[CI] Reorganize release pipeline: separate nightly vs release sections

Reorder the pipeline into clear sections for readability: 1. Build Python Wheels (always runs) 2. ROCm Wheel Pipeline (always runs) 3. Nightly Docker Images (NIGHTLY=1 only) - CUDA/Ubuntu builds, multi-arch manifests, DockerHub publish, ROCm image + publish 4. Release (manual) - version input, PyPI upload, CPU image builds, ROCm root index Key changes: - Extract CPU image builds (manual/blocked) from nightly-gated group into their own "Build release CPU Docker images" group so they remain available for actual releases without NIGHTLY=1 - Move ROCm wheel jobs (1-4) up next to CUDA wheel builds - Remove redundant per-step NIGHTLY gates inside already-gated groups - Rename groups: "Build release Docker images" -> "Build nightly Docker images", "Publish release images" -> "Publish nightly images" Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
[CI] Only build release Docker images when NIGHTLY=1
2026-04-15 01:08:39 -07:00 · 2026-04-15 01:01:03 -07:00
22 changed files with 419 additions and 740 deletions
@@ -1,9 +1,7 @@
 steps:
-  - input: "Provide Release version here"
-    id: input-release-version
-    fields:
-      - text: "What is the release version?"
-        key: release-version
+  # =============================================================================
+  # Build Python Wheels (runs on every pipeline trigger)
+  # =============================================================================

  - group: "Build Python wheels"
    key: "build-wheels"
@@ -98,8 +96,257 @@ steps:
    commands:
      - "bash .buildkite/scripts/generate-and-upload-nightly-index.sh"

-  - group: "Build release Docker images"
+  # =============================================================================
+  # ROCm Wheel Pipeline (runs on every pipeline trigger)
+  # =============================================================================
+
+  # ROCm Job 1: Build ROCm Base Wheels (with S3 caching)
+  - label: ":rocm: Build ROCm Base Image & Wheels"
+    id: build-rocm-base-wheels
+    depends_on: ~
+    agents:
+      queue: cpu_queue_release
+    commands:
+      - |
+        set -euo pipefail
+
+        # Generate cache key
+        CACHE_KEY=$$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
+        ECR_CACHE_TAG="public.ecr.aws/q9t5s3a7/vllm-release-repo:$${CACHE_KEY}-rocm-base"
+
+        echo "========================================"
+        echo "ROCm Base Build Configuration"
+        echo "========================================"
+        echo "  CACHE_KEY: $${CACHE_KEY}"
+        echo "  ECR_CACHE_TAG: $${ECR_CACHE_TAG}"
+        echo "========================================"
+
+        # Login to ECR
+        aws ecr-public get-login-password --region us-east-1 | \
+          docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
+
+        IMAGE_EXISTS=false
+        WHEELS_EXIST=false
+
+        # Check ECR for Docker image
+
+        if docker manifest inspect "$${ECR_CACHE_TAG}" > /dev/null 2>&1; then
+          IMAGE_EXISTS=true
+          echo "ECR image cache HIT"
+        fi
+
+        # Check S3 for wheels
+        WHEEL_CACHE_STATUS=$(.buildkite/scripts/cache-rocm-base-wheels.sh check)
+        if [ "$${WHEEL_CACHE_STATUS}" = "hit" ]; then
+          WHEELS_EXIST=true
+          echo "S3 wheels cache HIT"
+        fi
+
+
+        # Scenario 1: Both cached (best case)
+        if [ "$${IMAGE_EXISTS}" = "true" ] && [ "$${WHEELS_EXIST}" = "true" ]; then
+          echo ""
+          echo "FULL CACHE HIT - Reusing both image and wheels"
+          echo ""
+
+          # Download wheels
+          .buildkite/scripts/cache-rocm-base-wheels.sh download
+
+          # Save ECR tag for downstream jobs
+          buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
+
+        # Scenario 2: Full rebuild needed
+        else
+          echo ""
+          echo " CACHE MISS - Building from scratch..."
+          echo ""
+
+          # Build full base image and push to ECR
+          DOCKER_BUILDKIT=1 docker buildx build \
+            --file docker/Dockerfile.rocm_base \
+            --tag "$${ECR_CACHE_TAG}" \
+            --build-arg USE_SCCACHE=1 \
+            --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
+            --build-arg SCCACHE_REGION_NAME=us-west-2 \
+            --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
+            --push \
+            .
