters": {
+        "model": "Qwen/Qwen3-30B-A3B"
+      },
+      "client_parameters": {
+        "model": "Qwen/Qwen3-30B-A3B",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
     {
       "test_name": "serving_glm9B_tp1_random_128_128",
       "server_parameters": {
-        "model": "zai-org/glm-4-9b-hf",
-        "tensor_parallel_size": 1
+        "model": "zai-org/glm-4-9b-hf"
       },
       "client_parameters": {
         "model": "zai-org/glm-4-9b-hf",
@@ -342,8 +187,7 @@
     {
       "test_name": "serving_gemma7B_tp1_random_128_128",
       "server_parameters": {
-        "model": "google/gemma-7b",
-        "tensor_parallel_size": 1
+        "model": "google/gemma-7b"
       },
       "client_parameters": {
         "model": "google/gemma-7b",
@@ -351,6 +195,94 @@
         "random-input-len": 128,
         "random-output-len": 128
       }
+    },
+    {
+      "test_name": "serving_gemma3-4b_tp1_random_128_128",
+      "server_environment_variables": {
+	"VLLM_CPU_SGL_KERNEL": 0
+      },
+      "server_parameters": {
+        "model": "google/gemma-3-4b-it"
+      },
+      "client_parameters": {
+        "model": "google/gemma-3-4b-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_gemma3-12b_tp1_random_128_128",
+      "server_environment_variables": {
+	"VLLM_CPU_SGL_KERNEL": 0
+      },
+      "server_parameters": {
+        "model": "google/gemma-3-12b-it"
+      },
+      "client_parameters": {
+        "model": "google/gemma-3-12b-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_gemma4-4b_tp1_random_128_128",
+      "server_environment_variables": {
+	"VLLM_CPU_SGL_KERNEL": 0
+      },
+      "server_parameters": {
+        "model": "google/gemma-4-E4B-it"
+      },
+      "client_parameters": {
+        "model": "google/gemma-4-E4B-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_gemma4-2b_tp1_random_128_128",
+      "server_environment_variables": {
+	"VLLM_CPU_SGL_KERNEL": 0
+      },
+      "server_parameters": {
+        "model": "google/gemma-4-E2B-it"
+      },
+      "client_parameters": {
+        "model": "google/gemma-4-E2B-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_gemma4-26b_tp1_random_128_128",
+      "server_environment_variables": {
+	"VLLM_CPU_SGL_KERNEL": 0,
+        "VLLM_CPU_ATTN_SPLIT_KV": 0
+      },
+      "server_parameters": {
+        "model": "google/gemma-4-26B-A4B-it"
+      },
+      "client_parameters": {
+        "model": "google/gemma-4-26B-A4B-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_phi4_tp1_random_128_128",
+      "server_parameters": {
+        "model": "microsoft/Phi-4-reasoning"
+      },
+      "client_parameters": {
+        "model": "microsoft/Phi-4-reasoning",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
     }
   ]
 }

.buildkite/performance-benchmarks/tests/serving-tests-cpu.json

@@ -5,7 +5,6 @@
     ],
     "max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
     "server_environment_variables": {
-      "VLLM_RPC_TIMEOUT": 100000,
       "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
       "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
       "VLLM_CPU_SGL_KERNEL": 1,

.buildkite/performance-benchmarks/tests/serving-tests.json

@@ -1,77 +1,112 @@
-[
-    {
-        "test_name": "serving_llama8B_tp1_sharegpt",
-        "qps_list": [1, 4, 16, "inf"],
-        "server_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
-            "tensor_parallel_size": 1,
-            "disable_log_stats": "",
-            "load_format": "dummy"
-        },
-        "client_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-8B-Instruct",
-            "backend": "vllm",
-            "dataset_name": "sharegpt",
-            "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
-            "temperature": 0,
-            "num_prompts": 200
-        }
+{
+  "defaults": {
+    "qps_list": [
+      "inf"
+    ],
+    "max_concurrency_list": [12, 16, 24, 32, 64, 128, 200],
+    "server_parameters": {
+      "model": "meta-llama/Llama-3.1-8B-Instruct",
+      "tensor_parallel_size": 1,
+      "dtype": "bfloat16"
     },
-    {
-        "test_name": "serving_llama70B_tp4_sharegpt",
-        "qps_list": [1, 4, 16, "inf"],
-        "server_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-            "tensor_parallel_size": 4,
-            "disable_log_stats": "",
-            "load_format": "dummy"
-        },
-        "client_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-            "backend": "vllm",
-            "dataset_name": "sharegpt",
-            "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
-            "temperature": 0,
-            "num_prompts": 200
-        }
-    },
-    {
-        "test_name": "serving_mixtral8x7B_tp2_sharegpt",
-        "qps_list": [1, 4, 16, "inf"],
-        "server_parameters": {
-            "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
-            "tensor_parallel_size": 2,
-            "disable_log_stats": "",
-            "load_format": "dummy"
-        },
-        "client_parameters": {
-            "model": "mistralai/Mixtral-8x7B-Instruct-v0.1",
-            "backend": "vllm",
-            "dataset_name": "sharegpt",
-            "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
-            "temperature": 0,
-            "num_prompts": 200
-        }
-    },
-    {
-        "test_name": "serving_llama70B_tp4_sharegpt_specdecode",
-        "qps_list": [2],
-        "server_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-70B-Instruct", 
-            "tensor_parallel_size": 4,
-            "speculative_config": {
-                "model": "turboderp/Qwama-0.5B-Instruct",
-                "num_speculative_tokens": 4,
-                "draft_tensor_parallel_size": 1
-            }
-        },
-        "client_parameters": {
-            "model": "meta-llama/Meta-Llama-3.1-70B-Instruct",
-            "backend": "vllm",
-            "dataset_name": "sharegpt",
-            "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json",
-            "temperature": 0,
-            "num_prompts": 200 
-        }
+    "client_parameters": {
+      "model": "meta-llama/Llama-3.1-8B-Instruct",
+      "backend": "vllm",
+      "ignore-eos": "",
+      "temperature": 0,
+      "num_prompts": 200
     }
-]
+  },
+  "tests": [
+    {
+      "test_name": "serving_llama8B_tp1_sharegpt",
+      "server_parameters": {
+        "tensor_parallel_size": 1
+      },
+      "client_parameters": {
+        "dataset_name": "sharegpt",
+        "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
+      }
+    },
+    {
+        "dataset_name": "sharegpt",
+        "dataset_path": "./ShareGPT_V3_unfiltered_cleaned_split.json"
+      }
+    },
+    {
+      "test_name": "serving_llama8B_tp1_random_128_128",
+      "server_parameters": {
+        "tensor_parallel_size": 1
+      },
+      "client_parameters": {
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_llama8B_tp1_random_128_2048",
+      "server_parameters": {
+        "tensor_parallel_size": 1
+      },
+      "client_parameters": {
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 2048
+      }
+    },
+    {
+      "test_name": "serving_llama8B_tp1_random_2048_128",
+      "server_parameters": {
+        "tensor_parallel_size": 1
+      },
+      "client_parameters": {
+        "dataset_name": "random",
+        "random-input-len": 2048,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_llama8B_tp1_random_2048_2048",
+      "server_parameters": {
+        "tensor_parallel_size": 1
+      },
+      "client_parameters": {
+        "dataset_name": "random",
+        "random-input-len": 2048,
+        "random-output-len": 2048
+      }
+    },
+    {
+      "test_name": "serving_llama70B_tp4_random_128_128",
+      "server_parameters": {
+        "model": "meta-llama/Llama-3.3-70B-Instruct",
+        "async_scheduling": "",
+	"no_enable_prefix_caching": "",
+        "max_num_batched_tokens": 8192
+      },
+      "client_parameters": {
+        "model": "meta-llama/Llama-3.3-70B-Instruct",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    },
+    {
+      "test_name": "serving_gemma4-e4b_tp1_random_128_128",
+      "server_parameters": {
+        "model": "google/gemma-4-E4B-it",
+	"enable_auto_tool_choice": "",
+	"tool_call_parser": "gemma4",
+	"chat_template": "examples/tool_chat_template_gemma4.jinja",
+	"reasoning_parser": "gemma4"
+      },
+      "client_parameters": {
+        "model": "google/gemma-4-E4B-it",
+        "dataset_name": "random",
+        "random-input-len": 128,
+        "random-output-len": 128
+      }
+    }
+  ]
+}

.buildkite/performance-benchmarks/tests/throughput-tests-arm64-cpu.json

@@ -2,7 +2,6 @@
     {
         "test_name": "throughput_llama8B_tp1",
         "environment_variables": {
-            "VLLM_RPC_TIMEOUT": 100000,
             "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
             "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
             "VLLM_CPU_KVCACHE_SPACE": 40

.buildkite/performance-benchmarks/tests/throughput-tests-cpu.json

@@ -2,7 +2,6 @@
     {
         "test_name": "throughput_llama8B_tp2",
         "environment_variables": {
-            "VLLM_RPC_TIMEOUT": 100000,
 	    "VLLM_ALLOW_LONG_MAX_MODEL_LEN": 1,
 	    "VLLM_ENGINE_ITERATION_TIMEOUT_S": 120,
 	    "VLLM_CPU_SGL_KERNEL": 1,

.buildkite/release-pipeline.yaml

@@ -1,12 +1,28 @@
 # CUDA architecture lists — following PyTorch RELEASE.md
 # (https://github.com/pytorch/pytorch/blob/main/RELEASE.md)
 # SM86 included for broader Ampere coverage; SM89 for marlin fp8 support
+# These requested arches are filtered by CMake's CUDA_SUPPORTED_ARCHS before
+# per-kernel arch selection. Do not add +PTX here: top-level +PTX is stripped
+# during that filtering, so kernels that need PTX must request it locally.
 env:
-  CUDA_ARCH_X86: "7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX"
-  # aarch64 only architectures: 8.7 for Orin, 11.0 for Thor (since CUDA 13)
-  CUDA_ARCH_AARCH64: "8.0 8.7 8.9 9.0 10.0 11.0 12.0+PTX"
+  # for CUDA >=13, sm_100+ targets have family specifiers (see CMakeLists.txt)
+  # so targets like 10.3 and 12.1 are automatically supported with this list
+  CUDA_ARCH_X86: "7.5 8.0 8.6 8.9 9.0 10.0 12.0"
+  # aarch64-only targets: Orin (8.7), Thor (11.0, CUDA 13+)
+  CUDA_ARCH_AARCH64: "8.0 8.7 8.9 9.0 10.0 11.0 12.0"
+
+  # for CUDA <13, we need to specify all needed targets
+  # some targets (10.3, 12.1) are skipped to limit the wheel size (< 500MB)
+  # please use CUDA 13 wheels or compile yourself on these new devices
   CUDA_ARCH_X86_CU129: "7.5 8.0 8.6 8.9 9.0 10.0 12.0"
   CUDA_ARCH_AARCH64_CU129: "8.0 8.7 8.9 9.0 10.0 12.0"
+  
+  # pre-built mooncake wheels
+  # the manylinux_2_35 wheel has compatibility issue on Ubuntu 24.04
+  # so we use different wheels for the time being
+  MOONCAKE_WHEEL_AARCH64_2_35: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_35_aarch64.whl"
+  MOONCAKE_WHEEL_AARCH64_2_39: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_39_aarch64.whl"
+  MOONCAKE_WHEEL_X86_64: "https://vllm-wheels.s3.amazonaws.com/mooncake/mooncake_transfer_engine-0.3.10.post2-0da9dfea3-cp312-cp312-manylinux_2_35_x86_64.whl"
 
 steps:
   - input: "Provide Release version here"
@@ -24,10 +40,11 @@ steps:
         agents:
           queue: arm64_cpu_queue_release
         commands:
-          - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
+          - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_AARCH64_CU129}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinuxaarch64-builder:cuda12.9 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -41,6 +58,7 @@ steps:
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -54,6 +72,7 @@ steps:
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -63,10 +82,11 @@ steps:
         agents:
           queue: cpu_queue_release
         commands:
-          - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86_CU129}\" --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
+          - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg USE_SCCACHE=1 --build-arg GIT_REPO_CHECK=1 --build-arg CUDA_VERSION=12.9.1 --build-arg torch_cuda_arch_list=\"${CUDA_ARCH_X86_CU129}\" --build-arg BUILD_OS=manylinux --build-arg BUILD_BASE_IMAGE=pytorch/manylinux2_28-builder:cuda12.9 --tag vllm-ci:build-image --target build --progress plain -f docker/Dockerfile ."
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -80,6 +100,7 @@ steps:
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -93,6 +114,7 @@ steps:
           - "mkdir artifacts"
           - "docker run --rm -v $(pwd)/artifacts:/artifacts_host vllm-ci:build-image bash -c 'cp -r dist /artifacts_host && chmod -R a+rw /artifacts_host'"
           - "bash .buildkite/scripts/upload-nightly-wheels.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "s3://vllm-wheels/$$BUILDKITE_COMMIT/$(cd artifacts/dist && echo *.whl)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -130,6 +152,8 @@ steps:
               --build-arg CUDA_VERSION=13.0.2 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 \
               --target vllm-openai \
               --progress plain \
@@ -138,6 +162,7 @@ steps:
           # re-tag to default image tag and push, just in case arm64 build fails
           - "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m) public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
 
       - label: "Build release image - aarch64 - CUDA 13.0"
         depends_on: ~
@@ -155,11 +180,14 @@ steps:
               --build-arg CUDA_VERSION=13.0.2 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu22.04 \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)"'
 
       - label: "Build release image - x86_64 - CUDA 12.9"
         depends_on: ~
@@ -177,6 +205,8 @@ steps:
               --build-arg CUDA_VERSION=12.9.1 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_X86_CU129}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
@@ -184,6 +214,7 @@ steps:
           # re-tag to default image tag and push, just in case arm64 build fails
           - "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"'
 
       - label: "Build release image - aarch64 - CUDA 12.9"
         depends_on: ~
@@ -201,10 +232,13 @@ steps:
               --build-arg CUDA_VERSION=12.9.1 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_35}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129"'
 
       - label: "Build release image - x86_64 - CUDA 13.0 - Ubuntu 24.04"
         depends_on: ~
@@ -224,6 +258,8 @@ steps:
               --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_X86}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 \
               --target vllm-openai \
               --progress plain \
@@ -231,6 +267,7 @@ steps:
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
           - "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"'
 
       - label: "Build release image - aarch64 - CUDA 13.0 - Ubuntu 24.04"
         depends_on: ~
@@ -250,11 +287,14 @@ steps:
               --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.2-devel-ubuntu24.04 \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-ubuntu2404"'
 
       - label: "Build release image - x86_64 - CUDA 12.9 - Ubuntu 24.04"
         depends_on: ~
@@ -274,12 +314,15 @@ steps:
               --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_X86_CU129}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"
           - "docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"'
 
       - label: "Build release image - aarch64 - CUDA 12.9 - Ubuntu 24.04"
         depends_on: ~
@@ -299,16 +342,20 @@ steps:
               --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 \
               --build-arg torch_cuda_arch_list="${CUDA_ARCH_AARCH64_CU129}" \
               --build-arg INSTALL_KV_CONNECTORS=true \
+              --build-arg MOONCAKE_WHEEL_AARCH64="${MOONCAKE_WHEEL_AARCH64_2_39}" \
+              --build-arg MOONCAKE_WHEEL_X86_64="${MOONCAKE_WHEEL_X86_64}" \
               --target vllm-openai \
               --progress plain \
               -f docker/Dockerfile .
           - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu129-ubuntu2404"'
 
       - block: "Build release image for x86_64 CPU"
         key: block-cpu-release-image-build
         depends_on: ~
 
       - label: "Build release image - x86_64 - CPU"
+        key: build-cpu-release-image-x86
         depends_on:
           - block-cpu-release-image-build
           - input-release-version
@@ -319,6 +366,7 @@ steps:
           - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --build-arg VLLM_CPU_X86=true --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
           - "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:latest"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -327,7 +375,8 @@ steps:
         depends_on: ~
 
       - label: "Build release image - arm64 - CPU"
-        depends_on: 
+        key: build-cpu-release-image-arm64
+        depends_on:
           - block-arm64-cpu-release-image-build
           - input-release-version
         agents:
@@ -337,6 +386,7 @@ steps:
           - "DOCKER_BUILDKIT=1 docker build --build-arg max_jobs=16 --build-arg GIT_REPO_CHECK=1 --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version) --tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest --progress plain --target vllm-openai -f docker/Dockerfile.cpu ."
           - "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:latest"
           - "docker push public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "$$BUILDKITE_LABEL" "public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:$(buildkite-agent meta-data get release-version)"'
         env:
           DOCKER_BUILDKIT: "1"
 
@@ -354,15 +404,7 @@ steps:
           - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
           - "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64 --amend"
           - "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"
-
-      - label: "Annotate release workflow - CUDA 13.0"
-        depends_on:
-          - create-multi-arch-manifest
-        id: annotate-release-workflow
-        agents:
-          queue: small_cpu_queue_release
-        commands:
-          - "bash .buildkite/scripts/annotate-release.sh"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 13.0" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT"'
 
       - label: "Create multi-arch manifest - CUDA 12.9"
         depends_on:
@@ -375,6 +417,7 @@ steps:
           - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
           - "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu129 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu129 --amend"
           - "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 12.9" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129"'
 
       - label: "Create multi-arch manifest - CUDA 13.0 - Ubuntu 24.04"
         depends_on:
@@ -387,6 +430,7 @@ steps:
           - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
           - "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-ubuntu2404 --amend"
           - "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 13.0 Ubuntu 24.04" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-ubuntu2404"'
 
       - label: "Create multi-arch manifest - CUDA 12.9 - Ubuntu 24.04"
         depends_on:
@@ -399,6 +443,7 @@ steps:
           - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
           - "docker manifest create public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-x86_64-cu129-ubuntu2404 public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-aarch64-cu129-ubuntu2404 --amend"
           - "docker manifest push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"
+          - 'bash .buildkite/scripts/annotate-build-artifact.sh "Manifest: CUDA 12.9 Ubuntu 24.04" "public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-cu129-ubuntu2404"'
 
       - label: "Publish nightly multi-arch image to DockerHub"
         depends_on:
@@ -436,24 +481,6 @@ steps:
           DOCKER_BUILDKIT: "1"
           DOCKERHUB_USERNAME: "vllmbot"
 
-  - group: "Publish wheels"
-    key: "publish-wheels"
-    steps:
-      - block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
-        key: block-upload-release-wheels
-        depends_on:
-          - input-release-version
-          - build-wheels
-
-      - label: "Upload release wheels to PyPI"
-        depends_on:
-          - block-upload-release-wheels
-        id: upload-release-wheels
-        agents:
-          queue: small_cpu_queue_release
-        commands:
-          - "bash .buildkite/scripts/upload-release-wheels-pypi.sh"
-
   # =============================================================================
   # ROCm Release Pipeline (x86_64 only)
   # =============================================================================
@@ -567,7 +594,7 @@ steps:
           echo ""
           echo " Build complete - Image and wheels cached"
         fi
-        
+
     artifact_paths:
       - "artifacts/rocm-base-wheels/*.whl"
     env:
@@ -723,7 +750,7 @@ steps:
       - "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
     env:
       S3_BUCKET: "vllm-wheels"
-      VARIANT: "rocm721"
+      VARIANT: "rocm723"
 
   # ROCm Job 6: Build ROCm Release Docker Image
   - label: ":docker: Build release image - x86_64 - ROCm"
@@ -783,7 +810,7 @@ steps:
         
         # Push to ECR
         docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm
-        
+
         echo ""
         echo " Successfully built and pushed ROCm release image"
         echo "   Image: public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm"
@@ -810,3 +837,59 @@ steps:
     env:
       DOCKER_BUILDKIT: "1"
       DOCKERHUB_USERNAME: "vllmbot"
+
+  # =============================================================================
+  # Publish to DockerHub and PyPI (at the end so all builds complete first)
+  # =============================================================================
+
+  - block: "Publish release images to DockerHub"
+    key: block-publish-release-images
+    depends_on:
+      - create-multi-arch-manifest
+      - create-multi-arch-manifest-cuda-12-9
+      - create-multi-arch-manifest-ubuntu2404
+      - create-multi-arch-manifest-cuda-12-9-ubuntu2404
+      - build-rocm-release-image
+      - input-release-version
+      # Wait for CPU builds if their block steps were unblocked, so publish
+      # doesn't race the in-progress CPU build. allow_failure lets publish
+      # proceed when the operator legitimately leaves the CPU block steps
+      # unblocked or the CPU build fails.
+      - step: build-cpu-release-image-x86
+        allow_failure: true
+      - step: build-cpu-release-image-arm64
+        allow_failure: true
+
+  - label: "Publish release images to DockerHub"
+    depends_on:
+      - block-publish-release-images
+    key: publish-release-images-dockerhub
+    agents:
+      queue: small_cpu_queue_release
+    commands:
+      - "bash .buildkite/scripts/publish-release-images.sh"
+    plugins:
+      - docker-login#v3.0.0:
+          username: vllmbot
+          password-env: DOCKERHUB_TOKEN
+    env:
+      DOCKER_BUILDKIT: "1"
+      DOCKERHUB_USERNAME: "vllmbot"
+
+  - group: "Publish wheels"
+    key: "publish-wheels"
+    steps:
+      - block: "Confirm update release wheels to PyPI (experimental, use with caution)?"
+        key: block-upload-release-wheels
+        depends_on:
+          - input-release-version
+          - build-wheels
+
+      - label: "Upload release wheels to PyPI"
+        depends_on:
+          - block-upload-release-wheels
+        id: upload-release-wheels
+        agents:
+          queue: small_cpu_queue_release
+        commands:
+          - "bash .buildkite/scripts/upload-release-wheels-pypi.sh"

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

@@ -0,0 +1,9 @@
+#!/bin/bash
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+#
+# Append a build artifact line to the Buildkite annotation.
+# Usage: annotate-build-artifact.sh <label> <value>
+set -e
+echo "- **${1}**: \`${2}\`" | \
+  buildkite-agent annotate --append --style 'info' --context 'release-artifacts'