+
+          # Build wheel extraction stage
+          DOCKER_BUILDKIT=1 docker buildx build \
+            --file docker/Dockerfile.rocm_base \
+            --tag rocm-base-debs:$${BUILDKITE_BUILD_NUMBER} \
+            --target debs_wheel_release \
+            --build-arg USE_SCCACHE=1 \
+            --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
+            --build-arg SCCACHE_REGION_NAME=us-west-2 \
+            --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
+            --load \
+            .
+
+          # Extract and upload wheels
+          mkdir -p artifacts/rocm-base-wheels
+          cid=$(docker create rocm-base-debs:$${BUILDKITE_BUILD_NUMBER})
+          docker cp $${cid}:/app/debs/. artifacts/rocm-base-wheels/
+          docker rm $${cid}
+
+          .buildkite/scripts/cache-rocm-base-wheels.sh upload
+
+          # Cache base docker image to ECR
+          docker push "$${ECR_CACHE_TAG}"
+
+          buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
+
+          echo ""
+          echo " Build complete - Image and wheels cached"
+        fi
+
+    artifact_paths:
+      - "artifacts/rocm-base-wheels/*.whl"
+    env:
+      DOCKER_BUILDKIT: "1"
+      S3_BUCKET: "vllm-wheels"
+
+  # ROCm Job 2: Build vLLM ROCm Wheel
+  - label: ":python: Build vLLM ROCm Wheel - x86_64"
+    id: build-rocm-vllm-wheel
+    depends_on:
+      - step: build-rocm-base-wheels
+        allow_failure: false
+    agents:
+      queue: cpu_queue_release
+    timeout_in_minutes: 180
+    commands:
+      # Download artifacts and prepare Docker image
+      - |
+        set -euo pipefail
+
+        # Ensure git tags are up-to-date (Buildkite's default fetch doesn't update tags)
+        # This fixes version detection when tags are moved/force-pushed
+        echo "Fetching latest tags from origin..."
+        git fetch --tags --force origin
+
+        # Log tag information for debugging version detection
+        echo "========================================"
+        echo "Git Tag Verification"
+        echo "========================================"
+        echo "Current HEAD: $(git rev-parse HEAD)"
+        echo "git describe --tags: $(git describe --tags 2>/dev/null || echo 'No tags found')"
+        echo ""
+        echo "Recent tags (pointing to commits near HEAD):"
+        git tag -l --sort=-creatordate | head -5
+        echo "setuptools_scm version detection:"
+        pip install -q setuptools_scm 2>/dev/null || true
+        python3 -c "import setuptools_scm; print('  Detected version:', setuptools_scm.get_version())" 2>/dev/null || echo "  (setuptools_scm not available in this environment)"
+        echo "========================================"
+
+        # Download wheel artifacts from current build
+        echo "Downloading wheel artifacts from current build"
+        buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
+
+        # Get ECR image tag from metadata (set by build-rocm-base-wheels)
+        ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
+        if [ -z "$${ECR_IMAGE_TAG}" ]; then
+          echo "ERROR: rocm-base-image-tag metadata not found"
+          echo "This should have been set by the build-rocm-base-wheels job"
+          exit 1
+        fi
+
+        echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
+
+        # Login to ECR
+        aws ecr-public get-login-password --region us-east-1 | \
+          docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
+
+        # Pull base Docker image from ECR
+        docker pull "$${ECR_IMAGE_TAG}"
+
+        echo "Loaded base image: $${ECR_IMAGE_TAG}"
+
+        # Prepare base wheels for Docker build context
+        mkdir -p docker/context/base-wheels
+        touch docker/context/base-wheels/.keep
+        cp artifacts/rocm-base-wheels/*.whl docker/context/base-wheels/
+        echo "Base wheels for vLLM build:"
+        ls -lh docker/context/base-wheels/
+
+        echo "========================================"
+        echo "Building vLLM wheel with:"
+        echo "  BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
+        echo "  BUILDKITE_BRANCH: $${BUILDKITE_BRANCH}"
+        echo "  BASE_IMAGE: $${ECR_IMAGE_TAG}"
+        echo "========================================"
+
+        # Build vLLM wheel using local checkout (REMOTE_VLLM=0)
+        DOCKER_BUILDKIT=1 docker build \
+          --file docker/Dockerfile.rocm \
+          --target export_vllm_wheel_release \
+          --output type=local,dest=rocm-dist \
+          --build-arg BASE_IMAGE="$${ECR_IMAGE_TAG}" \
+          --build-arg REMOTE_VLLM=0 \
+          --build-arg GIT_REPO_CHECK=1 \
+          --build-arg USE_SCCACHE=1 \
+          --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
+          --build-arg SCCACHE_REGION_NAME=us-west-2 \
+          --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
+          .
+        echo "Built vLLM wheel:"
+        ls -lh rocm-dist/*.whl
+        # Copy wheel to artifacts directory
+        mkdir -p artifacts/rocm-vllm-wheel
+        cp rocm-dist/*.whl artifacts/rocm-vllm-wheel/
+        echo "Final vLLM wheel:"
+        ls -lh artifacts/rocm-vllm-wheel/
+    artifact_paths:
+      - "artifacts/rocm-vllm-wheel/*.whl"
+    env:
+      DOCKER_BUILDKIT: "1"
+      S3_BUCKET: "vllm-wheels"
+
+  # ROCm Job 3: Upload Wheels to S3
+  - label: ":s3: Upload ROCm Wheels to S3"
+    id: upload-rocm-wheels
+    depends_on:
+      - step: build-rocm-vllm-wheel
+        allow_failure: false
+    agents:
+      queue: cpu_queue_release
+    timeout_in_minutes: 60
+    commands:
+      # Download all wheel artifacts and run upload
+      - |
+        set -euo pipefail
+
+        # Download artifacts from current build
+        echo "Downloading artifacts from current build"
+        buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
+        buildkite-agent artifact download "artifacts/rocm-vllm-wheel/*.whl" .
+
+        # Run upload script
+        bash .buildkite/scripts/upload-rocm-wheels.sh
+    env:
+      DOCKER_BUILDKIT: "1"
+      S3_BUCKET: "vllm-wheels"
+
+  # ROCm Job 4: Annotate ROCm Wheel Release
+  - label: ":memo: Annotate ROCm wheel release"
+    id: annotate-rocm-release
+    depends_on:
+      - upload-rocm-wheels
+    agents:
+      queue: cpu_queue_release
+    commands:
+      - "bash .buildkite/scripts/annotate-rocm-release.sh"
+    env:
+      S3_BUCKET: "vllm-wheels"
+
+  # =============================================================================
+  # Nightly: Build & Publish Docker Images (NIGHTLY=1 only)
+  # =============================================================================
+
+  - group: "Build nightly Docker images"
    key: "build-release-images"
+    if: build.env("NIGHTLY") == "1"
    steps:
      - label: "Build release image - x86_64 - CUDA 12.9"
        depends_on: ~
@@ -192,44 +439,9 @@ steps:
          - "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=13.0.1 --build-arg UBUNTU_VERSION=24.04 --build-arg GDRCOPY_OS_VERSION=Ubuntu24_04 --build-arg FLASHINFER_AOT_COMPILE=true --build-arg torch_cuda_arch_list='8.7 8.9 9.0 10.0+PTX 12.0 12.1' --build-arg INSTALL_KV_CONNECTORS=true --build-arg BUILD_BASE_IMAGE=nvidia/cuda:13.0.1-devel-ubuntu24.04 --tag public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404 --target vllm-openai --progress plain -f docker/Dockerfile ."
          - "docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$BUILDKITE_COMMIT-$(uname -m)-cu130-ubuntu2404"

-      - block: "Build release image for x86_64 CPU"
-        key: block-cpu-release-image-build
-        depends_on: ~
-
-      - label: "Build release image - x86_64 - CPU"
-        depends_on:
-          - block-cpu-release-image-build
-          - input-release-version
-        agents:
-          queue: cpu_queue_release
-        commands:
-          - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
-          - "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)"
-        env:
-          DOCKER_BUILDKIT: "1"
-
-      - block: "Build release image for arm64 CPU"
-        key: block-arm64-cpu-release-image-build
-        depends_on: ~
-
-      - label: "Build release image - arm64 - CPU"
-        depends_on: 
-          - block-arm64-cpu-release-image-build
-          - input-release-version
-        agents:
-          queue: arm64_cpu_queue_release
-        commands:
-          - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
-          - "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)"
-        env:
-          DOCKER_BUILDKIT: "1"
-
-  - group: "Publish release images"
+  - group: "Publish nightly images"
    key: "publish-release-images"
+    if: build.env("NIGHTLY") == "1"
    steps:
      - label: "Create multi-arch manifest - CUDA 12.9"
        depends_on:
@@ -291,7 +503,6 @@ steps:
      - label: "Publish nightly multi-arch image to DockerHub"
        depends_on:
          - create-multi-arch-manifest
-        if: build.env("NIGHTLY") == "1"
        agents:
          queue: small_cpu_queue_release
        commands:
@@ -309,7 +520,6 @@ steps:
      - label: "Publish nightly multi-arch image to DockerHub - CUDA 13.0"
        depends_on:
          - create-multi-arch-manifest-cuda-13-0
-        if: build.env("NIGHTLY") == "1"
        agents:
          queue: small_cpu_queue_release
        commands:
@@ -324,298 +534,10 @@ 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)
-  # =============================================================================
-  #
-  # vLLM version is determined by the Buildkite checkout (like CUDA pipeline).