.buildkite/scripts/annotate-release.sh

@@ -1,119 +0,0 @@
-#!/bin/bash
-
-set -ex
-
-# Get release version, default to 1.0.0.dev for nightly/per-commit builds
-RELEASE_VERSION=$(buildkite-agent meta-data get release-version 2>/dev/null | sed 's/^v//')
-if [ -z "${RELEASE_VERSION}" ]; then
-  RELEASE_VERSION="1.0.0.dev"
-fi
-
-ROCM_BASE_CACHE_KEY=$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
-
-buildkite-agent annotate --style 'info' --context 'release-workflow' << EOF
-To download the wheel (by commit):
-\`\`\`
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}-cp38-abi3-manylinux_2_35_x86_64.whl .
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}-cp38-abi3-manylinux_2_35_aarch64.whl .
-
-(Optional) For CUDA 12.9:
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu129-cp38-abi3-manylinux_2_31_x86_64.whl .
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cu129-cp38-abi3-manylinux_2_31_aarch64.whl .
-
-(Optional) For CPU:
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cpu-cp38-abi3-manylinux_2_35_x86_64.whl .
-aws s3 cp s3://vllm-wheels/${BUILDKITE_COMMIT}/vllm-${RELEASE_VERSION}+cpu-cp38-abi3-manylinux_2_35_aarch64.whl .
-\`\`\`
-
-
-To download and upload the image:
-
-\`\`\`
-# Download images:
-
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64-cu129
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64-cu129
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base
-docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-rocm
-docker pull public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION}
-docker pull public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION}
-
-# Tag and push images:
-
-## CUDA
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64 vllm/vllm-openai:x86_64
-docker tag vllm/vllm-openai:x86_64 vllm/vllm-openai:latest-x86_64
-docker tag vllm/vllm-openai:x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
-docker push vllm/vllm-openai:latest-x86_64
-docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-x86_64-cu129 vllm/vllm-openai:x86_64-cu129
-docker tag vllm/vllm-openai:x86_64-cu129 vllm/vllm-openai:latest-x86_64-cu129
-docker tag vllm/vllm-openai:x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
-docker push vllm/vllm-openai:latest-x86_64-cu129
-docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64 vllm/vllm-openai:aarch64
-docker tag vllm/vllm-openai:aarch64 vllm/vllm-openai:latest-aarch64
-docker tag vllm/vllm-openai:aarch64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
-docker push vllm/vllm-openai:latest-aarch64
-docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-aarch64-cu129 vllm/vllm-openai:aarch64-cu129
-docker tag vllm/vllm-openai:aarch64-cu129 vllm/vllm-openai:latest-aarch64-cu129
-docker tag vllm/vllm-openai:aarch64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
-docker push vllm/vllm-openai:latest-aarch64-cu129
-docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
-
-## ROCm
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${BUILDKITE_COMMIT}-rocm vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}
-docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT} vllm/vllm-openai-rocm:latest
-docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT} vllm/vllm-openai-rocm:v${RELEASE_VERSION}
-docker push vllm/vllm-openai-rocm:latest
-docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base
-docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base vllm/vllm-openai-rocm:latest-base
-docker tag vllm/vllm-openai-rocm:${BUILDKITE_COMMIT}-base vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
-docker push vllm/vllm-openai-rocm:latest-base
-docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
-
-## CPU
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION} vllm/vllm-openai-cpu:x86_64
-docker tag vllm/vllm-openai-cpu:x86_64 vllm/vllm-openai-cpu:latest-x86_64
-docker tag vllm/vllm-openai-cpu:x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
-docker push vllm/vllm-openai-cpu:latest-x86_64
-docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
-
-docker tag public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION} vllm/vllm-openai-cpu:arm64
-docker tag vllm/vllm-openai-cpu:arm64 vllm/vllm-openai-cpu:latest-arm64
-docker tag vllm/vllm-openai-cpu:arm64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
-docker push vllm/vllm-openai-cpu:latest-arm64
-docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
-
-# Create multi-arch manifest:
-
-docker manifest rm vllm/vllm-openai:latest
-docker manifest create vllm/vllm-openai:latest vllm/vllm-openai:latest-x86_64 vllm/vllm-openai:latest-aarch64
-docker manifest create vllm/vllm-openai:v${RELEASE_VERSION} vllm/vllm-openai:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
-docker manifest push vllm/vllm-openai:latest
-docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}
-
-docker manifest rm vllm/vllm-openai:latest-cu129
-docker manifest create vllm/vllm-openai:latest-cu129 vllm/vllm-openai:latest-x86_64-cu129 vllm/vllm-openai:latest-aarch64-cu129
-docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
-docker manifest push vllm/vllm-openai:latest-cu129
-docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu129
-
-docker manifest rm vllm/vllm-openai-cpu:latest || true
-docker manifest create vllm/vllm-openai-cpu:latest vllm/vllm-openai-cpu:latest-x86_64 vllm/vllm-openai-cpu:latest-arm64
-docker manifest create vllm/vllm-openai-cpu:v${RELEASE_VERSION} vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
-docker manifest push vllm/vllm-openai-cpu:latest
-docker manifest push vllm/vllm-openai-cpu:v${RELEASE_VERSION}
-\`\`\`
-EOF

.buildkite/scripts/ci-clean-log.sh

@@ -13,5 +13,8 @@ INPUT_FILE="$1"
 # Strip timestamps
 sed -i 's/^\[[0-9]\{4\}-[0-9]\{2\}-[0-9]\{2\}T[0-9]\{2\}:[0-9]\{2\}:[0-9]\{2\}Z\] //' "$INPUT_FILE"
 
+# Strip Buildkite inline timestamp markers (ESC _bk;t=<ms> BEL)
+sed -i 's/\x1B_bk;t=[0-9]*\x07//g' "$INPUT_FILE"
+
 # Strip colorization
 sed -i -r 's/\x1B\[[0-9;]*[mK]//g' "$INPUT_FILE"

.buildkite/scripts/ci-fetch-log.sh

@@ -1,55 +1,178 @@
 #!/bin/bash
-# Usage: ./ci-fetch-log.sh <buildkite_job_url> [output_file]
-#        ./ci-fetch-log.sh <build_number> <job_uuid> [output_file]
+# Fetch vLLM Buildkite CI logs (public; no login required).
 #
-# Downloads the raw log for a Buildkite job from the public, unauthenticated
-# /organizations/<org>/pipelines/<pipeline>/builds/<n>/jobs/<uuid>/download
-# endpoint, then strips ANSI/timestamps via ci-clean-log.sh.
+# Usage:
+#   ci-fetch-log.sh [--soft|--all] --pr [<PR>]  failed jobs in the PR's latest
+#                                               build (current branch if omitted)
+#   ci-fetch-log.sh [--soft|--all] <build_url>  failed jobs in that build
+#   ci-fetch-log.sh <job_url> [output]          one job; both #<job_uuid> and
+#                                               ?sid=<id> URL forms work
+#   ci-fetch-log.sh <build> <job_uuid> [output]
 #
-# Find <build_number> and <job_uuid> via:
-#   gh pr checks <PR> --repo vllm-project/vllm
-# Each failing row's URL is .../builds/<build_number>#<job_uuid>.
+# --soft also fetches soft-failed jobs; --all fetches every finished job.
+# Saves each log as ci-<build>-<job-name>.log (ANSI/timestamps stripped) and
+# prints "<file>\t<job name>" per job. [output] is single-job only; "-"
+# streams to stdout. Existing files are kept; CI_FETCH_LOG_FORCE=1 refetches.
 
 set -euo pipefail
 
 ORG="vllm"
 PIPELINE="ci"
+UA="vllm-ci-fetch-log"
+UUID_RE='[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}'
 
 usage() {
-    echo "Usage: $0 <buildkite_job_url> [output_file]"
-    echo "       $0 <build_number> <job_uuid> [output_file]"
+    sed -n '2,15p' "$0" | sed 's/^# \{0,1\}//'
     exit 1
 }
 
-if [ $# -lt 1 ]; then usage; fi
+die() {
+    echo "$1" >&2
+    exit 1
+}
 
-if [[ "$1" == https://* ]]; then
+BUILD="" JOB="" SID="" OUT=""
+SCOPE="failed"
+
+while :; do
+    case "${1:-}" in
+    --soft) SCOPE="soft" ;;
+    --all) SCOPE="all" ;;
+    *) break ;;
+    esac
+    shift
+done
+
+case "${1:-}" in
+--pr)
+    PR="${2:-}"
+    # gh pr checks exits non-zero when checks are failing; that is the
+    # expected case here.
+    URL=$(gh pr checks ${PR:+"$PR"} --repo vllm-project/vllm 2>/dev/null |
+        grep -oE "https://buildkite.com/${ORG}/${PIPELINE}/builds/[0-9]+" |
+        sort -t/ -k7 -n | tail -1 || true)
+    [ -n "$URL" ] || die "No Buildkite build found via: gh pr checks ${PR:-<current branch>}"
+    BUILD="${URL##*/}"
+    ;;
+https://*)
     BUILD=$(echo "$1" | sed -nE 's#.*/builds/([0-9]+).*#\1#p')
-    JOB=$(echo "$1" | grep -oE '[0-9a-f]{8}-[0-9a-f-]+' | head -n 1)
-    OUT="${2:-ci-${BUILD}-${JOB:0:8}.log}"
-else
-    if [ $# -lt 2 ]; then usage; fi
+    JOB=$(echo "$1" | grep -oE "#${UUID_RE}" | head -n 1 | cut -c2- || true)
+    SID=$(echo "$1" | grep -oE "[?&]sid=${UUID_RE}" | head -n 1 | sed 's/.*sid=//' || true)
+    OUT="${2:-}"
+    [ -n "$BUILD" ] || die "Could not parse build number from: $1"
+    ;;
+[0-9]*)
+    [ $# -ge 2 ] || usage
     BUILD="$1"
     JOB="$2"
-    OUT="${3:-ci-${BUILD}-${JOB:0:8}.log}"
-fi
-
-if [ -z "$BUILD" ] || [ -z "$JOB" ]; then
-    echo "Could not parse build number or job UUID from: $1" >&2
+    OUT="${3:-}"
+    ;;
+*)
     usage
-fi
+    ;;
+esac
 
 COOKIES=$(mktemp)
-trap 'rm -f "$COOKIES"' EXIT
+JOBS_TSV=$(mktemp)
+trap 'rm -f "$COOKIES" "$JOBS_TSV"' EXIT
 
-# Buildkite issues a session cookie on first hit; subsequent /download needs it.
-curl -fsSL -c "$COOKIES" -A "vllm-ci-fetch-log" \
+# Buildkite issues a session cookie on first hit; later requests need it.
+curl -fsSL -c "$COOKIES" -A "$UA" \
     "https://buildkite.com/${ORG}/${PIPELINE}/builds/${BUILD}" -o /dev/null
 
-curl -fsSL -b "$COOKIES" -A "vllm-ci-fetch-log" \
-    "https://buildkite.com/organizations/${ORG}/pipelines/${PIPELINE}/builds/${BUILD}/jobs/${JOB}/download" \
-    -o "$OUT"
+# The build's job list (id, step uuid, state, name) is served as JSON from
+# the user-facing /data/jobs endpoint. Flatten it to TSV for easy filtering:
+#   job_id  step_uuid  failed  soft_failed  finished  slug  name
+curl -fsSL -b "$COOKIES" -A "$UA" \
+    "https://buildkite.com/${ORG}/${PIPELINE}/builds/${BUILD}/data/jobs" |
+    python3 -c '
+import json, re, sys
 
-bash "$(dirname "$0")/ci-clean-log.sh" "$OUT"
+data = json.load(sys.stdin)
+if data.get("has_next_page"):
+    print("warning: job list is paginated; some jobs not shown", file=sys.stderr)
+for r in data["records"]:
+    if r.get("type") != "script":
+        continue
+    name = (r.get("name") or "").replace("\t", " ").replace("\n", " ")
+    slug = re.sub(r"[^a-z0-9]+", "-", name.lower()).strip("-")[:60]
+    print("\t".join([
+        r["id"],
+        r.get("step_uuid") or "",
+        str(r.get("passed") is False),
+        str(bool(r.get("soft_failed"))),
+        str(bool(r.get("finished_at"))),
+        slug,
+        name,
+    ]))
+' >"$JOBS_TSV" || die "Could not list jobs for build ${BUILD}"
 
-echo "$OUT"
+if [ -n "$SID" ] && [ -z "$JOB" ]; then
+    # The ?sid= in builds/<N>/list URLs is the *step* uuid, not the job uuid.
+    JOB=$(awk -F'\t' -v s="$SID" '$1 == s || $2 == s {print $1; exit}' "$JOBS_TSV")
+    [ -n "$JOB" ] || die "No job matching sid=${SID} in build ${BUILD}"
+fi
+
+fetch_job() { # <job_uuid> <output_file>
+    curl -fsSL -b "$COOKIES" -A "$UA" \
+        "https://buildkite.com/organizations/${ORG}/pipelines/${PIPELINE}/builds/${BUILD}/jobs/$1/download" \
+        -o "$2"
+    bash "$(dirname "$0")/ci-clean-log.sh" "$2"
+}
+
+if [ -n "$JOB" ]; then
+    # Single-job mode.
+    NAME=$(awk -F'\t' -v j="$JOB" '$1 == j {print $7; exit}' "$JOBS_TSV")
+    SLUG=$(awk -F'\t' -v j="$JOB" '$1 == j {print $6; exit}' "$JOBS_TSV")
+    [ -n "$OUT" ] || OUT="ci-${BUILD}-${SLUG:-${JOB:0:13}}.log"
+    if [ "$OUT" = "-" ]; then
+        TMP=$(mktemp)
+        fetch_job "$JOB" "$TMP"
+        cat "$TMP"
+        rm -f "$TMP"
+        exit 0
+    fi
+    if [ -e "$OUT" ] && [ -z "${CI_FETCH_LOG_FORCE:-}" ]; then
+        die "Refusing to overwrite existing ${OUT} (set CI_FETCH_LOG_FORCE=1 or pass an output path)."
+    fi
+    fetch_job "$JOB" "$OUT"
+    printf '%s\t%s\n' "$OUT" "${NAME:-$JOB}"
+    exit 0
+fi
+
+# Build-wide mode: fetch finished jobs matching $SCOPE.
+[ -z "$OUT" ] || die "[output_file] is only valid when fetching a single job."
+
+case "$SCOPE" in
+failed) FILTER='$3 == "True" && $4 == "False" && $5 == "True"' ;;
+soft) FILTER='$3 == "True" && $5 == "True"' ;;
+all) FILTER='$5 == "True"' ;;
+esac
+
+if [ "$SCOPE" = "failed" ]; then
+    SOFT=$(awk -F'\t' '$3 == "True" && $4 == "True"' "$JOBS_TSV" | wc -l)
+    [ "$SOFT" -eq 0 ] || echo "Skipping ${SOFT} soft-failed job(s); use --soft to include them." >&2
+fi
+
+FOUND=0
+EMITTED=" "
+while IFS=$'\t' read -r job_id _ _ _ _ slug name; do
+    FOUND=$((FOUND + 1))
+    out="ci-${BUILD}-${slug:-${job_id:0:13}}.log"
+    # Retries share a name with the original job; disambiguate by uuid.
+    case "$EMITTED" in
+    *" $out "*) out="ci-${BUILD}-${slug:-job}-${job_id:0:13}.log" ;;
+    esac
+    EMITTED="${EMITTED}${out} "
+    if [ -e "$out" ] && [ -z "${CI_FETCH_LOG_FORCE:-}" ]; then
+        echo "Keeping existing ${out} (set CI_FETCH_LOG_FORCE=1 to refetch)." >&2
+    elif ! fetch_job "$job_id" "$out"; then
+        echo "Failed to download log for job ${job_id} (${name})." >&2
+        continue
+    fi
+    printf '%s\t%s\n' "$out" "$name"
+done < <(awk -F'\t' "$FILTER" "$JOBS_TSV")
+
+if [ "$FOUND" -eq 0 ]; then
+    echo "No matching jobs in build ${BUILD} (scope: ${SCOPE})." >&2
+fi

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

@@ -28,32 +28,18 @@
 ###############################################################################
 set -o pipefail
 
-# Export Python path
-export PYTHONPATH=".."
+# 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.
+export PYTHONPATH="${PYTHONPATH:-..}"
 
 ###############################################################################
 # Helper Functions
 ###############################################################################
 
-cleanup_docker() {
-  # Get Docker's root directory
-  docker_root=$(docker info -f '{{.DockerRootDir}}')
-  if [ -z "$docker_root" ]; then
-    echo "Failed to determine Docker root directory."
-    exit 1
-  fi
-  echo "Docker root directory: $docker_root"
-
-  disk_usage=$(df "$docker_root" | tail -1 | awk '{print $5}' | sed 's/%//')
-  threshold=70
-  if [ "$disk_usage" -gt "$threshold" ]; then
-    echo "Disk usage is above $threshold%. Cleaning up Docker images and volumes..."
-    docker image prune -f
-    docker volume prune -f && docker system prune --force --filter "until=72h" --all
-    echo "Docker images and volumes cleanup completed."
-  else
-    echo "Disk usage is below $threshold%. No cleanup needed."
-  fi
+report_docker_usage() {
+  echo "--- Docker usage"
+  docker system df || true
 }
 
 cleanup_network() {
@@ -68,6 +54,108 @@ cleanup_network() {
   fi
 }
 
+prepare_artifact_image() {
+  if [[ "${VLLM_CI_USE_ARTIFACTS:-0}" != "1" ]]; then
+    return 1
+  fi
+  if ! command -v buildkite-agent >/dev/null 2>&1; then
+    echo "buildkite-agent not found; cannot download ROCm wheel artifact"
+    return 1
+  fi
+
+  local artifact_glob="${VLLM_CI_ARTIFACT_GLOB:-artifacts/vllm-rocm-install/vllm-rocm-install.tar.gz}"
+  local archive=""
+  local metadata_file=""
+  local base_image="${VLLM_CI_BASE_IMAGE:-rocm/vllm-dev:ci_base}"
+  local artifact_image=""
+  local artifact_key=""
+  local base_digest=""
+  local wheel_dir=""
+  local context_dir=""
+  local workspace_dir=""
+
+  artifact_work_dir=$(mktemp -d -t vllm-rocm-artifact.XXXXXX)
+  wheel_dir="${artifact_work_dir}/wheels"
+  context_dir="${artifact_work_dir}/context"
+  workspace_dir="${context_dir}/workspace"
+  mkdir -p "${wheel_dir}" "${context_dir}/wheels" "${workspace_dir}"
+
+  echo "--- Downloading ROCm wheel artifact"
+  if ! buildkite-agent artifact download "${artifact_glob}" "${artifact_work_dir}"; then
+    echo "Failed to download ${artifact_glob}"
+    return 1
+  fi
+  buildkite-agent artifact download \
+    "artifacts/vllm-rocm-install/ci-base-image.txt" \
+    "${artifact_work_dir}" >/dev/null 2>&1 || true
+
+  archive=$(find "${artifact_work_dir}" -name "vllm-rocm-install.tar.gz" -type f | head -1)
+  if [[ -z "${archive}" || ! -f "${archive}" ]]; then
+    echo "ROCm wheel artifact archive was not found"
+    return 1
+  fi
+
+  metadata_file=$(find "${artifact_work_dir}" -name "ci-base-image.txt" -type f | head -1)
+  if [[ -n "${metadata_file}" && -s "${metadata_file}" ]]; then
+    base_image=$(tr -d '[:space:]' < "${metadata_file}")
+  fi
+
+  echo "--- Preparing local ROCm test image"
+  echo "Base image: ${base_image}"
+  docker pull "${base_image}" || return 1
+  base_digest=$(
+    docker image inspect \
+      --format='{{if .RepoDigests}}{{index .RepoDigests 0}}{{else}}{{.Id}}{{end}}' \
+      "${base_image}" 2>/dev/null || printf '%s' "${base_image}"
+  )
+
+  artifact_key=$(
+    {
+      printf 'base-image:%s\n' "${base_digest}"
+      sha256sum "${archive}"
+    } | sha256sum | cut -c1-24
+  )
+  artifact_image="rocm/vllm-ci-artifact:${artifact_key}"
+
+  if docker image inspect "${artifact_image}" >/dev/null 2>&1; then
+    echo "Using existing local ROCm artifact image: ${artifact_image}"
+    image_name="${artifact_image}"
+    return 0
+  fi
+
+  tar -xzf "${archive}" -C "${wheel_dir}" || return 1
+  if ! ls "${wheel_dir}"/*.whl >/dev/null 2>&1; then
+    echo "ROCm wheel artifact did not contain a wheel"
+    return 1
+  fi
+  if [[ ! -d "${wheel_dir}/tests" ]]; then
+    echo "ROCm wheel artifact did not contain the test workspace"
+    return 1
+  fi
+
+  cp "${wheel_dir}"/*.whl "${context_dir}/wheels/" || return 1
+  tar -C "${wheel_dir}" --exclude='*.whl' -cf - . \
+    | tar -C "${workspace_dir}" -xf - || return 1
+  cat > "${context_dir}/Dockerfile" <<'EOF'
+ARG BASE_IMAGE
+FROM ${BASE_IMAGE}
+COPY wheels/ /tmp/vllm-wheels/
+COPY workspace/ /vllm-workspace/
+RUN python3 -m pip install --no-deps --force-reinstall /tmp/vllm-wheels/*.whl \
+    && rm -rf /tmp/vllm-wheels
+WORKDIR /vllm-workspace
+EOF
+
+  echo "--- Building local ROCm test image"
+  docker build \
+    --pull=false \
+    --build-arg "BASE_IMAGE=${base_image}" \
+    -t "${artifact_image}" \
+    "${context_dir}" || return 1
+  image_name="${artifact_image}"
+  return 0
+}
+
 is_multi_node() {
   local cmds="$1"
   # Primary signal: NUM_NODES environment variable set by the pipeline
@@ -114,8 +202,7 @@ handle_pytest_exit() {
 # unquoted since they have no spaces and work fine.
 #
 # Already-quoted expressions (containing literal single quotes) are passed
-# through untouched to avoid double-quoting values injected by
-# apply_rocm_test_overrides.
+# through untouched to avoid double-quoting well-formed shell fragments.
 #
 # NOTE: This ONLY fixes -m/-k flags. It cannot recover arbitrary inner
 # double-quotes stripped by the calling shell (see header comment).
@@ -247,102 +334,6 @@ re_quote_pytest_markers() {
   echo "${output% }"
 }
 
-###############################################################################
-# ROCm-specific pytest command rewrites
-#
-# These apply ignore flags and environment overrides for tests that are not
-# yet supported or behave differently on ROCm hardware. Kept as a single
-# function so new exclusions are easy to add in one place.
-###############################################################################
-
-apply_rocm_test_overrides() {
-  local cmds="$1"
-
-  # --- Model registry filter ---
-  if [[ $cmds == *"pytest -v -s models/test_registry.py"* ]]; then
-    cmds=${cmds//"pytest -v -s models/test_registry.py"/"pytest -v -s models/test_registry.py -k 'not BambaForCausalLM and not GritLM and not Mamba2ForCausalLM and not Zamba2ForCausalLM'"}
-  fi
-
-  # --- LoRA: disable custom paged attention ---
-  if [[ $cmds == *"pytest -v -s lora"* ]]; then
-    cmds=${cmds//"pytest -v -s lora"/"pytest -v -s lora"}
-  fi
-
-  # --- Kernel ignores ---
-  if [[ $cmds == *" kernels/core"* ]]; then
-    cmds="${cmds} \
-    --ignore=kernels/core/test_fused_quant_layernorm.py \
-    --ignore=kernels/core/test_permute_cols.py"
-  fi
-
-  if [[ $cmds == *" kernels/attention"* ]]; then
-    cmds="${cmds} \
-    --ignore=kernels/attention/test_attention_selector.py \
-    --ignore=kernels/attention/test_encoder_decoder_attn.py \
-    --ignore=kernels/attention/test_flash_attn.py \
-    --ignore=kernels/attention/test_flashinfer.py \
-    --ignore=kernels/attention/test_prefix_prefill.py \
-    --ignore=kernels/attention/test_cascade_flash_attn.py \
-    --ignore=kernels/attention/test_mha_attn.py \
-    --ignore=kernels/attention/test_lightning_attn.py \
-    --ignore=kernels/attention/test_attention.py"
-  fi
-
-  if [[ $cmds == *" kernels/quantization"* ]]; then
-    cmds="${cmds} \
-    --ignore=kernels/quantization/test_int8_quant.py \
-    --ignore=kernels/quantization/test_machete_mm.py \
-    --ignore=kernels/quantization/test_block_fp8.py \
-    --ignore=kernels/quantization/test_block_int8.py \
-    --ignore=kernels/quantization/test_marlin_gemm.py \
-    --ignore=kernels/quantization/test_cutlass_scaled_mm.py \
-    --ignore=kernels/quantization/test_int8_kernel.py"
-  fi
-
-  if [[ $cmds == *" kernels/mamba"* ]]; then
-    cmds="${cmds} \
-    --ignore=kernels/mamba/test_mamba_mixer2.py \
-    --ignore=kernels/mamba/test_causal_conv1d.py \
-    --ignore=kernels/mamba/test_mamba_ssm_ssd.py"
-  fi
-
-  if [[ $cmds == *" kernels/moe"* ]]; then
-    cmds="${cmds} \
-    --ignore=kernels/moe/test_moe.py \
-    --ignore=kernels/moe/test_cutlass_moe.py"
-  fi
-
-  # --- Entrypoint ignores ---
-  if [[ $cmds == *" entrypoints/openai "* ]]; then
-    cmds=${cmds//" entrypoints/openai "/" entrypoints/openai \
-    --ignore=entrypoints/openai/chat_completion/test_audio.py \
-    --ignore=entrypoints/openai/completion/test_shutdown.py \
-    --ignore=entrypoints/openai/test_completion.py \
-    --ignore=entrypoints/openai/models/test_models.py \
-    --ignore=entrypoints/openai/test_return_tokens_as_ids.py \
-    --ignore=entrypoints/openai/chat_completion/test_root_path.py \
-    --ignore=entrypoints/openai/completion/test_prompt_validation.py "}
-  fi
-
-  if [[ $cmds == *" entrypoints/serve"* ]]; then
-    cmds="${cmds} \
-    --ignore=entrypoints/serve/lora/test_lora_adapters.py"
-  fi
-
-  if [[ $cmds == *" entrypoints/llm "* ]]; then
-    cmds=${cmds//" entrypoints/llm "/" entrypoints/llm \
-    --ignore=entrypoints/llm/test_chat.py \
-    --ignore=entrypoints/llm/test_accuracy.py \
-    --ignore=entrypoints/llm/test_init.py \
-    --ignore=entrypoints/llm/test_prompt_validation.py "}
-  fi
-
-  # Clean up escaped newlines from --ignore appends
-  cmds=$(echo "$cmds" | sed 's/ \\ / /g')
-
-  echo "$cmds"
-}
-
 ###############################################################################
 # Main
 ###############################################################################
@@ -351,20 +342,36 @@ apply_rocm_test_overrides() {
 echo "--- ROCm info"
 rocminfo
 