-  # To build a specific version, trigger the build from that branch/tag.
-  #
-  # Environment variables for ROCm builds (set via Buildkite UI or schedule):
-  #
-  # Note: ROCm version is determined by BASE_IMAGE in docker/Dockerfile.rocm_base
-  #
-  # =============================================================================
-
-  # ROCm Job 1: Build ROCm Base Wheels (with S3 caching)
-  - label: ":rocm: Build ROCm Base Image & Wheels"
-    id: build-rocm-base-wheels
-    depends_on: ~
-    agents:
-      queue: cpu_queue_release
-    commands:
-      - |
-        set -euo pipefail
-
-        # Generate cache key
-        CACHE_KEY=$$(.buildkite/scripts/cache-rocm-base-wheels.sh key)
-        ECR_CACHE_TAG="public.ecr.aws/q9t5s3a7/vllm-release-repo:$${CACHE_KEY}-rocm-base"
-
-        echo "========================================"
-        echo "ROCm Base Build Configuration"
-        echo "========================================"
-        echo "  CACHE_KEY: $${CACHE_KEY}"
-        echo "  ECR_CACHE_TAG: $${ECR_CACHE_TAG}"
-        echo "========================================"
-        
-        # Login to ECR
-        aws ecr-public get-login-password --region us-east-1 | \
-          docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
-        
-        IMAGE_EXISTS=false
-        WHEELS_EXIST=false
-        
-        # Check ECR for Docker image
-
-        if docker manifest inspect "$${ECR_CACHE_TAG}" > /dev/null 2>&1; then
-          IMAGE_EXISTS=true
-          echo "ECR image cache HIT"
-        fi
-        
-        # Check S3 for wheels
-        WHEEL_CACHE_STATUS=$(.buildkite/scripts/cache-rocm-base-wheels.sh check)
-        if [ "$${WHEEL_CACHE_STATUS}" = "hit" ]; then
-          WHEELS_EXIST=true
-          echo "S3 wheels cache HIT"
-        fi
-
-        
-        # Scenario 1: Both cached (best case)
-        if [ "$${IMAGE_EXISTS}" = "true" ] && [ "$${WHEELS_EXIST}" = "true" ]; then
-          echo ""
-          echo "FULL CACHE HIT - Reusing both image and wheels"
-          echo ""
-
-          # Download wheels
-          .buildkite/scripts/cache-rocm-base-wheels.sh download
-          
-          # Save ECR tag for downstream jobs
-          buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
-          
-        # Scenario 2: Full rebuild needed
-        else
-          echo ""
-          echo " CACHE MISS - Building from scratch..."
-          echo ""
-          
-          # Build full base image and push to ECR
-          DOCKER_BUILDKIT=1 docker buildx build \
-            --file docker/Dockerfile.rocm_base \
-            --tag "$${ECR_CACHE_TAG}" \
-            --build-arg USE_SCCACHE=1 \
-            --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
-            --build-arg SCCACHE_REGION_NAME=us-west-2 \
-            --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
-            --push \
-            .
-          
-          # Build wheel extraction stage
-          DOCKER_BUILDKIT=1 docker buildx build \
-            --file docker/Dockerfile.rocm_base \
-            --tag rocm-base-debs:$${BUILDKITE_BUILD_NUMBER} \
-            --target debs_wheel_release \
-            --build-arg USE_SCCACHE=1 \
-            --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
-            --build-arg SCCACHE_REGION_NAME=us-west-2 \
-            --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
-            --load \
-            .