-# --- Docker housekeeping ---
-cleanup_docker
+# --- Docker status ---
+report_docker_usage
 
 # --- Pull test image ---
 echo "--- Pulling container"
-image_name="rocm/vllm-ci:${BUILDKITE_COMMIT}"
+image_name="${VLLM_CI_FALLBACK_IMAGE:-rocm/vllm-ci:${BUILDKITE_COMMIT:-local}}"
+artifact_work_dir=""
 container_name="rocm_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
-docker pull "${image_name}"
 
 remove_docker_container() {
-  docker rm -f "${container_name}" || docker image rm -f "${image_name}" || true
+  if docker container inspect "${container_name}" >/dev/null 2>&1; then
+    docker rm -f "${container_name}" || true
+  fi
+  if [[ "${VLLM_CI_REMOVE_TEST_IMAGE:-0}" == "1" ]]; then
+    docker image rm -f "${image_name}" || true
+  else
+    # Keep images by default so later jobs on the same AMD node can reuse layers.
+    echo "Keeping ROCm test image locally: ${image_name}"
+  fi
+  if [[ -n "${artifact_work_dir}" ]]; then
+    rm -rf "${artifact_work_dir}"
+  fi
 }
 trap remove_docker_container EXIT
 
+if ! prepare_artifact_image; then
+  echo "Using full ROCm CI image: ${image_name}"
+  docker pull "${image_name}" || exit 1
+fi
+
 # --- Prepare commands ---
 echo "--- Running container"
 
@@ -372,15 +379,25 @@ HF_CACHE="$(realpath ~)/huggingface"
 mkdir -p "${HF_CACHE}"
 HF_MOUNT="/root/.cache/huggingface"
 
+# Hugging Face Hub defaults to 10s request/download timeouts, while the ROCm
+# CI image currently raises downloads to 60s. AMD model-test jobs routinely
+# start from a cold or partially-populated shared cache, and the 60s read cap
+# has still timed out before pytest reached the vLLM behavior under test.
+# Keep the CI default explicit and overridable from the Buildkite environment.
+: "${HF_HUB_DOWNLOAD_TIMEOUT:=300}"
+: "${HF_HUB_ETAG_TIMEOUT:=60}"
+
 # ---- Command source selection ----
 # Prefer VLLM_TEST_COMMANDS (preserves all inner quoting intact).
 # Fall back to $* for backward compatibility, but warn that inner
 # double-quotes will have been stripped by the calling shell.
 if [[ -n "${VLLM_TEST_COMMANDS:-}" ]]; then
   commands="${VLLM_TEST_COMMANDS}"
+  commands_source="env"
   echo "Commands sourced from VLLM_TEST_COMMANDS (quoting preserved)"
 else
   commands="$*"
+  commands_source="argv"
   if [[ -z "$commands" ]]; then
     echo "Error: No test commands provided." >&2
     echo "Usage:" >&2
@@ -397,14 +414,26 @@ fi
 
 echo "Raw commands: $commands"
 
-# Fix quoting before ROCm overrides (so overrides see correct structure)
-commands=$(re_quote_pytest_markers "$commands")
-echo "After re-quoting: $commands"
+# Only try to repair stripped pytest -m/-k quoting in legacy argv mode.
+# VLLM_TEST_COMMANDS preserves inner quoting already, and re-quoting that path
+# can corrupt embedded echo strings or otherwise well-formed shell fragments.
+if [[ "$commands_source" == "argv" ]]; then
+  commands=$(re_quote_pytest_markers "$commands")
+  echo "After re-quoting: $commands"
+else
+  echo "Skipping re-quoting for VLLM_TEST_COMMANDS input"
+fi
 
-commands=$(apply_rocm_test_overrides "$commands")
 echo "Final commands: $commands"
 
-MYPYTHONPATH=".."
+MYPYTHONPATH="/vllm-workspace"
+
+container_job_id="${BUILDKITE_JOB_ID:-${BUILDKITE_PARALLEL_JOB:-0}}"
+container_job_id="${container_job_id//[^A-Za-z0-9_.-]/_}"
+container_job_id_short="${container_job_id:0:8}"
+CONTAINER_TMPDIR="/tmp/vllm-${container_job_id_short}"
+CONTAINER_CACHE_ROOT="/tmp/vllm-buildkite-${container_job_id}/cache"
+CONTAINER_PREFLIGHT="mkdir -p \"\$TMPDIR\" \"\$TORCHINDUCTOR_CACHE_DIR\" \"\$TRITON_CACHE_DIR\" \"\$VLLM_CACHE_ROOT\" \"\$XDG_CACHE_HOME\" && python -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\""
 
 # Verify GPU access
 render_gid=$(getent group render | cut -d: -f3)
@@ -481,6 +510,8 @@ else
     --group-add "$render_gid" \
     --rm \
     -e HF_TOKEN \
+    -e "HF_HUB_DOWNLOAD_TIMEOUT=${HF_HUB_DOWNLOAD_TIMEOUT}" \
+    -e "HF_HUB_ETAG_TIMEOUT=${HF_HUB_ETAG_TIMEOUT}" \
     -e AWS_ACCESS_KEY_ID \
     -e AWS_SECRET_ACCESS_KEY \
     -e BUILDKITE_PARALLEL_JOB \
@@ -488,10 +519,15 @@ else
     -v "${HF_CACHE}:${HF_MOUNT}" \
     -e "HF_HOME=${HF_MOUNT}" \
     -e "PYTHONPATH=${MYPYTHONPATH}" \
+    -e "TMPDIR=${CONTAINER_TMPDIR}/tmp" \
+    -e "TORCHINDUCTOR_CACHE_DIR=${CONTAINER_CACHE_ROOT}/torchinductor" \
+    -e "TRITON_CACHE_DIR=${CONTAINER_CACHE_ROOT}/triton" \
+    -e "VLLM_CACHE_ROOT=${CONTAINER_CACHE_ROOT}/vllm" \
+    -e "XDG_CACHE_HOME=${CONTAINER_CACHE_ROOT}/xdg" \
     -e "PYTORCH_ROCM_ARCH=" \
     --name "${container_name}" \
     "${image_name}" \
-    /bin/bash -c "${commands}"
+    /bin/bash -c "${CONTAINER_PREFLIGHT} && ${commands}"
 
   exit_code=$?
   handle_pytest_exit "$exit_code"

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

@@ -31,6 +31,22 @@ function cpu_tests() {
     set -e
     pip list"
 
+  # Run kernel tests
+  docker exec cpu-test bash -c "
+    set -e
+    pytest -x -v -s tests/kernels/test_onednn.py
+    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_moe.py -k test_cpu_fused_moe_basic
+    pytest -x -v -s tests/kernels/mamba/cpu/test_cpu_gdn_ops.py"
+
+  # skip tests requiring model downloads if HF_TOKEN is not set
+  # due to rate-limits
+  if [ -z "$HF_TOKEN" ]; then
+    echo "Warning: HF_TOKEN is not set. Skipping tests that require model downloads."
+    return
+  fi
+
   # offline inference
   docker exec cpu-test bash -c "
     set -e
@@ -46,13 +62,6 @@ function cpu_tests() {
     set -e
     pytest -x -v -s tests/quantization/test_compressed_tensors.py::test_compressed_tensors_w8a8_logprobs"
 
-  # Run kernel tests
-  docker exec cpu-test bash -c "
-    set -e
-    pytest -x -v -s tests/kernels/test_onednn.py
-    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_moe.py -k test_cpu_fused_moe_basic"
 
   # basic online serving
   docker exec cpu-test bash -c '
@@ -67,6 +76,21 @@ function cpu_tests() {
       --num-prompts 20 \
       --endpoint /v1/completions
     kill -s SIGTERM $server_pid &'
+
+  # smoke test for Gated DeltaNet
+  docker exec cpu-test bash -c '
+    set -e
+    VLLM_CPU_OMP_THREADS_BIND=$E2E_OMP_THREADS vllm serve Qwen/Qwen3.5-0.8B --max-model-len 2048 &
+    server_pid=$!
+    timeout 600 bash -c "until curl localhost:8000/v1/models; do sleep 1; done" || exit 1
+    vllm bench serve \
+      --backend vllm \
+      --dataset-name random \
+      --model Qwen/Qwen3.5-0.8B \
+      --num-prompts 20 \
+      --endpoint /v1/completions
+    kill -s SIGTERM $server_pid &'
+
 }
 
 # All of CPU tests are expected to be finished less than 40 mins.

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

@@ -324,23 +324,6 @@ IMAGE="${IMAGE_TAG_XPU:-${image_name}}"
 
 echo "Using image: ${IMAGE}"
 
-if docker image inspect "${IMAGE}" >/dev/null 2>&1; then
-  echo "Image already exists locally, skipping pull"
-else
-  echo "Image not found locally, waiting for lock..."
-
-  flock /tmp/docker-pull.lock bash -c "
-    if docker image inspect '${IMAGE}' >/dev/null 2>&1; then
-      echo 'Image already pulled by another runner'
-    else
-      echo 'Pulling image...'
-      timeout 900 docker pull '${IMAGE}'
-    fi
-  "
-
-  echo "Pull step completed"
-fi
-
 remove_docker_container() {
   docker rm -f "${container_name}" || true
 }
@@ -352,17 +335,36 @@ if [[ -z "${ZE_AFFINITY_MASK:-}" ]]; then
   echo "Warning: ZE_AFFINITY_MASK is not set. Proceeding without device affinity." >&2
 fi
 
-docker run \
+export CMDS="${commands}"
+export HF_TOKEN ZE_AFFINITY_MASK
+
+{
+  flock 9
+  if docker image inspect "${IMAGE}" >/dev/null 2>&1; then
+    echo "Image already exists locally, skipping pull"
+  else
+    echo "Image not found locally, pulling image..."
+    timeout 900 docker pull "${IMAGE}"
+    echo "Pull step completed"
+  fi
+
+  docker create \
     --device /dev/dri:/dev/dri \
     --net=host \
     --ipc=host \
     --privileged \
     -v /dev/dri/by-path:/dev/dri/by-path \
-    -v ${HOME}/.cache/huggingface:/root/.cache/huggingface \
-    --entrypoint="" \
-    -e "HF_TOKEN=${HF_TOKEN:-}" \
-    -e "ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK:-}" \
-    -e "CMDS=${commands}" \
+    -v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
+    --entrypoint='' \
+    -e HF_TOKEN \
+    -e ZE_AFFINITY_MASK \
+    -e BUILDKITE_PARALLEL_JOB \
+    -e BUILDKITE_PARALLEL_JOB_COUNT \
+    -e CMDS \
     --name "${container_name}" \
-    "${image_name}" \
-    bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"'
+    "${IMAGE}" \
+    bash -c 'set -e; echo "ZE_AFFINITY_MASK is ${ZE_AFFINITY_MASK:-}"; eval "$CMDS"' \
+    >/dev/null
+} 9>/tmp/docker-pull.lock
+
+docker start -a "${container_name}"

.buildkite/scripts/hardware_ci/run-tpu-v1-test-part2.sh

@@ -61,7 +61,7 @@ echo "Results will be stored in: $RESULTS_DIR"
 echo "--- Installing Python dependencies ---"
 python3 -m pip install --progress-bar off git+https://github.com/thuml/depyf.git \
     && python3 -m pip install --progress-bar off pytest pytest-asyncio tpu-info \
-    && python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.11" \
+    && python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.12" \
     && python3 -m pip install --progress-bar off hf-transfer tblib==3.1.0
 echo "--- Python dependencies installed ---"
 

.buildkite/scripts/hardware_ci/run-tpu-v1-test.sh

@@ -61,7 +61,7 @@ echo "Results will be stored in: $RESULTS_DIR"
 echo "--- Installing Python dependencies ---"
 python3 -m pip install --progress-bar off git+https://github.com/thuml/depyf.git \
     && python3 -m pip install --progress-bar off pytest pytest-asyncio tpu-info \
-    && python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.11" \
+    && python3 -m pip install --progress-bar off "lm-eval[api]>=0.4.12" \
     && python3 -m pip install --progress-bar off hf-transfer tblib==3.1.0
 echo "--- Python dependencies installed ---"
 
@@ -136,8 +136,6 @@ run_and_track_test 3 "test_accuracy.py::test_lm_eval_accuracy_v1_engine" \
     "python3 -m pytest -s -v /workspace/vllm/tests/entrypoints/llm/test_accuracy.py::test_lm_eval_accuracy_v1_engine"
 run_and_track_test 4 "test_quantization_accuracy.py" \
     "python3 -m pytest -s -v /workspace/vllm/tests/tpu/test_quantization_accuracy.py"
-run_and_track_test 5 "examples/offline_inference/tpu.py" \
-    "python3 /workspace/vllm/examples/offline_inference/tpu.py"
 run_and_track_test 6 "test_tpu_model_runner.py" \
     "python3 -m pytest -s -v /workspace/vllm/tests/v1/tpu/worker/test_tpu_model_runner.py"
 run_and_track_test 7 "test_sampler.py" \

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

@@ -1,53 +0,0 @@
-#!/bin/bash
-
-# This script build the CPU docker image and run the offline inference inside the container.
-# It serves a sanity check for compilation and basic model usage.
-set -ex
-
-image_name="xpu/vllm-ci:${BUILDKITE_COMMIT}"
-container_name="xpu_${BUILDKITE_COMMIT}_$(tr -dc A-Za-z0-9 < /dev/urandom | head -c 10; echo)"
-
-# Try building the docker image
-docker build -t "${image_name}" -f docker/Dockerfile.xpu .
-
-# Setup cleanup
-remove_docker_container() {
-  docker rm -f "${container_name}" || true
-}
-trap remove_docker_container EXIT
-
-# Run the image and test offline inference/tensor parallel
-docker run \
-    --device /dev/dri:/dev/dri \
-    --net=host \
-    --ipc=host \
-    --privileged \
-    -v /dev/dri/by-path:/dev/dri/by-path \
-    --entrypoint="" \
-    -e "HF_TOKEN=${HF_TOKEN}" \
-    -e "ZE_AFFINITY_MASK=${ZE_AFFINITY_MASK}" \
-    --name "${container_name}" \
-    "${image_name}" \
-    bash -c '
-    set -e
-    echo $ZE_AFFINITY_MASK
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 -O3 -cc.cudagraph_mode=NONE
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager -tp 2 --distributed-executor-backend ray
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager -tp 2 --distributed-executor-backend mp
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --attention-backend=TRITON_ATTN
-    python3 examples/basic/offline_inference/generate.py --model facebook/opt-125m --block-size 64 --enforce-eager --quantization fp8
-    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 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 OPEA/Qwen2.5-0.5B-Instruct-int4-sym-inc --block-size 64 --enforce-eager --max-model-len 8192
-    cd tests
-    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
-    pytest -v -s v1/sample --ignore=v1/sample/test_logprobs.py --ignore=v1/sample/test_logprobs_e2e.py
-    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/spec_decode --ignore=v1/spec_decode/test_max_len.py --ignore=v1/spec_decode/test_tree_attention.py --ignore=v1/spec_decode/test_speculators_eagle3.py --ignore=v1/spec_decode/test_acceptance_length.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
-    pytest -v -s v1/test_serial_utils.py
-'

.buildkite/scripts/install-kv-connectors.sh

@@ -0,0 +1,39 @@
+#!/bin/bash
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+set -euo pipefail
+
+REQUIREMENTS_FILE="${KV_CONNECTORS_REQUIREMENTS:-/vllm-workspace/requirements/kv_connectors.txt}"
+
+uv pip install --system -r "${REQUIREMENTS_FILE}"
+
+NIXL_METADATA=$(python3 - <<'PY'
+import importlib.metadata as metadata
+
+import torch
+
+cuda_version = torch.version.cuda
+if cuda_version is None:
+    raise SystemExit("torch.version.cuda is not set")
+
+print(cuda_version.split(".", 1)[0], metadata.version("nixl"))
+PY
+)
+read -r CUDA_MAJOR NIXL_VERSION <<<"${NIXL_METADATA}"
+
+# nixl>=1.1.0 can install multiple CUDA wheel variants. Keep only the variant
+# matching this CI image so nixl_ep_cpp links against the available libcudart.
+uv pip uninstall --system nixl-cu12 nixl-cu13 2>/dev/null || true
+uv pip install --system --no-deps "nixl-cu${CUDA_MAJOR}==${NIXL_VERSION}"
+
+python3 - <<'PY'
+import importlib.metadata as metadata
+
+for package_name in ("nixl", "nixl-cu12", "nixl-cu13"):
+    try:
+        version = metadata.version(package_name)
+    except metadata.PackageNotFoundError:
+        version = "not installed"
+    print(f"{package_name}: {version}")
+PY

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

@@ -0,0 +1,180 @@
+#!/bin/bash
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+#
+# Publish release Docker images from ECR to DockerHub.
+# Pulls per-arch images, tags with latest and versioned tags, pushes them,
+# then creates and pushes multi-arch manifests.
+
+set -euo pipefail
+
+RELEASE_VERSION=$(buildkite-agent meta-data get release-version --default "" | sed 's/^v//')
+if [ -z "${RELEASE_VERSION}" ]; then
+  echo "ERROR: release-version metadata not set"
+  exit 1
+fi
+
+COMMIT="$BUILDKITE_COMMIT"
+ROCM_BASE_CACHE_KEY=$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
+
+echo "========================================"
+echo "Publishing release images v${RELEASE_VERSION}"
+echo "  Commit: ${COMMIT}"
+echo "  ROCm base cache key: ${ROCM_BASE_CACHE_KEY}"
+echo "========================================"
+
+# Login to ECR to pull staging images
+aws ecr-public get-login-password --region us-east-1 | \
+  docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
+
+# ---- CUDA (default: 13.0) ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64 vllm/vllm-openai:latest-x86_64
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
+docker push vllm/vllm-openai:latest-x86_64
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64 vllm/vllm-openai:latest-aarch64
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
+docker push vllm/vllm-openai:latest-aarch64
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
+
+docker manifest rm vllm/vllm-openai:latest || true
+docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION} || true
+docker manifest create vllm/vllm-openai:latest vllm/vllm-openai:latest-x86_64 vllm/vllm-openai:latest-aarch64
+docker manifest create vllm/vllm-openai:v${RELEASE_VERSION} vllm/vllm-openai:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64
+docker manifest push vllm/vllm-openai:latest
+docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}
+
+# ---- CUDA 12.9 ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129 vllm/vllm-openai:latest-x86_64-cu129
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
+docker push vllm/vllm-openai:latest-x86_64-cu129
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129 vllm/vllm-openai:latest-aarch64-cu129
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
+docker push vllm/vllm-openai:latest-aarch64-cu129
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
+
+docker manifest rm vllm/vllm-openai:latest-cu129 || true
+docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-cu129 || true
+docker manifest create vllm/vllm-openai:latest-cu129 vllm/vllm-openai:latest-x86_64-cu129 vllm/vllm-openai:latest-aarch64-cu129
+docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129
+docker manifest push vllm/vllm-openai:latest-cu129
+docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu129
+
+# ---- Ubuntu 24.04 (CUDA 13.0) ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404 vllm/vllm-openai:latest-x86_64-ubuntu2404
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404
+docker push vllm/vllm-openai:latest-x86_64-ubuntu2404
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404 vllm/vllm-openai:latest-aarch64-ubuntu2404
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
+docker push vllm/vllm-openai:latest-aarch64-ubuntu2404
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
+
+docker manifest rm vllm/vllm-openai:latest-ubuntu2404 || true
+docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404 || true
+docker manifest create vllm/vllm-openai:latest-ubuntu2404 vllm/vllm-openai:latest-x86_64-ubuntu2404 vllm/vllm-openai:latest-aarch64-ubuntu2404
+docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-ubuntu2404
+docker manifest push vllm/vllm-openai:latest-ubuntu2404
+docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-ubuntu2404
+
+# ---- Ubuntu 24.04 (CUDA 12.9) ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404
+docker push vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404 vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-aarch64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
+docker push vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
+docker push vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
+
+docker manifest rm vllm/vllm-openai:latest-cu129-ubuntu2404 || true
+docker manifest rm vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404 || true
+docker manifest create vllm/vllm-openai:latest-cu129-ubuntu2404 vllm/vllm-openai:latest-x86_64-cu129-ubuntu2404 vllm/vllm-openai:latest-aarch64-cu129-ubuntu2404
+docker manifest create vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-x86_64-cu129-ubuntu2404 vllm/vllm-openai:v${RELEASE_VERSION}-aarch64-cu129-ubuntu2404
+docker manifest push vllm/vllm-openai:latest-cu129-ubuntu2404
+docker manifest push vllm/vllm-openai:v${RELEASE_VERSION}-cu129-ubuntu2404
+
+# ---- ROCm ----
+
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm
+docker pull public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm vllm/vllm-openai-rocm:latest
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${COMMIT}-rocm vllm/vllm-openai-rocm:v${RELEASE_VERSION}
+docker push vllm/vllm-openai-rocm:latest
+docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}
+
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:latest-base
+docker tag public.ecr.aws/q9t5s3a7/vllm-release-repo:${ROCM_BASE_CACHE_KEY}-rocm-base vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
+docker push vllm/vllm-openai-rocm:latest-base
+docker push vllm/vllm-openai-rocm:v${RELEASE_VERSION}-base
+
+# ---- CPU ----
+# CPU images are behind separate block steps and may not have been built.
+# All-or-nothing: inspect both arches first, then either publish everything
+# (per-arch + multi-arch manifest) or skip everything. Publishing only one
+# arch would leave `:latest-x86_64` pointing at the new release while the
+# `:latest` multi-arch manifest still resolves to the previous release.
+
+CPU_X86_TAG=public.ecr.aws/q9t5s3a7/vllm-cpu-release-repo:v${RELEASE_VERSION}
+CPU_ARM_TAG=public.ecr.aws/q9t5s3a7/vllm-arm64-cpu-release-repo:v${RELEASE_VERSION}
+
+CPU_X86_AVAILABLE=false
+CPU_ARM_AVAILABLE=false
+docker manifest inspect "${CPU_X86_TAG}" >/dev/null 2>&1 && CPU_X86_AVAILABLE=true
+docker manifest inspect "${CPU_ARM_TAG}" >/dev/null 2>&1 && CPU_ARM_AVAILABLE=true
+
+if [ "$CPU_X86_AVAILABLE" = "true" ] && [ "$CPU_ARM_AVAILABLE" = "true" ]; then
+  docker pull "${CPU_X86_TAG}"
+  docker tag "${CPU_X86_TAG}" vllm/vllm-openai-cpu:latest-x86_64
+  docker tag "${CPU_X86_TAG}" vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
+  docker push vllm/vllm-openai-cpu:latest-x86_64
+  docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64
+
+  docker pull "${CPU_ARM_TAG}"
+  docker tag "${CPU_ARM_TAG}" vllm/vllm-openai-cpu:latest-arm64
+  docker tag "${CPU_ARM_TAG}" vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
+  docker push vllm/vllm-openai-cpu:latest-arm64
+  docker push vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
+
+  docker manifest rm vllm/vllm-openai-cpu:latest || true
+  docker manifest rm vllm/vllm-openai-cpu:v${RELEASE_VERSION} || true
+  docker manifest create vllm/vllm-openai-cpu:latest vllm/vllm-openai-cpu:latest-x86_64 vllm/vllm-openai-cpu:latest-arm64
+  docker manifest create vllm/vllm-openai-cpu:v${RELEASE_VERSION} vllm/vllm-openai-cpu:v${RELEASE_VERSION}-x86_64 vllm/vllm-openai-cpu:v${RELEASE_VERSION}-arm64
+  docker manifest push vllm/vllm-openai-cpu:latest
+  docker manifest push vllm/vllm-openai-cpu:v${RELEASE_VERSION}
+elif [ "$CPU_X86_AVAILABLE" = "false" ] && [ "$CPU_ARM_AVAILABLE" = "false" ]; then
+  echo "WARNING: Neither CPU image found in ECR, skipping CPU publish (ensure block-cpu-release-image-build and block-arm64-cpu-release-image-build were unblocked and the builds finished pushing)"
+else
+  # Partial state: one arch built, the other did not. Fail loudly rather than
+  # ship a Docker Hub state where `:latest-${arch}` and `:latest` (multi-arch)
+  # disagree on which release they point at.
+  echo "ERROR: Partial CPU build detected (x86_64=${CPU_X86_AVAILABLE}, arm64=${CPU_ARM_AVAILABLE})."
+  echo "       Refusing to publish to avoid split-tag drift between per-arch and multi-arch tags."
+  echo "       Re-run the missing CPU build and retry, or manually publish if a single-arch release is intended."
+  exit 1
+fi
+
+echo ""
+echo "Successfully published release images for v${RELEASE_VERSION}"

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

@@ -0,0 +1,187 @@
+#!/usr/bin/env bash
+set -euo pipefail
+
+MODE="${1:-}"
+
+if [[ "$MODE" != "style-clippy" && "$MODE" != "test" ]]; then
+  echo "Usage: $0 {style-clippy|test}" >&2
+  exit 2
+fi
+
+ROOT_DIR="$(git rev-parse --show-toplevel)"
+cd "$ROOT_DIR"
+
+export CARGO_TERM_COLOR="${CARGO_TERM_COLOR:-always}"
+export CARGO_HOME="${CARGO_HOME:-$HOME/.cargo}"
+export RUSTUP_HOME="${RUSTUP_HOME:-$HOME/.rustup}"
+export PATH="$CARGO_HOME/bin:$PATH"
+
+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)
+      arch="x86_64"
+      ;;
+    aarch64|arm64)
+      arch="aarch_64"
+      ;;
+    *)
+      echo "Unsupported protoc architecture: $(uname -m)" >&2
+      return 1
+      ;;
+  esac
+
+  local url="https://github.com/protocolbuffers/protobuf/releases/download/v${version}/protoc-${version}-linux-${arch}.zip"
+  local tmp_dir
+  tmp_dir="$(mktemp -d)"
+
+  log_section "Installing 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"
+}
+
+rust_toolchain() {
+  awk -F '"' '/channel[[:space:]]*=/ { print $2; exit }' rust-toolchain.toml
+}
+
+install_rust_toolchain() {
+  log_section "Installing Rust toolchain"
+  if ! command -v rustup >/dev/null 2>&1; then
+    curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs \
+      | sh -s -- -y --profile minimal --default-toolchain none
+  fi
+
+  local toolchain
+  toolchain="$(rust_toolchain)"
+  rustup toolchain install "$toolchain" --profile minimal --component rustfmt,clippy
+  rustup component add --toolchain "$toolchain" rustfmt clippy
+}
+
+install_cargo_binstall() {
+  if command -v cargo-binstall >/dev/null 2>&1; then
+    return
+  fi
+
+  log_section "Installing cargo-binstall"
+  curl -L --proto '=https' --tlsv1.2 -sSf \
+    https://raw.githubusercontent.com/cargo-bins/cargo-binstall/main/install-from-binstall-release.sh \
+    | bash
+}
+
+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
+}
+
+install_cargo_nextest() {
+  if command -v cargo-nextest >/dev/null 2>&1; then
+    return
+  fi
+
+  log_section "Installing cargo-nextest"
+  install_cargo_binstall
+  cargo binstall --no-confirm --secure cargo-nextest
+}
+
+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 \
+    | env UV_INSTALL_DIR="$CARGO_HOME/bin" sh
+}
+
+setup_pyo3_python() {
+  local python_version="${PYO3_PYTHON_VERSION:-3.12}"
+
+  log_section "Installing Python ${python_version} for PyO3 tests"
+  uv python install "$python_version"
+  PYO3_PYTHON="$(uv python find \
+    --managed-python \
+    --no-project \
+    --resolve-links \
+    "$python_version")"
+  export PYO3_PYTHON
+
+  local python_libdir
+  python_libdir="$("$PYO3_PYTHON" - <<'PY'
+import pathlib
+import sysconfig
+
+libdir = pathlib.Path(sysconfig.get_config_var("LIBDIR"))
+ldlibrary = sysconfig.get_config_var("LDLIBRARY")
+assert sysconfig.get_config_var("Py_ENABLE_SHARED") == 1
+assert ldlibrary
+assert (libdir / ldlibrary).exists(), libdir / ldlibrary
+print(libdir)
+PY
+)"
+
+  export LD_LIBRARY_PATH="${python_libdir}:${LD_LIBRARY_PATH:-}"
+  export LIBRARY_PATH="${python_libdir}:${LIBRARY_PATH:-}"
+}
+
+run_style_clippy() {
+  install_cargo_sort
+
+  log_section "Checking Rust formatting"
+  cargo fmt --manifest-path rust/Cargo.toml --all -- --check
+
+  log_section "Checking Cargo.toml ordering"
+  cargo sort --workspace --check rust
+
+  log_section "Running clippy"
+  cargo clippy \
+    --manifest-path rust/Cargo.toml \
+    --workspace \
+    --all-targets \
+    --all-features \
+    --locked \
+    -- \
+    -D warnings
+}
+
+run_tests() {
+  install_uv
+  setup_pyo3_python
+  install_cargo_nextest
+
+  log_section "Running cargo nextest"
+  cargo nextest run \
+    --manifest-path rust/Cargo.toml \
+    --workspace \
+    --all-features \
+    --locked \
+    --no-fail-fast
+}
+
+install_protoc
+install_rust_toolchain
+
+case "$MODE" in
+  style-clippy)
+    run_style_clippy
+    ;;
+  test)
+    run_tests
+    ;;
+esac

.buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_ep_eplb.sh

@@ -49,6 +49,7 @@ for BACK in "${BACKENDS[@]}"; do
     --data-parallel-size 2 \
     --enable-expert-parallel \
     --enable-eplb \
+    --eplb-config '{"use_async": false}' \
     --trust-remote-code \
     --max-model-len 2048 \
     --all2all-backend "$BACK" \

.buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_prefetch_offload.sh

@@ -51,6 +51,7 @@ vllm serve "$MODEL" \
   --offload-num-in-group 2 \
   --offload-prefetch-step 1 \
   --offload-params w13_weight w2_weight \
+  --generation-config vllm \
   --port "$PORT" \
   ${EXTRA_ARGS+"${EXTRA_ARGS[@]}"} &
 SERVER_PID=$!

.buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh

@@ -48,7 +48,7 @@ for BACK in "${BACKENDS[@]}"; do
     --enforce-eager \
     --enable-eplb \
     --all2all-backend "$BACK" \
-    --eplb-config '{"window_size":10, "step_interval":100, "num_redundant_experts":0, "log_balancedness":true}' \
+    --eplb-config '{"window_size":10, "step_interval":100, "num_redundant_experts":0, "log_balancedness":true, "use_async":false}' \
     --tensor-parallel-size "${TENSOR_PARALLEL_SIZE}" \
     --data-parallel-size "${DATA_PARALLEL_SIZE}" \
     --enable-expert-parallel \

.buildkite/scripts/tool_call/run-bfcl-eval.sh

@@ -70,7 +70,7 @@ echo "============================================"
 # ---- Install bfcl-eval if missing ----
 if ! python3 -c "import bfcl_eval" 2>/dev/null; then
     echo "Installing bfcl-eval..."
-    pip install "bfcl-eval>=2025.10.20.1,<2026"
+    uv pip install "bfcl-eval>=2025.10.20.1,<2026"
 fi
 
 # ---- Cleanup handler ----
@@ -100,7 +100,7 @@ SERVE_ARGS=(
     --tensor-parallel-size "$TP_SIZE"
     --max-model-len "$MAX_MODEL_LEN"
     --enforce-eager
-    --no-enable-prefix-caching
+    --enable-prefix-caching
 )
 
 # Append reasoning parser if specified

.buildkite/scripts/upload-release-wheels-pypi.sh

@@ -39,10 +39,17 @@ fi
 
 set -x # avoid printing secrets above
 
-# install twine from pypi
-python3 -m venv /tmp/vllm-release-env
+# install uv if not already available
+if ! command -v uv &> /dev/null; then
+  curl -LsSf https://astral.sh/uv/install.sh | UV_VERSION=0.11.14 sh
+  export PATH="$HOME/.local/bin:$PATH"
+fi
+
+# install twine and sdist build prerequisites using uv with Python 3.12
+uv venv --python 3.12 /tmp/vllm-release-env
 source /tmp/vllm-release-env/bin/activate
-pip install twine
+uv pip install twine
+uv pip install -r requirements/build/cuda.txt
 python3 -m twine --version
 
 # copy release wheels to local directory

.buildkite/test_areas/attention.yaml

@@ -2,8 +2,8 @@ group: Attention
 depends_on: 
   - image-build
 steps:
-- label: V1 attention (H100)
-  key: v1-attention-h100
+- label: V1 attention (H100-MI300)
+  key: v1-attention-h100-mi300
   timeout_in_minutes: 30
   device: h100
   source_file_dependencies:
@@ -13,11 +13,25 @@ steps:
     - tests/v1/attention
   commands:
     - pytest -v -s v1/attention
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 70
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - vllm/config/attention.py
+      - vllm/model_executor/layers/attention
+      - vllm/v1/attention
+      - tests/v1/attention
+      - vllm/_aiter_ops.py
+      - vllm/envs.py
+      - vllm/platforms/rocm.py
 
 - label: V1 attention (B200)
   key: v1-attention-b200
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   source_file_dependencies:
     - vllm/config/attention.py
     - vllm/model_executor/layers/attention

.buildkite/test_areas/basic_correctness.yaml

@@ -10,9 +10,9 @@ steps:
   - vllm/
   - tests/basic_correctness/test_basic_correctness
   - tests/basic_correctness/test_cpu_offload
-  - tests/basic_correctness/test_cumem.py
+  - tests/basic_correctness/test_mem.py
   commands:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  - pytest -v -s basic_correctness/test_cumem.py
+  - pytest -v -s basic_correctness/test_mem.py
   - pytest -v -s basic_correctness/test_basic_correctness.py
   - pytest -v -s basic_correctness/test_cpu_offload.py

.buildkite/test_areas/benchmarks.yaml

@@ -14,7 +14,7 @@ steps:
 
 - label: Attention Benchmarks Smoke Test (B200)
   key: attention-benchmarks-smoke-test-b200
-  device: b200
+  device: b200-k8s
   num_gpus: 2
   optional: true
   working_dir: "/vllm-workspace/"

.buildkite/test_areas/compile.yaml

@@ -43,7 +43,7 @@ steps:
   key: asynctp-correctness-tests-b200
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   commands:
@@ -68,7 +68,7 @@ steps:
   key: fusion-and-compile-unit-tests-2xb200
   timeout_in_minutes: 20
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   source_file_dependencies:
   - csrc/quantization/fp4/
   - vllm/model_executor/layers/quantization/
@@ -137,7 +137,7 @@ steps:
   key: fusion-e2e-config-sweep-b200
   timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   num_devices: 1
   optional: true
   commands:
@@ -209,7 +209,7 @@ steps:
   key: fusion-e2e-tp2-b200
   timeout_in_minutes: 20
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   num_devices: 2
   source_file_dependencies:
     - csrc/quantization/

.buildkite/test_areas/cuda.yaml

@@ -7,7 +7,11 @@ steps:
   timeout_in_minutes: 15
   device: h200_18gb
   source_file_dependencies:
-  - vllm/
+  - vllm/envs.py
+  - vllm/logger.py
+  - vllm/platforms/
+  - vllm/plugins/
+  - vllm/utils/
   - tests/cuda
   commands:
     - pytest -v -s cuda/test_cuda_context.py
@@ -23,4 +27,5 @@ steps:
   - vllm/compilation
   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_cudagraph_mode.py
+    - pytest -v -s v1/cudagraph/test_breakable_cudagraph.py

.buildkite/test_areas/disaggregated.yaml

@@ -8,10 +8,10 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 - label: Distributed FlashInfer NixlConnector PD accuracy (4 GPUs)
   key: distributed-flashinfer-nixlconnector-pd-accuracy-4-gpus
@@ -19,10 +19,10 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - FLASHINFER=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 
 - label: DP EP Distributed NixlConnector PD accuracy tests (4 GPUs)
@@ -31,10 +31,10 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - DP_EP=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 
 - label: CrossLayer KV layout Distributed NixlConnector PD accuracy tests (4 GPUs)
@@ -43,37 +43,51 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - CROSS_LAYERS_BLOCKS=True bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 
 - label: Hybrid SSM NixlConnector PD accuracy tests (4 GPUs)
   key: hybrid-ssm-nixlconnector-pd-accuracy-tests-4-gpus
-  timeout_in_minutes: 20
+  timeout_in_minutes: 25
   working_dir: "/vllm-workspace/tests"
   num_devices: 4
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - HYBRID_SSM=1 bash v1/kv_connector/nixl_integration/config_sweep_accuracy_test.sh
 
+- label: Hybrid SSM NixlConnector PD prefix cache test (2 GPUs)
+  key: hybrid-ssm-nixlconnector-pd-prefix-cache-2-gpus
+  timeout_in_minutes: 25
+  working_dir: "/vllm-workspace/tests"
+  num_devices: 2
+  source_file_dependencies:
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
+    - vllm/v1/core/sched/
+    - vllm/v1/core/kv_cache_coordinator.py
+    - tests/v1/kv_connector/nixl_integration/
+  commands:
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
+    - bash v1/kv_connector/nixl_integration/run_mamba_prefix_cache_test.sh
+
 - label: MultiConnector (Nixl+Offloading) PD accuracy (2 GPUs)
   key: multiconnector-nixl-offloading-pd-accuracy-2-gpus
   timeout_in_minutes: 30
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
     - vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
     - vllm/distributed/kv_transfer/kv_connector/v1/offloading/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - bash v1/kv_connector/nixl_integration/run_multi_connector_accuracy_test.sh
 
 - label: NixlConnector PD + Spec Decode acceptance (2 GPUs)
@@ -83,12 +97,12 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - vllm/v1/worker/kv_connector_model_runner_mixin.py
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
-    - bash v1/kv_connector/nixl_integration/spec_decode_acceptance_test.sh
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
+    - 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
@@ -96,11 +110,11 @@ steps:
   working_dir: "/vllm-workspace/tests"
   num_devices: 2
   source_file_dependencies:
-    - vllm/distributed/kv_transfer/kv_connector/v1/nixl_connector.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/nixl/
     - vllm/distributed/kv_transfer/kv_connector/v1/multi_connector.py
     - vllm/distributed/kv_transfer/kv_connector/v1/offloading_connector.py
     - vllm/distributed/kv_transfer/kv_connector/v1/offloading/
     - tests/v1/kv_connector/nixl_integration/
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
-    - bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
+    - bash v1/kv_connector/nixl_integration/run_multi_connector_edge_case_test.sh

.buildkite/test_areas/distributed.yaml

@@ -212,7 +212,7 @@ steps:
 
 - label: Distributed Tests (2 GPUs)(B200)
   key: distributed-tests-2-gpus-b200
-  device: b200
+  device: b200-k8s
   optional: true
   working_dir: "/vllm-workspace/"
   num_devices: 2

.buildkite/test_areas/e2e_integration.yaml

@@ -2,8 +2,8 @@ group: E2E Integration
 depends_on: 
   - image-build
 steps:
-- label: DeepSeek V2-Lite Accuracy
-  key: deepseek-v2-lite-accuracy
+- label: DeepSeek V2-Lite Sync EPLB Accuracy
+  key: deepseek-v2-lite-sync-eplb-accuracy
   timeout_in_minutes: 60
   device: h100
   optional: true
@@ -12,8 +12,8 @@ steps:
   commands:
   - bash .buildkite/scripts/scheduled_integration_test/deepseek_v2_lite_ep_eplb.sh 0.25 200 8010
 
-- label: Qwen3-30B-A3B-FP8-block Accuracy
-  key: qwen3-30b-a3b-fp8-block-accuracy
+- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy
+  key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy
   timeout_in_minutes: 60
   device: h100
   optional: true
@@ -22,10 +22,10 @@ steps:
   commands:
   - bash .buildkite/scripts/scheduled_integration_test/qwen30b_a3b_fp8_block_ep_eplb.sh 0.8 200 8020
 
-- label: Qwen3-30B-A3B-FP8-block Accuracy (B200)
-  key: qwen3-30b-a3b-fp8-block-accuracy-b200
+- label: Qwen3-30B-A3B-FP8-block Sync EPLB Accuracy (B200)
+  key: qwen3-30b-a3b-fp8-block-sync-eplb-accuracy-b200
   timeout_in_minutes: 60
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   working_dir: "/vllm-workspace"

.buildkite/test_areas/engine.yaml

@@ -7,14 +7,31 @@ steps:
   timeout_in_minutes: 15
   device: h200_18gb
   source_file_dependencies:
-  - vllm/
+  - vllm/compilation/
+  - vllm/config/
+  - vllm/engine/
+  - vllm/entrypoints/logger.py
+  - vllm/envs.py
+  - vllm/logger.py
+  - vllm/logging_utils/
+  - vllm/platforms/
+  - vllm/sequence.py
+  - vllm/triton_utils/
+  - vllm/utils/
   - tests/engine
   - tests/test_sequence
   - tests/test_config
   - tests/test_logger
   - tests/test_vllm_port
+  - tests/test_jit_monitor.py
   commands:
-  - pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py
+  - pytest -v -s engine test_sequence.py test_config.py test_logger.py test_vllm_port.py test_jit_monitor.py
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 60
+      depends_on:
+      - image-build-amd
 
 - label: Engine (1 GPU)
   key: engine-1-gpu
@@ -25,6 +42,12 @@ steps:
   commands:
     - pytest -v -s v1/engine/test_preprocess_error_handling.py
     - pytest -v -s v1/engine --ignore v1/engine/test_preprocess_error_handling.py
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 40
+      depends_on:
+      - image-build-amd
 
 - label: e2e Scheduling (1 GPU)
   key: e2e-scheduling-1-gpu
@@ -35,8 +58,15 @@ steps:
     - tests/v1/e2e/general/
   commands:
     - pytest -v -s v1/e2e/general/test_async_scheduling.py
+  mirror:
+    amd:
+      device: mi250_1
+      timeout_in_minutes: 60
+      depends_on:
+      - image-build-amd
 
 - label: e2e Core (1 GPU)
+  device: h200_35gb
   key: e2e-core-1-gpu
   timeout_in_minutes: 30
   source_file_dependencies:
@@ -51,16 +81,27 @@ steps:
   optional: true
   num_devices: 2
   source_file_dependencies:
-    - vllm/
-    - tests/v1/e2e
+    - vllm/compilation/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/envs.py
+    - vllm/forward_context.py
+    - vllm/inputs/
+    - vllm/logger.py
+    - vllm/logging_utils/
+    - vllm/model_executor/
+    - vllm/multimodal/
+    - vllm/platforms/
+    - vllm/sampling_params.py
+    - vllm/transformers_utils/
+    - vllm/triton_utils/
+    - vllm/utils/
+    - vllm/v1/
+    - tests/v1/e2e/spec_decode
   commands:
     # Only run tests that need exactly 2 GPUs
     - pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "tensor_parallelism"
-  mirror:
-    amd:
-      device: mi325_2
-      depends_on:
-      - image-build-amd
 
 - label: V1 e2e (4 GPUs)
   key: v1-e2e-4-gpus
@@ -68,16 +109,27 @@ steps:
   optional: true
   num_devices: 4
   source_file_dependencies:
-    - vllm/
-    - tests/v1/e2e
+    - vllm/compilation/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/envs.py
+    - vllm/forward_context.py
+    - vllm/inputs/
+    - vllm/logger.py
+    - vllm/logging_utils/
+    - vllm/model_executor/
+    - vllm/multimodal/
+    - vllm/platforms/
+    - vllm/sampling_params.py
+    - vllm/transformers_utils/
+    - vllm/triton_utils/
+    - vllm/utils/
+    - vllm/v1/
+    - tests/v1/e2e/spec_decode
   commands:
     # Only run tests that need 4 GPUs
     - pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "eagle_correctness_heavy"
-  mirror:
-    amd:
-      device: mi325_4
-      depends_on:
-      - image-build-amd
 
 - label: V1 e2e (4xH100)
   key: v1-e2e-4xh100

.buildkite/test_areas/entrypoints.yaml

@@ -8,10 +8,11 @@ steps:
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/entrypoints
-  - tests/entrypoints/
+  - tests/entrypoints/unit_tests
+  - tests/entrypoints/weight_transfer
   commands:
-  - pytest -v -s entrypoints/openai/tool_parsers
-  - pytest -v -s entrypoints/ --ignore=entrypoints/llm --ignore=entrypoints/rpc --ignore=entrypoints/sleep --ignore=entrypoints/serve/instrumentator --ignore=entrypoints/openai --ignore=entrypoints/offline_mode --ignore=entrypoints/test_chat_utils.py  --ignore=entrypoints/pooling
+  - pytest -v -s entrypoints/unit_tests
+  - pytest -v -s entrypoints/weight_transfer
 
 - label: Entrypoints Integration (LLM)
   key: entrypoints-integration-llm
@@ -20,14 +21,36 @@ steps:
   source_file_dependencies:
   - vllm/
   - tests/entrypoints/llm
-  - tests/entrypoints/offline_mode
   commands:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  - pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_collective_rpc.py
+  - pytest -v -s entrypoints/llm --ignore=entrypoints/llm/test_generate.py --ignore=entrypoints/llm/test_collective_rpc.py --ignore=entrypoints/llm/offline_mode
   - pytest -v -s entrypoints/llm/test_generate.py # it needs a clean process
-  - pytest -v -s entrypoints/offline_mode # Needs to avoid interference with other tests
+  - pytest -v -s entrypoints/llm/offline_mode # Needs to avoid interference with other tests
+  mirror:
+    amd:
+      device: mi325_1
+      depends_on:
+      - image-build-amd
 
-- label: Entrypoints Integration (API Server openai - Part 1)
+- label: Entrypoints Integration (API Server)
+  key: entrypoints-integration-api-server
+  device: h200_35gb
+  timeout_in_minutes: 130
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - vllm/
+  - tests/entrypoints/serve
+  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
+  mirror:
+    amd:
+      device: mi325_1
+      depends_on:
+      - image-build-amd
+
+- label: Entrypoints Integration (API Server OpenAI - Part 1)
   key: entrypoints-integration-api-server-openai-part-1
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
@@ -37,15 +60,15 @@ steps:
   - tests/entrypoints/test_chat_utils
   commands:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  - pytest -v -s entrypoints/openai/chat_completion --ignore=entrypoints/openai/chat_completion/test_chat_with_tool_reasoning.py --ignore=entrypoints/openai/chat_completion/test_oot_registration.py
+  - pytest -v -s entrypoints/openai --ignore=entrypoints/openai/completion --ignore=entrypoints/openai/chat_completion --ignore=entrypoints/openai/responses --ignore=entrypoints/openai/correctness
   mirror:
     amd:
       device: mi325_1
+      timeout_in_minutes: 80
       depends_on:
       - image-build-amd
 
-
-- label: Entrypoints Integration (API Server openai - Part 2)
+- label: Entrypoints Integration (API Server OpenAI - Part 2)
   key: entrypoints-integration-api-server-openai-part-2
   timeout_in_minutes: 50
   working_dir: "/vllm-workspace/tests"
@@ -54,42 +77,71 @@ steps:
   - tests/entrypoints/openai
   - tests/entrypoints/test_chat_utils
   commands:
+  - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+  - pytest -v -s entrypoints/openai/chat_completion
   - pytest -v -s entrypoints/openai/completion --ignore=entrypoints/openai/completion/test_tensorizer_entrypoint.py
-  - pytest -v -s entrypoints/openai/speech_to_text/
-  - pytest -v -s entrypoints/test_chat_utils.py
   mirror:
     amd:
       device: mi325_1
+      timeout_in_minutes: 80
       depends_on:
       - image-build-amd
 
-- label: Entrypoints Integration (API Server openai - Part 3)
-  key: entrypoints-integration-api-server-openai-part-3
+- label: Entrypoints Integration (API Server Generate)
+  key: entrypoints-integration-api-server-generate
   timeout_in_minutes: 50
-  device: h200_18gb
   working_dir: "/vllm-workspace/tests"
   source_file_dependencies:
   - vllm/
-  - tests/entrypoints/openai
-  - tests/entrypoints/test_chat_utils
-  commands:
-  - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  - pytest -v -s entrypoints/openai --ignore=entrypoints/openai/chat_completion --ignore=entrypoints/openai/completion --ignore=entrypoints/openai/speech_to_text/ --ignore=entrypoints/openai/correctness/ --ignore=entrypoints/openai/tool_parsers/ --ignore=entrypoints/openai/responses --ignore=entrypoints/openai/test_multi_api_servers.py
-
-- label: Entrypoints Integration (API Server 2)
-  key: entrypoints-integration-api-server-2
-  timeout_in_minutes: 130
-  working_dir: "/vllm-workspace/tests"
-  source_file_dependencies:
-  - vllm/
-  - tests/entrypoints/rpc
-  - tests/entrypoints/serve/instrumentator
   - tests/tool_use
+  - tests/entrypoints/tool_parsers
+  - tests/entrypoints/anthropic
+  - tests/entrypoints/generate
+  commands:
+  - pytest -v -s tool_use
+  - pytest -v -s entrypoints/tool_parsers
+  - pytest -v -s entrypoints/generate
+  - pytest -v -s entrypoints/anthropic
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 60
+      depends_on:
+      - image-build-amd
+
+- label: Entrypoints Integration (Responses API)
+  key: entrypoints-integration-responses-api
+  timeout_in_minutes: 50
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - vllm/
+  - tests/entrypoints/openai/responses
+  commands:
+  - pytest -v -s entrypoints/openai/responses
+
+- label: Entrypoints Integration (Speech to Text)
+  device: h200_35gb
+  key: entrypoints-integration-speech_to_text
+  timeout_in_minutes: 50
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - vllm/
+  - tests/entrypoints/speech_to_text
   commands:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-  - pytest -v -s entrypoints/serve/instrumentator
-  - PYTHONPATH=/vllm-workspace pytest -v -s entrypoints/rpc
-  - pytest -v -s tool_use
+  - pytest -v -s entrypoints/speech_to_text
+
+- label: Entrypoints Integration (Multimodal)
+  device: h200_35gb
+  key: entrypoints-integration-multimodal
+  timeout_in_minutes: 50
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - vllm/
+  - tests/entrypoints/multimodal
+  commands:
+  - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+  - pytest -v -s entrypoints/multimodal
 
 - label: Entrypoints Integration (Pooling)
   key: entrypoints-integration-pooling
@@ -102,16 +154,6 @@ steps:
   - export VLLM_WORKER_MULTIPROC_METHOD=spawn
   - pytest -v -s entrypoints/pooling
 
-- label: Entrypoints Integration (Responses API)
-  key: entrypoints-integration-responses-api
-  timeout_in_minutes: 50
-  working_dir: "/vllm-workspace/tests"
-  source_file_dependencies:
-  - vllm/
-  - tests/entrypoints/openai/responses
-  commands:
-  - pytest -v -s entrypoints/openai/responses
-
 - label: OpenAI API Correctness
   key: openai-api-correctness
   timeout_in_minutes: 30
@@ -119,6 +161,22 @@ steps:
   source_file_dependencies:
   - csrc/
   - vllm/entrypoints/openai/
-  - vllm/model_executor/models/whisper.py
-  commands: # LMEval+Transcription WER check
+  commands: # LMEval
   - pytest -s entrypoints/openai/correctness/
+  mirror:
+    amd:
+      device: mi325_1
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - csrc/
+      - vllm/entrypoints/openai/
+      - vllm/model_executor/layers/
+      - vllm/v1/attention/backends/
+      - vllm/v1/attention/selector.py
+      - vllm/_aiter_ops.py
+      - vllm/platforms/rocm.py
+      - vllm/model_executor/model_loader/
+      commands:
+      - bash ../tools/install_torchcodec_rocm.sh || exit 1
+      - pytest -s entrypoints/openai/correctness/

.buildkite/test_areas/kernels.yaml

@@ -21,8 +21,9 @@ steps:
   - 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
+    - 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
 
 - label: Kernels MiniMax Reduce RMS Test (2 GPUs)
   key: kernels-minimax-reduce-rms-test-2-gpus
@@ -38,6 +39,28 @@ steps:
   commands:
     - pytest -v -s kernels/core/test_minimax_reduce_rms.py
 
+- label: Deepseek V4 Kernel Test (H100)
+  key: deepseek-v4-kernel-test-h100
+  timeout_in_minutes: 15
+  device: h100
+  source_file_dependencies:
+  - csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
+  - vllm/models/deepseek_v4/common/ops/
+  - tests/kernels/test_fused_deepseek_v4_qnorm_rope_kv_insert.py
+  commands:
+    - pytest -v -s kernels/test_fused_deepseek_v4_*.py
+
+- label: Deepseek V4 Kernel Test (B200)
+  key: deepseek-v4-kernel-test-b200
+  timeout_in_minutes: 15
+  device: b200-k8s
+  source_file_dependencies:
+  - csrc/fused_deepseek_v4_qnorm_rope_kv_insert_kernel.cu
+  - vllm/models/deepseek_v4/common/ops/
+  - tests/kernels/test_fused_deepseek_v4_qnorm_rope_kv_insert.py
+  commands:
+    - pytest -v -s kernels/test_fused_deepseek_v4_*.py
+
 - label: Kernels Attention Test %N
   key: kernels-attention-test
   timeout_in_minutes: 35
@@ -52,6 +75,19 @@ steps:
     - pytest -v -s kernels/attention --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
   parallelism: 2
 
+- label: Kernels Attention DiffKV Test (H100)
+  key: kernels-attention-diffkv-test-h100
+  timeout_in_minutes: 20
+  device: h100
+  num_devices: 1
+  source_file_dependencies:
+  - vllm/v1/attention/ops/triton_unified_attention_diffkv.py
+  - vllm/v1/attention/backends/triton_attn_diffkv.py
+  - vllm/v1/attention/backends/flash_attn_diffkv.py
+  - tests/kernels/attention/test_triton_unified_attention_diffkv.py
+  commands:
+    - pytest -v -s kernels/attention/test_triton_unified_attention_diffkv.py
+
 - label: Kernels Quantization Test %N
   key: kernels-quantization-test
   timeout_in_minutes: 90
@@ -62,6 +98,19 @@ steps:
   commands:
     - pytest -v -s kernels/quantization --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT
   parallelism: 2
+  mirror:
+    amd:
+      device: mi325_1
+      source_file_dependencies:
+      - csrc/quantization/
+      - vllm/model_executor/layers/quantization
+      - tests/kernels/quantization
+      - tests/kernels/quantization/test_rocm_skinny_gemms.py
+      - vllm/_aiter_ops.py
+      - vllm/platforms/rocm.py
+      - vllm/model_executor/kernels/
+      depends_on:
+      - image-build-amd
 
 - label: Kernels MoE Test %N
   key: kernels-moe-test
@@ -91,6 +140,7 @@ steps:
 
 - label: Kernels KDA Test
   timeout_in_minutes: 20
+  device: h200_18gb
   source_file_dependencies:
   - vllm/model_executor/layers/fla/ops/kda.py
   - vllm/model_executor/layers/fla/ops/chunk_delta_h.py
@@ -105,7 +155,11 @@ steps:
   device: h100
   num_devices: 1
   source_file_dependencies:
+  - cmake/external_projects/deepgemm.cmake
   - tools/install_deepgemm.sh
+  - tools/build_deepgemm_C.py
+  - tools/setup_deepgemm_pythons.sh
+  - tools/check_wheel_deepgemm.py
   - vllm/utils/deep_gemm.py
   - vllm/model_executor/layers/fused_moe
   - vllm/model_executor/layers/quantization
@@ -115,6 +169,7 @@ steps:
   - tests/kernels/attention/test_deepgemm_attention.py
   - tests/quantization/test_cutlass_w4a16.py
   commands:
+    - python3 ../tools/check_wheel_deepgemm.py
     - pytest -v -s kernels/quantization/test_block_fp8.py
     - pytest -v -s kernels/moe/test_deepgemm.py
     - pytest -v -s kernels/moe/test_batched_deepgemm.py
@@ -125,15 +180,18 @@ steps:
   key: kernels-b200
   timeout_in_minutes: 30
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   # optional: true
   source_file_dependencies:
   - csrc/quantization/fp4/
   - csrc/attention/mla/
   - csrc/quantization/cutlass_w8a8/moe/
-  - vllm/model_executor/layers/fused_moe/cutlass_moe.py
-  - vllm/model_executor/layers/fused_moe/flashinfer_cutlass_moe.py
-  - vllm/model_executor/layers/fused_moe/flashinfer_a2a_prepare_finalize.py
+  - vllm/model_executor/layers/fused_moe/experts/cutlass_moe.py
+  - vllm/model_executor/layers/fused_moe/experts/flashinfer_cutlass_moe.py
+  - vllm/model_executor/layers/fused_moe/experts/trtllm_nvfp4_moe.py
+  - vllm/model_executor/layers/fused_moe/oracle/nvfp4.py
+  - vllm/model_executor/layers/fused_moe/prepare_finalize/flashinfer_nvlink_one_sided.py
+  - vllm/model_executor/layers/fused_moe/prepare_finalize/flashinfer_nvlink_two_sided.py
   - vllm/model_executor/layers/quantization/utils/flashinfer_utils.py
   - vllm/v1/attention/backends/flashinfer.py
   - vllm/v1/attention/backends/mla/cutlass_mla.py
@@ -166,6 +224,7 @@ steps:
     - pytest -v -s tests/kernels/moe/test_ocp_mx_moe.py
     - pytest -v -s tests/kernels/moe/test_flashinfer.py
     - 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
     # e2e
     - pytest -v -s tests/models/quantization/test_nvfp4.py
@@ -178,7 +237,7 @@ steps:
   - vllm/utils/import_utils.py
   - tests/kernels/helion/
   commands:
-    - pip install helion==1.0.0
+    - pip install helion==1.1.0
     - pytest -v -s kernels/helion/
 
  
@@ -212,7 +271,7 @@ steps:
 - label: Kernels Fp4 MoE Test (B200)
   key: kernels-fp4-moe-test-b200
   timeout_in_minutes: 60
-  device: b200
+  device: b200-k8s
   num_devices: 1
   optional: true
   commands:
@@ -242,7 +301,7 @@ steps:
 - label: Kernels FusedMoE Layer Test (2 B200s)
   key: kernels-fusedmoe-layer-test-2-b200s
   timeout_in_minutes: 90
-  device: b200
+  device: b200-k8s
   num_devices: 2
   source_file_dependencies:
   - csrc/quantization/cutlass_w8a8/moe/
@@ -254,3 +313,4 @@ steps:
   - vllm/config
   commands:
     - pytest -v -s kernels/moe/test_moe_layer.py
+    - pytest -v -s kernels/moe/test_deepep_v2_moe.py

.buildkite/test_areas/lm_eval.yaml

@@ -3,6 +3,7 @@ depends_on:
   - image-build
 steps:
 - label: LM Eval Small Models
+  device: h200_35gb
   key: lm-eval-small-models
   timeout_in_minutes: 75
   source_file_dependencies:
@@ -11,6 +12,21 @@ steps:
   autorun_on_main: true
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-small.txt
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 55
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - csrc/
+      - vllm/model_executor/layers/quantization
+      - vllm/model_executor/models/
+      - vllm/model_executor/model_loader/
+      - vllm/v1/attention/backends/
+      - vllm/v1/attention/selector.py
+      - vllm/_aiter_ops.py
+      - vllm/platforms/rocm.py
 
 # - label: LM Eval Large Models (4 GPUs)(A100)
 #   device: a100
@@ -40,7 +56,7 @@ steps:
 - label: LM Eval Small Models (B200)
   key: lm-eval-small-models-b200
   timeout_in_minutes: 120
-  device: b200
+  device: b200-k8s
   optional: true
   source_file_dependencies:
   - csrc/
@@ -48,10 +64,22 @@ steps:
   commands:
   - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell.txt
 
+- label: LM Eval Large Models (B200, EP)
+  key: lm-eval-large-models-b200-ep
+  timeout_in_minutes: 120
+  device: b200-k8s
+  optional: true
+  num_devices: 2
+  source_file_dependencies:
+  - csrc/
+  - vllm/model_executor/layers/quantization
+  commands:
+  - pytest -s -v evals/gsm8k/test_gsm8k_correctness.py --config-list-file=configs/models-blackwell-ep.txt
+
 - label: LM Eval Qwen3.5 Models (B200)
   key: lm-eval-qwen3-5-models-b200
   timeout_in_minutes: 120
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   source_file_dependencies:
@@ -84,7 +112,7 @@ steps:
   
 - label: MoE Refactor Integration Test (B200 - TEMPORARY)
   key: moe-refactor-integration-test-b200-temporary
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   commands:
@@ -92,7 +120,7 @@ steps:
 
 - label: MoE Refactor Integration Test (B200 DP - TEMPORARY)
   key: moe-refactor-integration-test-b200-dp-temporary
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   commands:
@@ -102,6 +130,7 @@ steps:
 - label: LM Eval TurboQuant KV Cache
   key: lm-eval-turboquant-kv-cache
   timeout_in_minutes: 75
+  device: h200_18gb
   source_file_dependencies:
   - vllm/model_executor/layers/quantization/turboquant/
   - vllm/v1/attention/backends/turboquant_attn.py
@@ -127,7 +156,7 @@ steps:
 - label: GPQA Eval (GPT-OSS) (B200)
   key: gpqa-eval-gpt-oss-b200
   timeout_in_minutes: 120
-  device: b200
+  device: b200-k8s
   optional: true
   num_devices: 2
   source_file_dependencies:
@@ -139,6 +168,7 @@ steps:
     - pytest -s -v evals/gpt_oss/test_gpqa_correctness.py --config-list-file=configs/models-b200.txt
 
 - label: MRCR Eval Small Models
+  device: h200_35gb
   timeout_in_minutes: 30
   source_file_dependencies:
   - tests/evals/mrcr/

.buildkite/test_areas/lora.yaml

@@ -3,13 +3,14 @@ depends_on:
   - image-build
 steps:
 - label: LoRA %N
+  device: h200_35gb
   key: lora
   timeout_in_minutes: 30
   source_file_dependencies:
   - vllm/lora
   - tests/lora
   commands:
-    - pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py --ignore=lora/test_llm_with_multi_loras.py --ignore=lora/test_olmoe_tp.py --ignore=lora/test_deepseekv2_tp.py --ignore=lora/test_gptoss_tp.py --ignore=lora/test_qwen3moe_tp.py --ignore=lora/test_qwen35_densemodel_lora.py 
+    - pytest -v -s lora --shard-id=$$BUILDKITE_PARALLEL_JOB --num-shards=$$BUILDKITE_PARALLEL_JOB_COUNT --ignore=lora/test_chatglm3_tp.py --ignore=lora/test_llama_tp.py --ignore=lora/test_qwen3_with_multi_loras.py --ignore=lora/test_olmoe_tp.py --ignore=lora/test_deepseekv2_tp.py --ignore=lora/test_gptoss_tp.py --ignore=lora/test_qwen3moe_tp.py --ignore=lora/test_qwen35_densemodel_lora.py 
   parallelism: 4
 
 
@@ -19,6 +20,7 @@ steps:
   num_devices: 4
   source_file_dependencies:
   - vllm/lora
+  - vllm/model_executor/layers/fused_moe/
   - tests/lora
   commands:
     # FIXIT: find out which code initialize cuda before running the test
@@ -30,7 +32,7 @@ steps:
     # requires multi-GPU testing for validation.
     - pytest -v -s -x lora/test_chatglm3_tp.py
     - pytest -v -s -x lora/test_llama_tp.py
-    - pytest -v -s -x lora/test_llm_with_multi_loras.py
+    - pytest -v -s -x lora/test_qwen3_with_multi_loras.py
     - pytest -v -s -x lora/test_olmoe_tp.py
     - pytest -v -s -x lora/test_gptoss_tp.py
     - pytest -v -s -x lora/test_qwen35_densemodel_lora.py

.buildkite/test_areas/misc.yaml

@@ -3,27 +3,41 @@ depends_on:
   - image-build
 steps:
 - label: V1 Spec Decode
+  device: h200_35gb
   key: v1-spec-decode
   timeout_in_minutes: 30
   source_file_dependencies:
-    - vllm/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/inputs/
+    - vllm/model_executor/
+    - vllm/platforms/
+    - vllm/sampling_params.py
+    - vllm/transformers_utils/
+    - vllm/utils/
+    - vllm/v1/
     - tests/v1/spec_decode
   commands:
     - export VLLM_WORKER_MULTIPROC_METHOD=spawn
     # TODO: create another `optional` test group for slow tests
     - pytest -v -s -m 'not slow_test' v1/spec_decode
-  mirror:
-    amd:
-      device: mi325_1
-      depends_on:
-      - image-build-amd
 
 - label: V1 Sample + Logits
   key: v1-sample-logits
   timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
-    - vllm/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/inputs/
+    - vllm/logger.py
+    - vllm/model_executor/
+    - vllm/platforms/
+    - vllm/sampling_params.py
+    - vllm/transformers_utils/
+    - vllm/utils/
+    - vllm/v1/
     - tests/v1/sample
     - tests/v1/logits_processors
     - tests/v1/test_oracle.py
@@ -46,39 +60,66 @@ steps:
   key: v1-core-kv-metrics
   timeout_in_minutes: 30
   source_file_dependencies:
-    - vllm/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/entrypoints/pooling/
+    - vllm/inputs/
+    - vllm/lora/
+    - vllm/model_executor/
+    - vllm/multimodal/
+    - vllm/outputs.py
+    - vllm/platforms/
+    - vllm/pooling_params.py
+    - vllm/profiler/
+    - vllm/sampling_params.py
+    - vllm/tokenizers/
+    - vllm/transformers_utils/
+    - vllm/utils/
+    - vllm/v1/
     - tests/v1/core
     - tests/v1/executor
     - tests/v1/kv_offload
+    - tests/v1/simple_kv_offload
     - tests/v1/worker
     - tests/v1/kv_connector/unit
     - tests/v1/metrics
     - tests/entrypoints/openai/correctness/test_lmeval.py
   commands:
-    - uv pip install --system -r /vllm-workspace/requirements/kv_connectors.txt
+    - bash /vllm-workspace/.buildkite/scripts/install-kv-connectors.sh
     - export VLLM_WORKER_MULTIPROC_METHOD=spawn
     # split the test to avoid interference
     - pytest -v -s -m 'not cpu_test' v1/core
     - pytest -v -s v1/executor
     - pytest -v -s v1/kv_offload
+    - 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/metrics
     # Integration test for streaming correctness (requires special branch).
     - pip install -U git+https://github.com/robertgshaw2-redhat/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
-      depends_on:
-      - image-build-amd
 
 - label: V1 Others (CPU)
   key: v1-others-cpu
   depends_on:
     - image-build-cpu
   source_file_dependencies:
-    - vllm/
+    - vllm/config/
+    - vllm/distributed/
+    - vllm/engine/
+    - vllm/inputs/
+    - vllm/lora/
+    - vllm/multimodal/
+    - vllm/outputs.py
+    - vllm/platforms/
+    - vllm/pooling_params.py
+    - vllm/profiler/
+    - vllm/sampling_params.py
+    - vllm/tokenizers/
+    - vllm/transformers_utils/
+    - vllm/utils/
+    - vllm/v1/
     - tests/v1
   device: cpu-small
   commands:
@@ -89,12 +130,50 @@ steps:
     - pytest -v -s -m 'cpu_test' v1/kv_connector/unit
     - pytest -v -s -m 'cpu_test' v1/metrics
 
+- label: Extract Hidden States Integration
+  key: extract-hidden-states-integration
+  timeout_in_minutes: 20
+  device: h200_18gb
+  source_file_dependencies:
+    - vllm/v1/spec_decode/extract_hidden_states.py
+    - vllm/model_executor/models/extract_hidden_states.py
+    - vllm/transformers_utils/configs/extract_hidden_states.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/example_hidden_states_connector.py
+    - tests/v1/kv_connector/extract_hidden_states_integration
+  commands:
+    - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+    - pytest -v -s v1/kv_connector/extract_hidden_states_integration
+
+- label: Extract Hidden States Integration (2 GPUs)
+  key: extract-hidden-states-integration-2-gpus
+  timeout_in_minutes: 20
+  num_devices: 2
+  source_file_dependencies:
+    - vllm/v1/spec_decode/extract_hidden_states.py
+    - vllm/model_executor/models/extract_hidden_states.py
+    - vllm/transformers_utils/configs/extract_hidden_states.py
+    - vllm/distributed/kv_transfer/kv_connector/v1/example_hidden_states_connector.py
+    - tests/v1/kv_connector/extract_hidden_states_integration
+  commands:
+    - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+    - pytest -v -s -m 'distributed' v1/kv_connector/extract_hidden_states_integration
+
 - label: Regression
   key: regression
   timeout_in_minutes: 20
   device: h200_18gb
   source_file_dependencies:
-  - vllm/
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
   - tests/test_regression
   commands:
   - pip install modelscope
@@ -102,6 +181,7 @@ steps:
   working_dir: "/vllm-workspace/tests" # optional
 
 - label: Examples
+  device: h200_35gb
   key: examples
   timeout_in_minutes: 45
   working_dir: "/vllm-workspace/examples"
@@ -127,8 +207,8 @@ steps:
     - python3 pooling/embed/vision_embedding_offline.py --seed 0
     # for features demo
     - python3 features/automatic_prefix_caching/prefix_caching_offline.py
-    - python3 offline_inference/llm_engine_example.py
-    - python3 others/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 others/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
+    - python3 deployment/llm_engine_example.py
+    - python3 features/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 features/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
     - python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 2048
     # https://github.com/vllm-project/vllm/pull/26682 uses slightly more memory in PyTorch 2.9+ causing this test to OOM in 1xL4 GPU
     - python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle3 --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 1536
@@ -138,7 +218,18 @@ steps:
   timeout_in_minutes: 20
   num_devices: 2
   source_file_dependencies:
-  - vllm/
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/tracing/
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
   - tests/v1/tracing
   commands:
   - "pip install \
@@ -151,7 +242,9 @@ steps:
 - label: Python-only Installation
   key: python-only-installation
   depends_on: ~
+  optional: true
   timeout_in_minutes: 20
+  device: h200_18gb
   source_file_dependencies:
   - tests/standalone_tests/python_only_compile.sh
   - setup.py
@@ -159,10 +252,23 @@ steps:
   - bash standalone_tests/python_only_compile.sh
 
 - label: Async Engine, Inputs, Utils, Worker
+  device: h200_35gb
   key: async-engine-inputs-utils-worker
   timeout_in_minutes: 50
   source_file_dependencies:
-  - vllm/
+  - vllm/assets/
+  - vllm/config/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/inputs/
+  - vllm/model_executor/
+  - vllm/multimodal/
+  - vllm/platforms/
+  - vllm/sampling_params.py
+  - vllm/tokenizers/
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
   - tests/detokenizer
   - tests/multimodal
   - tests/utils_
@@ -177,7 +283,32 @@ steps:
   - image-build-cpu
   timeout_in_minutes: 30
   source_file_dependencies:
-  - vllm/
+  - vllm/assets/
+  - vllm/config/
+  - vllm/engine/arg_utils.py
+  - vllm/entrypoints/chat_utils.py
+  - vllm/entrypoints/mcp/
+  - vllm/entrypoints/openai/chat_completion/protocol.py
+  - vllm/entrypoints/openai/engine/protocol.py
+  - vllm/envs.py
+  - vllm/exceptions.py
+  - vllm/inputs/
+  - vllm/model_executor/layers/quantization/quark/
+  - vllm/multimodal/
+  - vllm/outputs.py
+  - vllm/parser/
+  - vllm/platforms/
+  - vllm/pooling_params.py
+  - vllm/ray/
+  - vllm/reasoning/
+  - vllm/renderers/
+  - vllm/sampling_params.py
+  - vllm/tokenizers/
+  - vllm/tool_parsers/
+  - vllm/transformers_utils/
+  - vllm/utils/
+  - vllm/v1/
+  - tests/test_envs.py
   - tests/test_inputs.py
   - tests/test_outputs.py
   - tests/test_pooling_params.py
@@ -185,26 +316,43 @@ steps:
   - tests/multimodal
   - tests/renderers
   - tests/standalone_tests/lazy_imports.py
-  - tests/tokenizers_
   - tests/reasoning
   - tests/tool_parsers
+  - tests/tokenizers_
+  - tests/parser
   - tests/transformers_utils
   - tests/config
   device: cpu-small
   commands:
   - python3 standalone_tests/lazy_imports.py
+  - pytest -v -s test_envs.py
   - pytest -v -s test_inputs.py
   - pytest -v -s test_outputs.py
   - pytest -v -s test_pooling_params.py
   - pytest -v -s test_ray_env.py
   - pytest -v -s -m 'cpu_test' multimodal
   - pytest -v -s renderers
-  - pytest -v -s tokenizers_
-  - pytest -v -s reasoning --ignore=reasoning/test_seedoss_reasoning_parser.py --ignore=reasoning/test_glm4_moe_reasoning_parser.py --ignore=reasoning/test_gemma4_reasoning_parser.py
+  - pytest -v -s reasoning --ignore=reasoning/test_seedoss_reasoning_parser.py --ignore=reasoning/test_glm4_moe_reasoning_parser.py
   - pytest -v -s tool_parsers
+  - pytest -v -s tokenizers_
+  - pytest -v -s parser
   - pytest -v -s transformers_utils
   - pytest -v -s config
 
+- label: Batch Invariance (A100)
+  key: batch-invariance-a100
+  timeout_in_minutes: 30
+  device: a100
+  source_file_dependencies:
+    - vllm/v1/attention
+    - vllm/model_executor/layers
+    - tests/v1/determinism/
+  commands:
+    - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+    - pip install pytest-timeout pytest-forked
+    - pytest -v -s v1/determinism/test_batch_invariance.py
+    - VLLM_TEST_MODEL=deepseek-ai/DeepSeek-V2-Lite-Chat pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[TRITON_MLA]
+
 - label: Batch Invariance (H100)
   key: batch-invariance-h100
   timeout_in_minutes: 30
@@ -224,7 +372,7 @@ steps:
 - label: Batch Invariance (B200)
   key: batch-invariance-b200
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   source_file_dependencies:
     - vllm/v1/attention
     - vllm/model_executor/layers
@@ -237,8 +385,10 @@ steps:
     - VLLM_TEST_MODEL=deepseek-ai/DeepSeek-V2-Lite-Chat pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[TRITON_MLA]
     - VLLM_TEST_MODEL=Qwen/Qwen3-30B-A3B-Thinking-2507-FP8 pytest -v -s v1/determinism/test_batch_invariance.py::test_v1_generation_is_deterministic_across_batch_sizes_with_needle[FLASH_ATTN]
     - pytest -v -s v1/determinism/test_nvfp4_batch_invariant.py
+    - pytest -v -s v1/determinism/test_nvfp4_batch_invariant_scaled_mm.py
   
 - label: Acceptance Length Test (Large Models) # optional
+  device: h200_35gb
   key: acceptance-length-test-large-models
   timeout_in_minutes: 25
   gpu: h100

.buildkite/test_areas/model_executor.yaml

@@ -14,5 +14,12 @@ steps:
   commands:
     - apt-get update && apt-get install -y curl libsodium23
     - export VLLM_WORKER_MULTIPROC_METHOD=spawn
-    - pytest -v -s model_executor -m '(not slow_test)'
-    - pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py
+    # Dump tracebacks of all threads if a test hangs, so a wedged GPU/CUDA
+    # init surfaces a stack instead of silently stalling.
+    - export PYTHONFAULTHANDLER=1
+    # Per-test watchdog: a single hung test (e.g. stuck during engine/CUDA
+    # init) fails fast with a traceback instead of running until the global
+    # build timeout. The `thread` method also handles hangs inside C/CUDA
+    # calls that the signal method cannot interrupt.
+    - pytest -v -s model_executor -m '(not slow_test)' --timeout=900 --timeout-method=thread
+    - pytest -v -s entrypoints/openai/completion/test_tensorizer_entrypoint.py --timeout=900 --timeout-method=thread

.buildkite/test_areas/model_runner_v2.yaml

@@ -3,6 +3,7 @@ depends_on:
   - image-build
 steps:
 - label: Model Runner V2 Core Tests
+  device: h200_35gb
   key: model-runner-v2-core-tests
   timeout_in_minutes: 45
   source_file_dependencies:
@@ -26,6 +27,7 @@ steps:
   - pytest -v -s entrypoints/llm/test_struct_output_generate.py -k "xgrammar and not speculative_config6 and not speculative_config7 and not speculative_config8 and not speculative_config0"
 
 - label: Model Runner V2 Examples
+  device: h200_35gb
   key: model-runner-v2-examples
   timeout_in_minutes: 45
   working_dir: "/vllm-workspace/examples"
@@ -37,7 +39,7 @@ steps:
     - examples/generate/multimodal/
     - examples/features/
     - examples/pooling/embed/vision_embedding_offline.py
-    - examples/others/tensorize_vllm_model.py
+    - examples/features/tensorize_vllm_model.py
   commands:
     - set -x
     - export VLLM_USE_V2_MODEL_RUNNER=1
@@ -55,8 +57,8 @@ steps:
     - python3 pooling/embed/vision_embedding_offline.py --seed 0
     # for features demo
     - python3 features/automatic_prefix_caching/prefix_caching_offline.py
-    - python3 offline_inference/llm_engine_example.py
-    - python3 others/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 others/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
+    - python3 deployment/llm_engine_example.py
+    - python3 features/tensorize_vllm_model.py --model facebook/opt-125m serialize --serialized-directory /tmp/ --suffix v1 && python3 features/tensorize_vllm_model.py --model facebook/opt-125m deserialize --path-to-tensors /tmp/vllm/facebook/opt-125m/v1/model.tensors
     - python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 2048
     # https://github.com/vllm-project/vllm/pull/26682 uses slightly more memory in PyTorch 2.9+ causing this test to OOM in 1xL4 GPU
     - python3 features/speculative_decoding/spec_decode_offline.py --test --method eagle3 --num_spec_tokens 3 --dataset-name hf --dataset-path philschmid/mt-bench --num-prompts 80 --temp 0 --top-p 1.0 --top-k -1 --tp 1 --enable-chunked-prefill --max-model-len 1536
@@ -92,13 +94,16 @@ steps:
     - vllm/v1/worker/gpu_worker.py
     - tests/distributed/test_pipeline_parallel.py
     - tests/distributed/test_pp_cudagraph.py
+    - tests/v1/distributed/test_pp_dp_v2.py
   commands:
     - set -x
     - export VLLM_USE_V2_MODEL_RUNNER=1
     - pytest -v -s distributed/test_pipeline_parallel.py -k "not ray and not Jamba"
     - pytest -v -s distributed/test_pp_cudagraph.py -k "not ray"
+    - pytest -v -s v1/distributed/test_pp_dp_v2.py
 
 - label: Model Runner V2 Spec Decode
+  device: h200_35gb
   key: model-runner-v2-spec-decode
   timeout_in_minutes: 30
   working_dir: "/vllm-workspace/tests"
@@ -106,13 +111,12 @@ steps:
   - vllm/v1/worker/gpu/
   - vllm/v1/worker/gpu_worker.py
   - tests/v1/spec_decode/test_max_len.py
-  - tests/v1/spec_decode/test_probabilistic_rejection_sampler_utils.py
-  - tests/v1/spec_decode/test_synthetic_rejection_sampler_utils.py
+  - tests/v1/spec_decode/test_rejection_sampler_utils.py
   - tests/v1/e2e/spec_decode/test_spec_decode.py
   commands:
   - set -x
   - export VLLM_USE_V2_MODEL_RUNNER=1
   - pytest -v -s v1/spec_decode/test_max_len.py -k "eagle or mtp"
-  - pytest -v -s v1/spec_decode/test_probabilistic_rejection_sampler_utils.py
+  - pytest -v -s v1/spec_decode/test_rejection_sampler_utils.py
   - pytest -v -s v1/spec_decode/test_synthetic_rejection_sampler_utils.py
   - pytest -v -s v1/e2e/spec_decode/test_spec_decode.py -k "eagle or mtp"

.buildkite/test_areas/models_basic.yaml

@@ -5,6 +5,7 @@ steps:
 - label: Basic Models Tests (Initialization)
   key: basic-models-tests-initialization
   timeout_in_minutes: 45
+  device: h200_18gb
   torch_nightly: true
   source_file_dependencies:
   - vllm/
@@ -17,6 +18,7 @@ steps:
     torch_nightly: {}
 
 - label: Basic Models Tests (Extra Initialization) %N
+  device: h200_35gb
   key: basic-models-tests-extra-initialization
   timeout_in_minutes: 45
   source_file_dependencies:
@@ -33,6 +35,7 @@ steps:
     torch_nightly: {}
 
 - label: Basic Models Tests (Other)
+  device: h200_35gb
   key: basic-models-tests-other
   timeout_in_minutes: 45
   source_file_dependencies:
@@ -42,12 +45,6 @@ steps:
   - tests/models/test_registry.py
   commands:
     - pytest -v -s models/test_terratorch.py models/test_transformers.py models/test_registry.py
-  mirror:
-    amd:
-      device: mi325_1
-      depends_on:
-      - image-build-amd
-
 
 - label: Basic Models Test (Other CPU) # 5min
   key: basic-models-test-other-cpu
@@ -61,35 +58,3 @@ steps:
   device: cpu-small
   commands:
     - pytest -v -s models/test_utils.py models/test_vision.py
-
-- label: Transformers Nightly Models
-  key: transformers-nightly-models
-  working_dir: "/vllm-workspace/"
-  optional: true
-  soft_fail: true
-  commands:
-    - pip install --upgrade git+https://github.com/huggingface/transformers
-    - pytest -v -s tests/models/test_initialization.py
-    - pytest -v -s tests/models/test_transformers.py
-    - pytest -v -s tests/models/multimodal/processing/
-    - pytest -v -s tests/models/multimodal/test_mapping.py
-    - python3 examples/basic/offline_inference/chat.py
-    - python3 examples/generate/multimodal/vision_language_offline.py --model-type qwen2_5_vl
-    # Whisper needs spawn method to avoid deadlock
-    - VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/generate/multimodal/audio_language_offline.py --model-type whisper
-
-- label: Transformers Backward Compatibility Models Test
-  key: transformers-backward-compatibility-models-test
-  working_dir: "/vllm-workspace/"
-  optional: true
-  soft_fail: true
-  commands:
-    - pip install transformers==4.57.5
-    - pytest -v -s tests/models/test_initialization.py
-    - pytest -v -s tests/models/test_transformers.py
-    - pytest -v -s tests/models/multimodal/processing/
-    - pytest -v -s tests/models/multimodal/test_mapping.py
-    - python3 examples/basic/offline_inference/chat.py
-    - python3 examples/generate/multimodal/vision_language_offline.py --model-type qwen2_5_vl
-    # Whisper needs spawn method to avoid deadlock
-    - VLLM_WORKER_MULTIPROC_METHOD=spawn python3 examples/generate/multimodal/audio_language_offline.py --model-type whisper

.buildkite/test_areas/models_language.yaml

@@ -5,6 +5,7 @@ steps:
 - label: Language Models Tests (Standard)
   key: language-models-tests-standard
   timeout_in_minutes: 25
+  device: h200_18gb
   source_file_dependencies:
   - vllm/
   - tests/models/language
@@ -48,8 +49,18 @@ steps:
   parallelism: 2
   mirror:
     torch_nightly: {}
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 90
+      depends_on:
+      - image-build-amd
+      commands:
+      - uv pip install --system --no-build-isolation 'git+https://github.com/AndreasKaratzas/mamba@fix-rocm-7.0-warp-size-constexpr'
+      - 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
 
 - label: Language Models Test (Extended Generation) # 80min
+  device: h200_35gb
   key: language-models-test-extended-generation
   timeout_in_minutes: 110
   optional: true
@@ -62,15 +73,6 @@ steps:
     - 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 '(not core_model) and (not hybrid_model)'
-  mirror:
-    amd:
-      device: mi325_1
-      depends_on:
-      - image-build-amd
-      commands:
-      - uv pip install --system --no-build-isolation 'git+https://github.com/AndreasKaratzas/mamba@fix-rocm-7.0-warp-size-constexpr'
-      - 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 '(not core_model) and (not hybrid_model)'
 
 - label: Language Models Test (PPL)
   key: language-models-test-ppl
@@ -84,6 +86,7 @@ steps:
     - pytest -v -s models/language/generation_ppl_test
 
 - label: Language Models Test (Extended Pooling)  # 36min
+  device: h200_35gb
   key: language-models-test-extended-pooling
   timeout_in_minutes: 50
   optional: true
@@ -95,6 +98,7 @@ steps:
   mirror:
     amd:
       device: mi325_1
+      timeout_in_minutes: 100
       depends_on:
       - image-build-amd
 

.buildkite/test_areas/models_multimodal.yaml

@@ -38,6 +38,7 @@ steps:
       - image-build-amd
 
 - 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
   source_file_dependencies:
@@ -54,6 +55,7 @@ steps:
       - image-build-amd
 
 - label: "Multi-Modal Models (Standard) 4: other + whisper"
+  device: h200_35gb
   key: multi-modal-models-standard-4-other-whisper
   timeout_in_minutes: 45
   source_file_dependencies:
@@ -64,11 +66,6 @@ steps:
     - 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
     - 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
-  mirror:
-    amd:
-      device: mi325_1
-      depends_on:
-      - image-build-amd
 
 - label: Multi-Modal Processor (CPU)
   key: multi-modal-processor-cpu
@@ -97,6 +94,7 @@ steps:
     - 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
   working_dir: "/vllm-workspace/.buildkite/lm-eval-harness"
@@ -125,6 +123,7 @@ steps:
       - image-build-amd
 
 - label: Multi-Modal Models (Extended Generation 2)
+  device: h200_35gb
   key: multi-modal-models-extended-generation-2
   optional: true
   source_file_dependencies:
@@ -135,6 +134,7 @@ steps:
     - pytest -v -s models/multimodal/generation/test_common.py -m 'split(group=0) and not core_model'
 
 - label: Multi-Modal Models (Extended Generation 3)
+  device: h200_35gb
   key: multi-modal-models-extended-generation-3
   optional: true
   source_file_dependencies:
@@ -153,3 +153,12 @@ steps:
   - tests/models/multimodal/pooling
   commands:
     - pytest -v -s models/multimodal/pooling -m 'not core_model'
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 60
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - vllm/
+      - tests/models/multimodal/pooling

.buildkite/test_areas/plugins.yaml

@@ -37,6 +37,20 @@ steps:
   - pytest -v -s plugins_tests/test_scheduler_plugins.py
   - pip install -e ./plugins/vllm_add_dummy_model
   - pytest -v -s distributed/test_distributed_oot.py
-  - pytest -v -s entrypoints/openai/chat_completion/test_oot_registration.py # it needs a clean process
-  - pytest -v -s models/test_oot_registration.py # it needs a clean process
-  - pytest -v -s plugins/lora_resolvers # unit tests for in-tree lora resolver plugins
+  - pytest -v -s plugins_tests/test_oot_registration_online.py # it needs a clean process
+  - pytest -v -s plugins_tests/test_oot_registration_offline.py # it needs a clean process
+  - pytest -v -s plugins_tests/lora_resolvers # unit tests for in-tree lora resolver plugins
+
+
+- label: GGUF Plugin
+  key: gguf-plugin
+  device: h200_18gb
+  timeout_in_minutes: 30
+  soft_fail: true
+  optional: true
+  source_file_dependencies:
+  - vllm/model_executor/layers/quantization
+  - tests/plugins_tests/test_gguf_plugin.py
+  commands:
+    - pip install "vllm-gguf-plugin >= 0.0.2"
+    - pytest -v -s plugins_tests/gguf

.buildkite/test_areas/pytorch.yaml

@@ -3,10 +3,34 @@ depends_on:
   - image-build
 steps:
 - label: PyTorch Compilation Unit Tests
+  device: h200_35gb
   key: pytorch-compilation-unit-tests
   timeout_in_minutes: 10
   source_file_dependencies:
-    - vllm/
+    - 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:
   # Run unit tests defined directly under compile/,
@@ -24,7 +48,30 @@ steps:
   device: h100
   num_devices: 1
   source_file_dependencies:
-    - vllm/
+    - 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/h100/
   commands:
   - "find compile/h100/ -name 'test_*.py' -print0 | xargs -0 -n1 -I{} pytest -s -v '{}'"
@@ -33,7 +80,30 @@ steps:
   key: pytorch-compilation-passes-unit-tests
   timeout_in_minutes: 20
   source_file_dependencies:
-    - vllm/
+    - 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/passes
   commands:
   - pytest -s -v compile/passes --ignore compile/passes/distributed
@@ -42,7 +112,30 @@ steps:
   key: pytorch-fullgraph-smoke-test
   timeout_in_minutes: 35
   source_file_dependencies:
-  - vllm/
+  - 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:
   # Run smoke tests under fullgraph directory, except test_full_graph.py
@@ -56,7 +149,30 @@ steps:
   timeout_in_minutes: 30
   device: h200_18gb
   source_file_dependencies:
-  - vllm/
+  - 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:
     # fp8 kv scales not supported on sm89, tested on Blackwell instead

.buildkite/test_areas/quantization.yaml

@@ -21,11 +21,23 @@ steps:
   - uv pip install --system conch-triton-kernels
   - VLLM_TEST_FORCE_LOAD_FORMAT=auto pytest -v -s quantization/ --ignore quantization/test_blackwell_moe.py
 
+- label: Quantized Fusions
+  key: quantized-fusions
+  timeout_in_minutes: 30
+  source_file_dependencies:
+  - tests/fusion
+  - vllm/model_executor/layers/fusion
+  - vllm/model_executor/kernels/linear
+  - vllm/model_executor/layers/quantization/compressed_tensors
+  - vllm/model_executor/layers/quantization/modelopt.py
+  commands:
+    - pytest -v -s fusion/
+
 - label: Quantized MoE Test (B200)
   key: quantized-moe-test-b200
   timeout_in_minutes: 60
   working_dir: "/vllm-workspace/"
-  device: b200
+  device: b200-k8s
   source_file_dependencies:
   - tests/quantization/test_blackwell_moe.py
   - vllm/model_executor/models/deepseek_v2.py

.buildkite/test_areas/rust_frontend.yaml

@@ -0,0 +1,107 @@
+group: Rust Frontend E2E
+depends_on:
+  - image-build
+steps:
+- label: Rust Frontend OpenAI Coverage
+  timeout_in_minutes: 90
+  device: h200_18gb
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - rust/
+  - vllm/benchmarks/
+  - vllm/entrypoints/openai/
+  - vllm/entrypoints/serve/
+  - vllm/v1/sample/
+  - 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/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/v1/sample/test_logprobs_e2e.py
+  commands:
+  - 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
+  # - pytest -v -s entrypoints/openai/chat_completion/test_chat_logit_bias_validation.py -k "not invalid"
+
+  # - 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
+  - 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
+  device: h200_18gb
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - rust/
+  - 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/instrumentator/test_basic.py
+  - tests/entrypoints/serve/instrumentator/test_metrics.py
+  # - tests/entrypoints/serve/dev/test_sleep.py
+  commands:
+  - export VLLM_USE_RUST_FRONTEND=1
+  - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+  # - pytest -v -s entrypoints/serve/dev/rpc/test_collective_rpc.py
+  - 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"
+  - 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
+
+- label: Rust Frontend Core Correctness
+  timeout_in_minutes: 30
+  device: h200_18gb
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - rust/
+  - vllm/entrypoints/openai/
+  - tests/utils.py
+  - tests/entrypoints/openai/correctness/test_lmeval.py
+  commands:
+  - 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
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - rust/
+  - vllm/entrypoints/openai/
+  - vllm/tool_parsers/
+  - tests/utils.py
+  - tests/tool_use/
+  commands:
+  - 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
+  num_devices: 4
+  working_dir: "/vllm-workspace/tests"
+  source_file_dependencies:
+  - rust/
+  - vllm/distributed/
+  - vllm/engine/
+  - vllm/executor/
+  - vllm/v1/engine/
+  - vllm/v1/worker/
+  - tests/utils.py
+  - tests/v1/distributed/test_internal_lb_dp.py
+  commands:
+  - export VLLM_USE_RUST_FRONTEND=1
+  - export VLLM_WORKER_MULTIPROC_METHOD=spawn
+  - export NCCL_CUMEM_HOST_ENABLE=0
+  - TP_SIZE=1 DP_SIZE=4 pytest -v -s v1/distributed/test_internal_lb_dp.py -k "not 4 and not server_info"

.buildkite/test_areas/rust_frontend_cargo.yaml

@@ -0,0 +1,30 @@
+group: Rust Frontend Cargo
+depends_on: []
+steps:
+- label: Rust Frontend Cargo Style + Clippy
+  key: rust-frontend-cargo-style-clippy
+  depends_on: []
+  timeout_in_minutes: 30
+  device: cpu-medium
+  no_plugin: true
+  source_file_dependencies:
+  - rust/
+  - rust-toolchain.toml
+  - .buildkite/test_areas/rust_frontend_cargo.yaml
+  - .buildkite/scripts/run-rust-frontend-cargo-ci.sh
+  commands:
+  - .buildkite/scripts/run-rust-frontend-cargo-ci.sh style-clippy
+
+- label: Rust Frontend Cargo Tests
+  key: rust-frontend-cargo-tests
+  depends_on: []
+  timeout_in_minutes: 30
+  device: cpu-medium
+  no_plugin: true
+  source_file_dependencies:
+  - rust/
+  - rust-toolchain.toml
+  - .buildkite/test_areas/rust_frontend_cargo.yaml
+  - .buildkite/scripts/run-rust-frontend-cargo-ci.sh
+  commands:
+  - .buildkite/scripts/run-rust-frontend-cargo-ci.sh test

.buildkite/test_areas/samplers.yaml

@@ -3,6 +3,7 @@ depends_on:
   - image-build
 steps:
 - label: Samplers Test
+  device: h200_35gb
   key: samplers-test
   timeout_in_minutes: 75
   source_file_dependencies:
@@ -10,6 +11,7 @@ steps:
   - vllm/sampling_metadata.py
   - tests/samplers
   - tests/conftest.py
+  - vllm/entrypoints/generate/beam_search
   commands:
     # VLLM_USE_FLASHINFER_SAMPLER defaults to 1 now, so we need to pin both
     # values explicitly to still cover the PyTorch-native (Triton) path.
@@ -17,7 +19,7 @@ steps:
     - VLLM_USE_FLASHINFER_SAMPLER=1 pytest -v -s samplers
   mirror:
     amd:
-      device: mi325_1
+      device: mi250_1
       depends_on:
       - image-build-amd
       commands:

.buildkite/test_areas/spec_decode.yaml

@@ -16,7 +16,7 @@ steps:
 - label: Spec Decode Eagle Nightly B200
   key: spec-decode-eagle-nightly-b200
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   optional: true
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -32,15 +32,31 @@ steps:
   source_file_dependencies:
     - vllm/v1/spec_decode/
     - vllm/v1/worker/gpu/spec_decode/
+    - vllm/v1/attention/backends/
     - vllm/transformers_utils/configs/speculators/
     - tests/v1/e2e/spec_decode/
   commands:
     - pytest -v -s v1/e2e/spec_decode -k "speculators or mtp_correctness"
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 65
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - vllm/v1/spec_decode/
+      - vllm/v1/worker/gpu/spec_decode/
+      - vllm/model_executor/model_loader/
+      - vllm/v1/sample/
+      - vllm/model_executor/layers/
+      - vllm/transformers_utils/configs/speculators/
+      - tests/v1/e2e/spec_decode/
+      - vllm/platforms/rocm.py
 
 - label: Spec Decode Speculators + MTP Nightly B200
   key: spec-decode-speculators-mtp-nightly-b200
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   optional: true
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -60,6 +76,20 @@ steps:
     - tests/v1/e2e/spec_decode/
   commands:
     - pytest -v -s v1/e2e/spec_decode -k "ngram or suffix"
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 65
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - vllm/v1/spec_decode/
+      - vllm/v1/worker/gpu/spec_decode/
+      - vllm/model_executor/model_loader/
+      - vllm/v1/sample/
+      - vllm/model_executor/layers/
+      - tests/v1/e2e/spec_decode/
+      - vllm/platforms/rocm.py
 
 - label: Spec Decode Draft Model
   key: spec-decode-draft-model
@@ -71,11 +101,25 @@ steps:
     - tests/v1/e2e/spec_decode/
   commands:
     - pytest -v -s v1/e2e/spec_decode -k "draft_model or no_sync or batch_inference"
+  mirror:
+    amd:
+      device: mi325_1
+      timeout_in_minutes: 50
+      depends_on:
+      - image-build-amd
+      source_file_dependencies:
+      - vllm/v1/spec_decode/
+      - vllm/v1/worker/gpu/spec_decode/
+      - vllm/model_executor/model_loader/
+      - vllm/v1/sample/
+      - vllm/model_executor/layers/
+      - tests/v1/e2e/spec_decode/
+      - vllm/platforms/rocm.py
 
 - label: Spec Decode Draft Model Nightly B200
   key: spec-decode-draft-model-nightly-b200
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   optional: true
   source_file_dependencies:
     - vllm/v1/spec_decode/
@@ -84,23 +128,23 @@ steps:
   commands:
     - pytest -v -s v1/e2e/spec_decode -k "draft_model or no_sync or batch_inference"
 
-- label: DFlash Speculators Correctness
-  key: dflash-speculators-correctness
-  timeout_in_minutes: 30
+- label: Speculators Correctness
+  key: speculators-correctness
+  timeout_in_minutes: 60
   device: h100
   optional: true
   num_devices: 1
   source_file_dependencies:
     - vllm/v1/spec_decode/
     - vllm/model_executor/models/qwen3_dflash.py
-    - tests/v1/spec_decode/test_speculators_dflash.py
+    - tests/v1/spec_decode/test_speculators_correctness.py
   commands:
     - export VLLM_ALLOW_INSECURE_SERIALIZATION=1
-    - pytest -v -s v1/spec_decode/test_speculators_dflash.py -m slow_test
+    - pytest -v -s v1/spec_decode/test_speculators_correctness.py -m slow_test
 
 - label: Spec Decode MTP hybrid (B200)
   timeout_in_minutes: 30
-  device: b200
+  device: b200-k8s
   optional: true
   source_file_dependencies:
     - vllm/v1/spec_decode/

.dockerignore

@@ -2,6 +2,7 @@
 /build
 dist
 vllm/*.so
+vllm/vllm-rs
 
 # Byte-compiled / optimized / DLL files
 __pycache__/
@@ -31,3 +32,4 @@ share/python-wheels/
 .installed.cfg
 *.egg
 MANIFEST
+rust/target/

.github/CODEOWNERS

@@ -6,8 +6,8 @@
 /vllm/distributed/kv_transfer @NickLucche @ApostaC @orozery @xuechendi
 /vllm/lora @jeejeelee
 /vllm/model_executor/layers/attention @LucasWilkinson @MatthewBonanni
-/vllm/model_executor/layers/fused_moe @mgoin @pavanimajety
-/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth @yewentao256 @pavanimajety
+/vllm/model_executor/layers/fused_moe @mgoin @pavanimajety @zyongye
+/vllm/model_executor/layers/quantization @mgoin @robertgshaw2-redhat @tlrmchlsmth @yewentao256 @pavanimajety @zyongye
 /vllm/model_executor/layers/mamba @tdoublep @tomeras91
 /vllm/model_executor/layers/mamba/gdn_linear_attn.py @tdoublep @ZJY0516 @vadiklyutiy
 /vllm/model_executor/layers/rotary_embedding.py @vadiklyutiy
@@ -18,27 +18,40 @@
 /vllm/kernels/helion @ProExpertProg @zou3519
 /vllm/multimodal @DarkLight1337 @ywang96 @NickLucche @tjtanaa
 /vllm/vllm_flash_attn @LucasWilkinson @MatthewBonanni
-CMakeLists.txt @tlrmchlsmth @LucasWilkinson
+/CMakeLists.txt @tlrmchlsmth @LucasWilkinson @Harry-Chen
+/cmake @tlrmchlsmth @LucasWilkinson @Harry-Chen
 
 # Any change to the VllmConfig changes can have a large user-facing impact,
 # so spam a lot of people
-/vllm/config @WoosukKwon @youkaichao @robertgshaw2-redhat @mgoin @tlrmchlsmth @houseroad @hmellor @yewentao256 @ProExpertProg
+/vllm/config @WoosukKwon @youkaichao @robertgshaw2-redhat @mgoin @tlrmchlsmth @houseroad @yewentao256 @ProExpertProg
 /vllm/config/cache.py @heheda12345
 
+# Config utils
+/vllm/config/utils.py @hmellor
+/vllm/engine/arg_utils.py @hmellor
+/vllm/utils/argparse_utils.py
+
 # Entrypoints
 /vllm/entrypoints/anthropic @mgoin @DarkLight1337
 /vllm/entrypoints/cli @hmellor @mgoin @DarkLight1337 @russellb
 /vllm/entrypoints/mcp @heheda12345
 /vllm/entrypoints/openai @aarnphm @chaunceyjiang @DarkLight1337 @russellb
-/vllm/entrypoints/openai/realtime @njhill
-/vllm/entrypoints/openai/speech_to_text @NickLucche
+/vllm/entrypoints/speech_to_text/realtime @njhill
+/vllm/entrypoints/speech_to_text @NickLucche
 /vllm/entrypoints/pooling @noooop
-/vllm/entrypoints/sagemaker @DarkLight1337
+/vllm/entrypoints/serve/sagemaker @DarkLight1337
 /vllm/entrypoints/serve @njhill
 /vllm/entrypoints/*.py @njhill
 /vllm/entrypoints/chat_utils.py @DarkLight1337
+/vllm/entrypoints/offline_utils.py @DarkLight1337
 /vllm/entrypoints/llm.py @DarkLight1337
 
+# Rust Frontend
+/rust/ @BugenZhao @njhill
+/build_rust.sh @BugenZhao @njhill
+/rust-toolchain.toml @BugenZhao @njhill
+/.buildkite/test_areas/rust* @BugenZhao @njhill
+
 # Input/Output Processing
 /vllm/sampling_params.py @njhill @NickLucche
 /vllm/pooling_params.py @noooop @DarkLight1337
@@ -67,21 +80,27 @@ CMakeLists.txt @tlrmchlsmth @LucasWilkinson
 /vllm/v1/worker/kv_connector_model_runner_mixin.py @orozery @NickLucche
 
 # Model runner V2
-/vllm/v1/worker/gpu @WoosukKwon @njhill
+/vllm/v1/worker/gpu @WoosukKwon @njhill @yewentao256
 /vllm/v1/worker/gpu/kv_connector.py @orozery
 
+# CI & building
+/.buildkite @Harry-Chen @khluu
+/docker/Dockerfile @Harry-Chen @khluu
+/pyproject.toml @khluu
+/setup.py @khluu
+
 # Test ownership
-/.buildkite/lm-eval-harness @mgoin 
+/.buildkite/lm-eval-harness @mgoin
 /tests/distributed/test_multi_node_assignment.py @youkaichao
 /tests/distributed/test_pipeline_parallel.py @youkaichao
 /tests/distributed/test_same_node.py @youkaichao
-/tests/entrypoints @DarkLight1337 @robertgshaw2-redhat @aarnphm @NickLucche
-/tests/evals @mgoin @vadiklyutiy
-/tests/kernels @mgoin @tlrmchlsmth @WoosukKwon @yewentao256
+/tests/entrypoints @DarkLight1337 @robertgshaw2-redhat @aarnphm @NickLucche @AndreasKaratzas
+/tests/evals @mgoin @vadiklyutiy @AndreasKaratzas
+/tests/kernels @mgoin @tlrmchlsmth @WoosukKwon @yewentao256 @zyongye @AndreasKaratzas
 /tests/kernels/ir @ProExpertProg @tjtanaa
-/tests/models @DarkLight1337 @ywang96
+/tests/models @DarkLight1337 @ywang96 @AndreasKaratzas
 /tests/multimodal @DarkLight1337 @ywang96 @NickLucche
-/tests/quantization @mgoin @robertgshaw2-redhat @yewentao256 @pavanimajety
+/tests/quantization @mgoin @robertgshaw2-redhat @yewentao256 @pavanimajety @zyongye @AndreasKaratzas
 /tests/test_inputs.py @DarkLight1337 @ywang96
 /tests/entrypoints/llm/test_struct_output_generate.py @mgoin @russellb @aarnphm
 /tests/v1/structured_output @mgoin @russellb @aarnphm
@@ -147,6 +166,10 @@ mkdocs.yaml @hmellor
 # MTP-specific files
 /vllm/model_executor/models/deepseek_mtp.py @luccafong
 
+# DeepseekV4-specific files
+/vllm/models/deepseek_v4 @zyongye
+/vllm/model_executor/layers/sparse_attn_indexer.py @zyongye
+
 # Mistral-specific files
 /vllm/model_executor/models/mistral*.py @patrickvonplaten
 /vllm/model_executor/models/mixtral*.py @patrickvonplaten
@@ -161,21 +184,21 @@ mkdocs.yaml @hmellor
 /vllm/model_executor/layers/fla @ZJY0516 @vadiklyutiy
 
 # ROCm related: specify owner with write access to notify AMD folks for careful code review
-/vllm/**/*rocm* @tjtanaa
-/docker/Dockerfile.rocm* @gshtras @tjtanaa
-/vllm/v1/attention/backends/rocm*.py @gshtras @tjtanaa
-/vllm/v1/attention/backends/mla/rocm*.py @gshtras @tjtanaa
-/vllm/v1/attention/ops/rocm*.py @gshtras @tjtanaa
-/vllm/model_executor/layers/fused_moe/rocm*.py @gshtras @tjtanaa
-/csrc/rocm @gshtras @tjtanaa
-/requirements/*rocm* @tjtanaa
-/tests/**/*rocm* @tjtanaa
+/vllm/**/*rocm* @tjtanaa @dllehr-amd
+/docker/Dockerfile.rocm* @tjtanaa @dllehr-amd @AndreasKaratzas
+/vllm/v1/attention/backends/rocm*.py @tjtanaa @dllehr-amd
+/vllm/v1/attention/backends/mla/rocm*.py @tjtanaa @dllehr-amd
+/vllm/v1/attention/ops/rocm*.py @tjtanaa @dllehr-amd
+/vllm/model_executor/layers/fused_moe/rocm*.py @tjtanaa @dllehr-amd
+/csrc/rocm @tjtanaa @dllehr-amd
+/requirements/*rocm* @tjtanaa @AndreasKaratzas
+/tests/**/*rocm* @tjtanaa @AndreasKaratzas
 /docs/**/*rocm* @tjtanaa
 /vllm/**/*quark* @tjtanaa
-/tests/**/*quark* @tjtanaa
+/tests/**/*quark* @tjtanaa @AndreasKaratzas
 /docs/**/*quark* @tjtanaa
-/vllm/**/*aiter* @tjtanaa
-/tests/**/*aiter* @tjtanaa
+/vllm/**/*aiter* @tjtanaa @AndreasKaratzas
+/tests/**/*aiter* @tjtanaa @AndreasKaratzas
 
 # TPU
 /vllm/v1/worker/tpu* @NickLucche

.github/dependabot.yml

@@ -21,7 +21,6 @@ updates:
       - dependency-name: "torchvision"
       - dependency-name: "xformers"
       - dependency-name: "lm-format-enforcer"
-      - dependency-name: "gguf"
       - dependency-name: "compressed-tensors"
       - dependency-name: "ray[cgraph]" # Ray Compiled Graph
       - dependency-name: "lm-eval"

.github/mergify.yml

@@ -21,6 +21,9 @@ pull_request_rules:
     - check-failure=pre-commit
     - -closed
     - -draft
+    - or:
+      - label=ready
+      - label=verified
   actions:
     comment:
       message: |
@@ -36,18 +39,6 @@ pull_request_rules:
 
         For future commits, `pre-commit` will run automatically on changed files before each commit.
 
-        > [!TIP]
-        > <details>
-        > <summary>Is <code>mypy</code> failing?</summary>
-        > <br/>
-        > <code>mypy</code> is run differently in CI. If the failure is related to this check, please use the following command to run it locally:
-        >
-        > ```bash
-        > # For mypy (substitute "3.10" with the failing version if needed)
-        > pre-commit run --hook-stage manual mypy-3.10
-        > ```
-        > </details>
-
 - name: comment-dco-failure
   description: Comment on PR when DCO check fails
   conditions:
@@ -103,6 +94,19 @@ pull_request_rules:
       add:
         - frontend
 
+- name: label-rust
+  description: Automatically apply rust label
+  conditions:
+    - label != stale
+    - or:
+      - files~=(?i)rust
+      - title~=(?i)rust
+      - title~=(?i)vllm-rs
+  actions:
+    label:
+      add:
+        - rust
+
 - name: label-llama
   description: Automatically apply llama label
   conditions:
@@ -140,12 +144,12 @@ pull_request_rules:
     - label != stale
     - or:
       - files~=^examples/.*mistral.*\.py
-      - files~=^tests/.*mistral.*\.py
-      - files~=^vllm/model_executor/models/.*mistral.*\.py
+      - files~=^tests/.*(?:mistral|voxtral|mixtral|pixtral).*\.py
+      - files~=^vllm/model_executor/models/.*(?:mistral|voxtral|mixtral|pixtral).*\.py
       - files~=^vllm/reasoning/.*mistral.*\.py
       - files~=^vllm/tool_parsers/.*mistral.*\.py
-      - files~=^vllm/transformers_utils/.*mistral.*\.py
-      - title~=(?i)Mistral
+      - files~=^vllm/transformers_utils/.*(?:mistral|voxtral|pixtral).*\.py
+      - title~=(?i)(?:mistral|ministral|voxtral|mixtral|pixtral)
   actions:
     label:
       add:
@@ -477,9 +481,7 @@ pull_request_rules:
   conditions:
     - label != stale
     - or:
-      - files~=^examples/online_serving/disaggregated[^/]*/.*
-      - files~=^examples/offline_inference/disaggregated[^/]*/.*
-      - files~=^examples/others/lmcache/
+      - files~=^examples/disaggregated/
       - files~=^tests/v1/kv_connector/
       - files~=^vllm/distributed/kv_transfer/
       - title~=(?i)\bP/?D\b

.github/workflows/add_label_automerge.yml

@@ -10,7 +10,7 @@ jobs:
         runs-on: ubuntu-latest
         steps:
             -   name: Add label
-                uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
+                uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
                 with:
                     script: |
                         github.rest.issues.addLabels({

.github/workflows/issue_autolabel.yml

@@ -14,7 +14,7 @@ jobs:
     steps:
       - name: Label issues based on keywords
         id: label-step
-        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd  # v8.0.0
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3  # v9.0.0
         with:
           script: |
             // Configuration: Add new labels and keywords here
@@ -315,7 +315,7 @@ jobs:
 
       - name: CC users for labeled issues
         if: steps.label-step.outputs.labels_added != '[]'
-        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd  # v8.0.0
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3  # v9.0.0
         with:
           script: |
             // Configuration: Map labels to GitHub users to CC
@@ -392,7 +392,7 @@ jobs:
 
       - name: Request missing ROCm info from issue author
         if: contains(steps.label-step.outputs.labels_added, 'rocm') && contains(toJSON(github.event.issue.labels.*.name), 'bug')
-        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd  # v8.0.0
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3  # v9.0.0
         with:
           script: |
             const body = (context.payload.issue.body || '').toLowerCase();

.github/workflows/new_pr_bot.yml

@@ -12,7 +12,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Update PR description
-        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
         with:
           script: |
             const { owner, repo } = context.repo;
@@ -55,7 +55,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - name: Post welcome comment for first-time contributors
-        uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
+        uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
         with:
           script: |
             const { owner, repo } = context.repo;

.github/workflows/pre-commit.yml

@@ -20,7 +20,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
     - name: Check PR label and author merge count
-      uses: actions/github-script@ed597411d8f924073f98dfc5c65a23a2325f34cd # v8.0.0
+      uses: actions/github-script@3a2844b7e9c422d3c10d287c895573f7108da1b3 # v9.0.0
       with:
         script: |
           const { data: pr } = await github.rest.pulls.get({

.github/workflows/scripts/build.sh

@@ -9,12 +9,18 @@ PATH=${cuda_home}/bin:$PATH
 LD_LIBRARY_PATH=${cuda_home}/lib64:$LD_LIBRARY_PATH
 
 # Install requirements
+if [ "$(echo "$2" | cut -d. -f1)" = "12" ]; then
+    sed -i 's/^nvidia-cutlass-dsl\[cu13\]>=/nvidia-cutlass-dsl>=/' requirements/cuda.txt
+fi
 $python_executable -m pip install -r requirements/build/cuda.txt -r requirements/cuda.txt
 
 # Limit the number of parallel jobs to avoid OOM
 export MAX_JOBS=1
 # Make sure release wheels are built for the following architectures
-export TORCH_CUDA_ARCH_LIST="7.5 8.0 8.6 8.9 9.0 10.0 12.0+PTX"
+# Do not add +PTX here: vLLM filters torch's top-level PTX flag when it
+# converts global gencode flags into per-kernel arch lists. If a specific
+# kernel needs PTX, add +PTX to that kernel's CMake arch list instead.
+export TORCH_CUDA_ARCH_LIST="7.5 8.0 8.6 8.9 9.0 10.0 12.0"
 
 bash tools/check_repo.sh
 

.github/workflows/stale.yml

@@ -15,7 +15,7 @@ jobs:
       actions: write
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/stale@997185467fa4f803885201cee163a9f38240193d # v10.1.1
+      - uses: actions/stale@eb5cf3af3ac0a1aa4c9c45633dd1ae542a27a899 # v10.3.0
         with:
           # Increasing this value ensures that changes to this workflow
           # propagate to all issues and PRs in days rather than months

.gitignore

@@ -15,6 +15,9 @@ vllm/third_party/flashmla/flash_mla_interface.py
 # DeepGEMM vendored package built from source
 vllm/third_party/deep_gemm/
 
+# fmha_sm100 vendored package built from source
+vllm/third_party/fmha_sm100/
+
 # triton jit
 .triton
 
@@ -26,6 +29,9 @@ __pycache__/
 # C extensions
 *.so
 
+# Rust binaries
+vllm/vllm-rs
+
 # Distribution / packaging
 .Python
 build/
@@ -230,7 +236,7 @@ actionlint
 shellcheck*/
 
 # Ignore moe/marlin_moe gen code
-csrc/moe/marlin_moe_wna16/kernel_*
+csrc/libtorch_stable/moe/marlin_moe_wna16/kernel_*
 
 # Ignore ep_kernels_workspace folder
 ep_kernels_workspace/

.pre-commit-config.yaml

@@ -21,7 +21,7 @@ repos:
   rev: v21.1.2
   hooks:
   - id: clang-format
-    exclude: 'csrc/(moe/topk_softmax_kernels.cu|quantization/gguf/(ggml-common.h|dequantize.cuh|vecdotq.cuh|mmq.cuh|mmvq.cuh))|vllm/third_party/.*'
+    exclude: 'csrc/libtorch_stable/moe/topk_softmax_kernels.cu|vllm/third_party/.*'
     types_or: [c++, cuda]
     args: [--style=file, --verbose]
 - repo: https://github.com/DavidAnson/markdownlint-cli2
@@ -131,6 +131,16 @@ repos:
         --python-version, "3.12",
       ]
       files: ^requirements/(common|xpu|test/xpu)\.(in|txt)$
+    - id: pip-compile
+      alias: pip-compile-docs
+      name: pip-compile-docs
+      args: [
+        requirements/docs.in,
+        -o, requirements/docs.txt,
+        --python-platform, x86_64-manylinux_2_28,
+        --python-version, "3.12",
+      ]
+      files: ^requirements/docs\.(in|txt)$
 - repo: local
   hooks:
   - id: format-torch-nightly-test
@@ -138,33 +148,27 @@ repos:
     language: python
     entry: python tools/pre_commit/generate_nightly_torch_test.py
     files: ^requirements/test/cuda\.(in|txt)$
-  - id: mypy-local
-    name: Run mypy locally for lowest supported Python version
-    entry: python tools/pre_commit/mypy.py 0 "3.10"
-    stages: [pre-commit] # Don't run in CI
+  - id: mypy-3.10 # TODO: Use https://github.com/pre-commit/mirrors-mypy when mypy setup is less awkward
+    name: Run mypy for Python 3.10
+    entry: python tools/pre_commit/mypy.py "3.10"
     <<: &mypy_common
       language: python
       types_or: [python, pyi]
       require_serial: true
-      additional_dependencies: ["mypy[faster-cache]==1.19.1", regex, types-cachetools, types-setuptools, types-PyYAML, types-requests, types-torch, pydantic]
-  - id: mypy-3.10 # TODO: Use https://github.com/pre-commit/mirrors-mypy when mypy setup is less awkward
-    name: Run mypy for Python 3.10
-    entry: python tools/pre_commit/mypy.py 1 "3.10"
-    <<: *mypy_common
-    stages: [manual] # Only run in CI
+      additional_dependencies: ["mypy==1.20.2", regex, types-cachetools, types-setuptools, types-PyYAML, types-requests, types-torch, pydantic]
   - id: mypy-3.11 # TODO: Use https://github.com/pre-commit/mirrors-mypy when mypy setup is less awkward
     name: Run mypy for Python 3.11
-    entry: python tools/pre_commit/mypy.py 1 "3.11"
+    entry: python tools/pre_commit/mypy.py "3.11"
     <<: *mypy_common
     stages: [manual] # Only run in CI
   - id: mypy-3.12 # TODO: Use https://github.com/pre-commit/mirrors-mypy when mypy setup is less awkward
     name: Run mypy for Python 3.12
-    entry: python tools/pre_commit/mypy.py 1 "3.12"
+    entry: python tools/pre_commit/mypy.py "3.12"
     <<: *mypy_common
     stages: [manual] # Only run in CI
   - id: mypy-3.13 # TODO: Use https://github.com/pre-commit/mirrors-mypy when mypy setup is less awkward
     name: Run mypy for Python 3.13
-    entry: python tools/pre_commit/mypy.py 1 "3.13"
+    entry: python tools/pre_commit/mypy.py "3.13"
     <<: *mypy_common
     stages: [manual] # Only run in CI
   - id: shellcheck
@@ -212,6 +216,12 @@ repos:
     name: Update Dockerfile dependency graph
     entry: tools/pre_commit/update-dockerfile-graph.sh
     language: script
+  - id: test-nonroot-entrypoint
+    name: Test non-root entrypoint wrapper
+    entry: bash docker/entrypoints/test_vllm_nonroot_entrypoint.sh
+    language: system
+    pass_filenames: false
+    files: ^docker/entrypoints/(vllm-nonroot-entrypoint|test_vllm_nonroot_entrypoint)\.sh$
   - id: check-forbidden-imports
     name: Check for forbidden imports
     entry: python tools/pre_commit/check_forbidden_imports.py
@@ -246,6 +256,32 @@ repos:
     entry: python tools/pre_commit/check_boolean_context_manager.py
     language: python
     types: [python]
+  # Rust hooks. These shell out to `cargo`; tools/pre_commit/rust-check.sh
+  # skips with a warning when cargo is not installed.
+  - id: rust-cargo-autoinherit
+    name: Rust - Normalize Cargo manifests with autoinherit
+    entry: tools/pre_commit/rust-check.sh autoinherit --prefer-simple-dotted
+    language: script
+    pass_filenames: false
+    require_serial: true
+    stages: [pre-commit] # Only run locally as Buildkite will cover this
+    files: ^rust/(Cargo\.toml|src/.*/Cargo\.toml)$
+  - id: rust-cargo-sort
+    name: Rust - Sort Cargo manifest sections
+    entry: tools/pre_commit/rust-check.sh sort --workspace
+    language: script
+    pass_filenames: false
+    require_serial: true
+    stages: [pre-commit] # Only run locally as Buildkite will cover this
+    files: ^rust/(Cargo\.toml|src/.*/Cargo\.toml)$
+  - id: rust-cargo-fmt
+    name: Rust - Format code
+    entry: tools/pre_commit/rust-check.sh fmt
+    language: script
+    pass_filenames: false
+    require_serial: true
+    stages: [pre-commit] # Only run locally as Buildkite will cover this
+    files: ^rust/.*(\.rs|Cargo\.toml|rustfmt\.toml)$
   # Keep `suggestion` last
   - id: suggestion
     name: Suggestion

.readthedocs.yaml

@@ -9,8 +9,8 @@ build:
     python: "3.12"
   jobs:
     post_checkout:
-      # - bash docs/maybe_skip_pr_build.sh
       - git fetch origin main --unshallow --no-tags --filter=blob:none || true
+      - bash docs/pre_run_check.sh
     pre_create_environment:
       - pip install uv
     create_environment:

AGENTS.md

@@ -98,7 +98,31 @@ pre-commit run --all-files
 pre-commit run ruff-check --all-files
 
 # Run mypy as it is in CI:
-pre-commit run mypy-3.10 --all-files --hook-stage manual
+pre-commit run mypy-3.12 --all-files --hook-stage manual
+```
+
+The line length limit for Python code is 88 characters. If you are not sure, use pre-commit to check.
+
+Use [Google-style docstrings](https://google.github.io/styleguide/pyguide.html#38-comments-and-docstrings) (`Args:`/`Returns:`/`Raises:` sections), not reStructuredText/Sphinx fields (`:param:`, `:return:`, `:rtype:`).
+
+### 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.
+- Assume the reader is familiar with vLLM.
+
+### Diagnosing CI failures
+
+Buildkite logs are public; no login needed. Details: [docs/contributing/ci/failures.md](docs/contributing/ci/failures.md).
+
+```bash
+# All failed-job logs for a PR's latest build (current branch's PR if omitted):
+.buildkite/scripts/ci-fetch-log.sh --pr <PR>
+# Any Buildkite build or job URL also works:
+.buildkite/scripts/ci-fetch-log.sh "<buildkite_url>"
 ```
 
 ### Commit messages

MANIFEST.in

@@ -4,6 +4,7 @@ include requirements/cuda.txt
 include requirements/rocm.txt
 include requirements/cpu.txt
 include CMakeLists.txt
+include tools/build_rust.py
 
 recursive-include cmake *
 recursive-include csrc *

SECURITY.md

@@ -34,6 +34,15 @@ Vulnerabilities that cause denial of service or partial disruption, but do not a
 
 Minor issues such as informational disclosures, logging errors, non-exploitable flaws, or weaknesses that require local or high-privilege access and offer negligible impact. Examples include side channel attacks or hash collisions. These issues often have CVSS scores less than 4.0
 
+## Fix disclosure policy
+
+When a security report is accepted, the fix process depends on the severity:
+
+* **CRITICAL and HIGH severity**: Fixes are developed in a private security fork and coordinated with the prenotification group before public disclosure.
+* **MODERATE and LOW severity**: Fixes are developed and submitted as public pull requests. These issues do not require embargo since they do not enable arbitrary code execution or significant data breach, and public visibility accelerates community review and adoption of the fix.
+
+The vulnerability management team reserves the right to adjust the disclosure approach on a case-by-case basis, taking into account factors such as active exploitation, unusual attack surface, or coordination requirements with downstream vendors.
+
 ## Prenotification policy
 
 For certain security issues of CRITICAL, HIGH, or MODERATE severity level, we may prenotify certain organizations or vendors that ship vLLM. The purpose of this prenotification is to allow for a coordinated release of fixes for severe issues.

benchmarks/attention_benchmarks/README.md

@@ -108,7 +108,6 @@ python benchmark.py \
     --backends flash triton flashinfer \
     --batch-specs "q2k" "8q1s1k" "2q2k_32q1s1k" \
     --num-layers 10 \
-    --repeats 5 \
     --output-csv results.csv
 ```
 
@@ -164,14 +163,17 @@ python benchmark.py \
 # Model configuration
 --num-layers N                      # Number of layers
 --head-dim N                        # Head dimension
+--v-head-dim N                      # Value head dimension (defaults to --head-dim)
 --num-q-heads N                     # Query heads
 --num-kv-heads N                    # KV heads
 --block-size N                      # Block size
+--kv-lora-rank N                    # MLA KV LoRA rank
+--qk-nope-head-dim N                # MLA non-RoPE QK head dim
+--qk-rope-head-dim N                # MLA RoPE QK head dim
 
 # Benchmark settings
 --device DEVICE                     # Device (default: cuda:0)
---repeats N                         # Repetitions
---warmup-iters N                    # Warmup iterations
+--warmup-ms N                       # Warmup window in ms for triton do_bench
 --profile-memory                    # Profile memory usage
 
 # Parameter sweeps
@@ -211,8 +213,6 @@ config = BenchmarkConfig(
     num_kv_heads=1,
     block_size=128,
     device="cuda:0",
-    repeats=5,
-    warmup_iters=3,
 )
 
 # CUTLASS MLA with specific num_kv_splits
@@ -253,14 +253,10 @@ formatter.save_json(results, "output.json")
 
 ## Tips
 
-**1. Warmup matters** - Use `--warmup-iters 10` for stable results
+**1. Save results** - Always use `--output-csv` or `--output-json`
 
-**2. Multiple repeats** - Use `--repeats 20` for low variance
+**2. Test incrementally** - Start with `--num-layers 1`
 
-**3. Save results** - Always use `--output-csv` or `--output-json`
+**3. Extended grammar** - Leverage spec decode, chunked prefill patterns
 
-**4. Test incrementally** - Start with `--num-layers 1 --repeats 1`
-
-**5. Extended grammar** - Leverage spec decode, chunked prefill patterns
-
-**6. Parameter sweeps** - Use `--sweep-param` and `--sweep-values` to find optimal values
+**4. Parameter sweeps** - Use `--sweep-param` and `--sweep-values` to find optimal values

benchmarks/attention_benchmarks/benchmark.py

@@ -26,6 +26,9 @@ Examples:
 """
 
 import argparse
+import os
+import shutil
+import subprocess
 import sys
 from dataclasses import replace
 from pathlib import Path
@@ -83,13 +86,15 @@ def run_benchmark(config: BenchmarkConfig, **kwargs) -> BenchmarkResult:
         else:
             return run_standard_attention_benchmark(config)
     except Exception as e:
+        error_msg = str(e) or repr(e)
         return 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),
+            error=error_msg,
         )
 
 
@@ -115,9 +120,12 @@ def run_model_parameter_sweep(
     """
     all_results = []
 
-    console.print(
-        f"[yellow]Model sweep mode: testing {sweep.param_name} = {sweep.values}[/]"
+    sweep_desc = (
+        f"{sweep.param_name} = {sweep.values}"
+        if sweep.param_name
+        else f"{len(sweep.values)} configurations"
     )
+    console.print(f"[yellow]Model sweep mode: testing {sweep_desc}[/]")
 
     total = len(backends) * len(batch_specs) * len(sweep.values)
 
@@ -125,9 +133,9 @@ def run_model_parameter_sweep(
         for backend in backends:
             for spec in batch_specs:
                 for value in sweep.values:
-                    # Create config with modified model parameter
+                    # Create config with modified model parameter(s)
                     config_args = base_config_args.copy()
-                    config_args[sweep.param_name] = value
+                    sweep.apply(config_args, value)
 
                     # Create config with original backend for running
                     clean_config = BenchmarkConfig(
@@ -144,13 +152,21 @@ def run_model_parameter_sweep(
                     all_results.append(result)
 
                     if not result.success:
+                        err_label = (
+                            f"{sweep.param_name}={value}"
+                            if sweep.param_name
+                            else f"{value}"
+                        )
                         console.print(
-                            f"[red]Error {backend} {spec} {sweep.param_name}="
-                            f"{value}: {result.error}[/]"
+                            f"[red]Error {backend} {spec} {err_label}"
+                            f": {result.error}[/]"
                         )
 
                     pbar.update(1)
 
+    if base_config_args.get("ncu_profile"):
+        return all_results
+
     # Display sweep results - create separate table for each parameter value
     console.print("\n[bold green]Model Parameter Sweep Results:[/]")
     formatter = ResultsFormatter(console)
@@ -184,7 +200,10 @@ def run_model_parameter_sweep(
     )
 
     for param_value in sorted_param_values:
-        console.print(f"\n[bold cyan]{sweep.param_name} = {param_value}[/]")
+        label = (
+            f"{sweep.param_name} = {param_value}" if sweep.param_name else param_value
+        )
+        console.print(f"\n[bold cyan]{label}[/]")
         param_results = by_param_value[param_value]
 
         # Create modified results with original backend names
@@ -200,8 +219,9 @@ def run_model_parameter_sweep(
         formatter.print_table(modified_results, backends, compare_to_fastest=True)
 
     # Show optimal backend for each (param_value, batch_spec) combination
+    sweep_name = sweep.param_name or "config"
     console.print(
-        f"\n[bold cyan]Optimal backend for each ({sweep.param_name}, batch_spec):[/]"
+        f"\n[bold cyan]Optimal backend for each ({sweep_name}, batch_spec):[/]"
     )
 
     # Group by (param_value, batch_spec)
@@ -236,7 +256,10 @@ def run_model_parameter_sweep(
     for param_value, spec in sorted_keys:
         # Print header when param value changes
         if param_value != current_param_value:
-            console.print(f"\n  [bold]{sweep.param_name}={param_value}:[/]")
+            header = (
+                f"{sweep.param_name}={param_value}" if sweep.param_name else param_value
+            )
+            console.print(f"\n  [bold]{header}:[/]")
             current_param_value = param_value
 
         results = by_param_and_spec[(param_value, spec)]
@@ -322,6 +345,9 @@ def run_parameter_sweep(
 
                     pbar.update(1)
 
+    if base_config_args.get("ncu_profile"):
+        return all_results
+
     # Display sweep results
     console.print("\n[bold green]Sweep Results:[/]")
     backend_labels = [sweep.get_label(b, v) for b in backends for v in sweep_values]
@@ -474,11 +500,35 @@ def main():
     parser.add_argument("--num-q-heads", type=int, default=32, help="Query heads")
     parser.add_argument("--num-kv-heads", type=int, default=8, help="KV heads")
     parser.add_argument("--block-size", type=int, default=16, help="Block size")
+    parser.add_argument(
+        "--v-head-dim",
+        type=int,
+        default=None,
+        help="Value head dimension (defaults to --head-dim if unset)",
+    )
+
+    # MLA-specific model dimensions
+    parser.add_argument(
+        "--kv-lora-rank", type=int, default=None, help="MLA KV LoRA rank"
+    )
+    parser.add_argument(
+        "--qk-nope-head-dim", type=int, default=None, help="MLA non-RoPE QK head dim"
+    )
+    parser.add_argument(
+        "--qk-rope-head-dim", type=int, default=None, help="MLA RoPE QK head dim"
+    )
 
     # Benchmark settings
     parser.add_argument("--device", default="cuda:0", help="Device")
-    parser.add_argument("--repeats", type=int, default=1, help="Repetitions")
-    parser.add_argument("--warmup-iters", type=int, default=3, help="Warmup iterations")
+    parser.add_argument(
+        "--warmup-ms",
+        type=int,
+        default=None,
+        help=(
+            "Warmup window in ms for triton's do_bench (default: triton's own). "
+            "Has no effect with CUDA graphs; pass --no-cuda-graphs to use it."
+        ),
+    )
     parser.add_argument("--profile-memory", action="store_true", help="Profile memory")
     parser.add_argument(
         "--kv-cache-dtype",
@@ -491,10 +541,33 @@ def main():
         action=argparse.BooleanOptionalAction,
         default=True,
         help=(
-            "Launch kernels with CUDA graphs to eliminate CPU overhead"
-            "in measurements (default: True)"
+            "Use triton do_bench_cudagraph (True) or do_bench (False) "
+            "for timing. CUDA graphs eliminate CPU launch overhead "
+            "(default: True)"
         ),
     )
+    parser.add_argument(
+        "--num-splits",
+        type=int,
+        default=None,
+        help="FlashAttention split-K factor (0=auto heuristic, 1=disabled, >1=force N)",
+    )
+    parser.add_argument(
+        "--ncu-profile",
+        action="store_true",
+        default=False,
+        help=(
+            "Enable Nsight Compute profiling mode. Automatically wraps the "
+            "script with ncu, capturing a profile with source correlation. "
+            "Use --ncu-output to set the output file name."
+        ),
+    )
+    parser.add_argument(
+        "--ncu-output",
+        type=str,
+        default="profile",
+        help="Output file name for ncu profile (default: 'profile').",
+    )
 
     # Parameter sweep (use YAML config for advanced sweeps)
     parser.add_argument(
@@ -576,23 +649,28 @@ def main():
             model = yaml_config["model"]
             args.num_layers = model.get("num_layers", args.num_layers)
             args.head_dim = model.get("head_dim", args.head_dim)
+            args.v_head_dim = model.get("v_head_dim", args.v_head_dim)
             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)
+            # 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)
+            args.qk_rope_head_dim = model.get("qk_rope_head_dim", args.qk_rope_head_dim)
 
         # Benchmark settings (top-level keys)
         if "device" in yaml_config:
             args.device = yaml_config["device"]
-        if "repeats" in yaml_config:
-            args.repeats = yaml_config["repeats"]
-        if "warmup_iters" in yaml_config:
-            args.warmup_iters = yaml_config["warmup_iters"]
+        if "warmup_ms" in yaml_config:
+            args.warmup_ms = yaml_config["warmup_ms"]
         if "profile_memory" in yaml_config:
             args.profile_memory = yaml_config["profile_memory"]
         if "kv_cache_dtype" in yaml_config:
             args.kv_cache_dtype = yaml_config["kv_cache_dtype"]
         if "cuda_graphs" in yaml_config:
             args.cuda_graphs = yaml_config["cuda_graphs"]
+        if "ncu_profile" in yaml_config:
+            args.ncu_profile = yaml_config["ncu_profile"]
 
         # Parameter sweep configuration
         if "parameter_sweep" in yaml_config:
@@ -612,7 +690,7 @@ def main():
         if "model_parameter_sweep" in yaml_config:
             sweep_config = yaml_config["model_parameter_sweep"]
             args.model_parameter_sweep = ModelParameterSweep(
-                param_name=sweep_config["param_name"],
+                param_name=sweep_config.get("param_name"),
                 values=sweep_config["values"],
                 label_format=sweep_config.get(
                     "label_format", "{backend}_{param_name}_{value}"
@@ -631,6 +709,32 @@ def main():
 
         console.print()
 
+    # Re-exec under ncu if --ncu-profile and not already inside ncu. This runs
+    # after YAML processing so ncu_profile set via config file is honored.
+    if args.ncu_profile and "_NCU_INNER" not in os.environ:
+        ncu = shutil.which("ncu")
+        if ncu is None:
+            print("Error: 'ncu' not found in PATH", file=sys.stderr)
+            sys.exit(1)
+        cmd = [
+            ncu,
+            "--profile-from-start",
+            "off",
+            "--set",
+            "full",
+            "--import-source",
+            "yes",
+            "-o",
+            args.ncu_output,
+            sys.executable,
+            *sys.argv,
+        ]
+        env = os.environ.copy()
+        env["CUTE_DSL_LINEINFO"] = "1"
+        env["_NCU_INNER"] = "1"
+        print(f"Launching: {' '.join(cmd)}")
+        sys.exit(subprocess.call(cmd, env=env))
+
     # Handle CLI-based parameter sweep (if not from YAML)
     if (
         (not hasattr(args, "parameter_sweep") or args.parameter_sweep is None)
@@ -655,6 +759,18 @@ def main():
     console.print(f"Batch specs: {', '.join(args.batch_specs)}")
     console.print(f"KV cache dtype: {args.kv_cache_dtype}")
     console.print(f"CUDA graphs: {args.cuda_graphs}")
+    if args.warmup_ms is not None and args.cuda_graphs:
+        console.print(
+            "[yellow]Warning: --warmup-ms is ignored with CUDA graphs "
+            "(do_bench_cudagraph warms up internally). Pass --no-cuda-graphs "
+            "to use it.[/]"
+        )
+    if args.num_splits == 0 and args.cuda_graphs:
+        console.print(
+            "[yellow]Warning: --num-splits 0 (FA3 heuristic) is not CUDA-graph "
+            "compatible and may fail or fall back. Pass --no-cuda-graphs or use "
+            "--num-splits >=1.[/]"
+        )
     console.print()
 
     init_workspace_manager(args.device)
@@ -662,6 +778,15 @@ def main():
     # Run benchmarks
     all_results = []
 
+    # Under ncu profiling the kernels run only to be captured by the profiler;
+    # timings are placeholder zeros, so the result tables and saved metrics are
+    # skipped. The Nsight Compute report (--ncu-output) holds the real data.
+    if args.ncu_profile:
+        console.print(
+            "[dim]ncu profiling enabled: result tables and saved metrics are "
+            "skipped (timings are placeholder zeros).[/]"
+        )
+
     # Handle special mode: decode_vs_prefill comparison
     if hasattr(args, "mode") and args.mode == "decode_vs_prefill":
         console.print("[yellow]Mode: Decode vs Prefill pipeline comparison[/]")
@@ -708,11 +833,11 @@ 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,
+                        ncu_profile=args.ncu_profile,
+                        warmup_ms=args.warmup_ms,
                     )
 
                     # Add decode pipeline config
@@ -749,6 +874,7 @@ def main():
                         result = BenchmarkResult(
                             config=config,
                             mean_time=timing["mean"],
+                            median_time=timing.get("median", timing["mean"]),
                             std_time=timing["std"],
                             min_time=timing["min"],
                             max_time=timing["max"],
@@ -770,6 +896,7 @@ def main():
                         result = BenchmarkResult(
                             config=config,
                             mean_time=float("inf"),
+                            median_time=float("inf"),
                             std_time=0,
                             min_time=float("inf"),
                             max_time=float("inf"),
@@ -779,6 +906,9 @@ def main():
 
                 pbar.update(1)
 
+        if args.ncu_profile:
+            return
+
         # Display decode vs prefill results
         console.print("\n[bold green]Decode vs Prefill Results:[/]")
 
@@ -858,15 +988,20 @@ def main():
         base_config_args = {
             "num_layers": args.num_layers,
             "head_dim": args.head_dim,
+            "v_head_dim": args.v_head_dim,
             "num_q_heads": args.num_q_heads,
             "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,
+            "ncu_profile": args.ncu_profile,
+            "warmup_ms": args.warmup_ms,
+            "num_splits": args.num_splits,
+            "kv_lora_rank": args.kv_lora_rank,
+            "qk_nope_head_dim": args.qk_nope_head_dim,
+            "qk_rope_head_dim": args.qk_rope_head_dim,
         }
         all_results = run_model_parameter_sweep(
             backends,
@@ -882,15 +1017,17 @@ def main():
         base_config_args = {
             "num_layers": args.num_layers,
             "head_dim": args.head_dim,
+            "v_head_dim": args.v_head_dim,
             "num_q_heads": args.num_q_heads,
             "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,
+            "ncu_profile": args.ncu_profile,
+            "warmup_ms": args.warmup_ms,
+            "num_splits": args.num_splits,
         }
         all_results = run_parameter_sweep(
             backends, args.batch_specs, base_config_args, args.parameter_sweep, console
@@ -914,15 +1051,17 @@ def main():
                             batch_spec=spec,
                             num_layers=args.num_layers,
                             head_dim=args.head_dim,
+                            v_head_dim=getattr(args, "v_head_dim", None),
                             num_q_heads=args.num_q_heads,
                             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,
+                            ncu_profile=args.ncu_profile,
+                            warmup_ms=args.warmup_ms,
+                            num_splits=args.num_splits,
                         )
 
                         result = run_benchmark(config)
@@ -935,9 +1074,10 @@ def main():
 
                         pbar.update(1)
 
-            console.print("\n[bold green]Results:[/]")
-            formatter = ResultsFormatter(console)
-            formatter.print_table(decode_results, backends)
+            if not args.ncu_profile:
+                console.print("\n[bold green]Results:[/]")
+                formatter = ResultsFormatter(console)
+                formatter.print_table(decode_results, backends)
 
         # Run prefill backend comparison
         if prefill_backends:
@@ -962,9 +1102,8 @@ 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,
+                            warmup_ms=args.warmup_ms,
                             prefill_backend=pb,
                         )
 
@@ -980,16 +1119,17 @@ def main():
 
                         pbar.update(1)
 
-            console.print("\n[bold green]Prefill Backend Results:[/]")
-            formatter = ResultsFormatter(console)
-            formatter.print_table(
-                prefill_results, prefill_backends, compare_to_fastest=True
-            )
+            if not args.ncu_profile:
+                console.print("\n[bold green]Prefill Backend Results:[/]")
+                formatter = ResultsFormatter(console)
+                formatter.print_table(
+                    prefill_results, prefill_backends, compare_to_fastest=True
+                )
 
         all_results = decode_results + prefill_results
 
-    # Save results
-    if all_results:
+    # Save results (skip ncu profiling runs: timings are placeholder zeros)
+    if all_results and not args.ncu_profile:
         formatter = ResultsFormatter(console)
         if args.output_csv:
             formatter.save_csv(all_results, args.output_csv)

benchmarks/attention_benchmarks/common.py

@@ -15,6 +15,8 @@ from batch_spec import get_batch_type, parse_batch_spec
 from rich.console import Console
 from rich.table import Table
 
+from vllm.triton_utils import triton
+
 
 def batch_spec_sort_key(spec: str) -> tuple[int, int, int]:
     """
@@ -34,6 +36,30 @@ def batch_spec_sort_key(spec: str) -> tuple[int, int, int]:
         return (0, 0, 0)
 
 
+def run_do_bench(
+    benchmark_fn,
+    use_cuda_graphs: bool,
+    warmup_ms: int | None = None,
+) -> list[float]:
+    kwargs: dict[str, Any] = {"return_mode": "all"}
+    if use_cuda_graphs:
+        result = triton.testing.do_bench_cudagraph(benchmark_fn, **kwargs)
+    else:
+        if warmup_ms is not None:
+            kwargs["warmup"] = warmup_ms
+        result = triton.testing.do_bench(benchmark_fn, **kwargs)
+    return result
+
+
+def run_ncu_profile(benchmark_fn) -> None:
+    benchmark_fn()
+    torch.accelerator.synchronize()
+    torch.cuda.cudart().cudaProfilerStart()
+    benchmark_fn()
+    torch.accelerator.synchronize()
+    torch.cuda.cudart().cudaProfilerStop()
+
+
 # Mock classes for vLLM attention infrastructure
 
 
@@ -182,18 +208,37 @@ class ParameterSweep:
 
 @dataclass
 class ModelParameterSweep:
-    """Configuration for sweeping a model configuration parameter."""
+    """Configuration for sweeping model configuration parameter(s).
 
-    param_name: str  # Name of the model config parameter to sweep (e.g., "num_q_heads")
-    values: list[Any]  # List of values to test
-    label_format: str = "{backend}_{param_name}_{value}"  # Result label template
+    Supports two modes:
+    - Single param: param_name="head_dim", values=[128, 256, 512]
+    - Multi param: values=[{head_dim: 192, v_head_dim: 128}, {head_dim: 256}]
+      When values are dicts, each dict's keys are applied as config overrides.
+    """
+
+    param_name: str | None = None
+    values: list[Any] | None = None
+    label_format: str = "{backend}_{param_name}_{value}"
 
     def get_label(self, backend: str, value: Any) -> str:
         """Generate a label for a specific parameter value."""
+        if isinstance(value, dict):
+            return self.label_format.format(
+                backend=backend, param_name=self.param_name, value=value, **value
+            )
         return self.label_format.format(
             backend=backend, param_name=self.param_name, value=value
         )
 
+    def apply(self, config_args: dict, value: Any) -> None:
+        """Apply a sweep value to config args."""
+        if isinstance(value, dict):
+            config_args.update(value)
+        elif self.param_name is not None:
+            config_args[self.param_name] = value
+        else:
+            raise ValueError("param_name must be set if sweep values are not dicts")
+
 
 @dataclass
 class BenchmarkConfig:
@@ -208,10 +253,10 @@ class BenchmarkConfig:
     block_size: int
     device: str
     dtype: torch.dtype = torch.float16
-    repeats: int = 1
-    warmup_iters: int = 3
     profile_memory: bool = False
     use_cuda_graphs: bool = False
+    ncu_profile: bool = False
+    warmup_ms: int | None = None
 
     # "auto" or "fp8"
     kv_cache_dtype: str = "auto"
@@ -226,6 +271,7 @@ class BenchmarkConfig:
     # Backend-specific tuning
     num_kv_splits: int | None = None  # CUTLASS MLA
     reorder_batch_threshold: int | None = None  # FlashAttn MLA, FlashMLA
+    num_splits: int | None = None  # FlashAttention split-K (0=auto, 1=disabled)
 
 
 @dataclass
@@ -234,6 +280,7 @@ class BenchmarkResult:
 
     config: BenchmarkConfig
     mean_time: float  # seconds
+    median_time: float  # seconds
     std_time: float  # seconds
     min_time: float  # seconds
     max_time: float  # seconds
@@ -252,6 +299,7 @@ class BenchmarkResult:
         return {
             "config": asdict(self.config),
             "mean_time": self.mean_time,
+            "median_time": self.median_time,
             "std_time": self.std_time,
             "min_time": self.min_time,
             "max_time": self.max_time,

benchmarks/attention_benchmarks/configs/mla_decode.yaml

@@ -53,10 +53,9 @@ backends:
   - FLASHINFER_MLA
   - FLASH_ATTN_MLA  # Hopper only
   - FLASHMLA        # Hopper only
+  - TOKENSPEED_MLA  # Blackwell + R1 dims + FP8 KV (use --kv-cache-dtype fp8)
 
 device: "cuda:0"
-repeats: 100
-warmup_iters: 10
 profile_memory: true
 
 # Backend-specific tuning

benchmarks/attention_benchmarks/configs/mla_mixed_batch.yaml

@@ -51,8 +51,6 @@ backends:
   - FLASHMLA         # Hopper only
 
 device: "cuda:0"
-repeats: 5
-warmup_iters: 3
 profile_memory: true
 
 # Analyze chunked prefill workspace size impact