-          
-          # Extract and upload wheels
-          mkdir -p artifacts/rocm-base-wheels
-          cid=$(docker create rocm-base-debs:$${BUILDKITE_BUILD_NUMBER})
-          docker cp $${cid}:/app/debs/. artifacts/rocm-base-wheels/
-          docker rm $${cid}
-          
-          .buildkite/scripts/cache-rocm-base-wheels.sh upload
-
-          # Cache base docker image to ECR
-          docker push "$${ECR_CACHE_TAG}"
-          
-          buildkite-agent meta-data set "rocm-base-image-tag" "$${ECR_CACHE_TAG}"
-          
-          echo ""
-          echo " Build complete - Image and wheels cached"
-        fi
-        
-    artifact_paths:
-      - "artifacts/rocm-base-wheels/*.whl"
-    env:
-      DOCKER_BUILDKIT: "1"
-      S3_BUCKET: "vllm-wheels"
-
-  # ROCm Job 2: Build vLLM ROCm Wheel
-  - label: ":python: Build vLLM ROCm Wheel - x86_64"
-    id: build-rocm-vllm-wheel
-    depends_on:
-      - step: build-rocm-base-wheels
-        allow_failure: false
-    agents:
-      queue: cpu_queue_release
-    timeout_in_minutes: 180
-    commands:
-      # Download artifacts and prepare Docker image
-      - |
-        set -euo pipefail
-
-        # Ensure git tags are up-to-date (Buildkite's default fetch doesn't update tags)
-        # This fixes version detection when tags are moved/force-pushed
-        echo "Fetching latest tags from origin..."
-        git fetch --tags --force origin
-        
-        # Log tag information for debugging version detection
-        echo "========================================"
-        echo "Git Tag Verification"
-        echo "========================================"
-        echo "Current HEAD: $(git rev-parse HEAD)"
-        echo "git describe --tags: $(git describe --tags 2>/dev/null || echo 'No tags found')"
-        echo ""
-        echo "Recent tags (pointing to commits near HEAD):"
-        git tag -l --sort=-creatordate | head -5
-        echo "setuptools_scm version detection:"
-        pip install -q setuptools_scm 2>/dev/null || true
-        python3 -c "import setuptools_scm; print('  Detected version:', setuptools_scm.get_version())" 2>/dev/null || echo "  (setuptools_scm not available in this environment)"
-        echo "========================================"
-
-        # Download wheel artifacts from current build
-        echo "Downloading wheel artifacts from current build"
-        buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
-
-        # Get ECR image tag from metadata (set by build-rocm-base-wheels)
-        ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
-        if [ -z "$${ECR_IMAGE_TAG}" ]; then
-          echo "ERROR: rocm-base-image-tag metadata not found"
-          echo "This should have been set by the build-rocm-base-wheels job"
-          exit 1
-        fi
-        
-        echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
-        
-        # Login to ECR
-        aws ecr-public get-login-password --region us-east-1 | \
-          docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
-        
-        # Pull base Docker image from ECR
-        docker pull "$${ECR_IMAGE_TAG}"
-        
-        echo "Loaded base image: $${ECR_IMAGE_TAG}"
-        
-        # Prepare base wheels for Docker build context
-        mkdir -p docker/context/base-wheels
-        touch docker/context/base-wheels/.keep
-        cp artifacts/rocm-base-wheels/*.whl docker/context/base-wheels/
-        echo "Base wheels for vLLM build:"
-        ls -lh docker/context/base-wheels/
-
-        echo "========================================"
-        echo "Building vLLM wheel with:"
-        echo "  BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
-        echo "  BUILDKITE_BRANCH: $${BUILDKITE_BRANCH}"
-        echo "  BASE_IMAGE: $${ECR_IMAGE_TAG}"
-        echo "========================================"
-
-        # Build vLLM wheel using local checkout (REMOTE_VLLM=0)
-        DOCKER_BUILDKIT=1 docker build \
-          --file docker/Dockerfile.rocm \
-          --target export_vllm_wheel_release \
-          --output type=local,dest=rocm-dist \
-          --build-arg BASE_IMAGE="$${ECR_IMAGE_TAG}" \
-          --build-arg REMOTE_VLLM=0 \
-          --build-arg GIT_REPO_CHECK=1 \
-          --build-arg USE_SCCACHE=1 \
-          --build-arg SCCACHE_BUCKET_NAME=vllm-build-sccache \
-          --build-arg SCCACHE_REGION_NAME=us-west-2 \
-          --build-arg SCCACHE_S3_NO_CREDENTIALS=0 \
-          .
-        echo "Built vLLM wheel:"
-        ls -lh rocm-dist/*.whl
-        # Copy wheel to artifacts directory
-        mkdir -p artifacts/rocm-vllm-wheel
-        cp rocm-dist/*.whl artifacts/rocm-vllm-wheel/
-        echo "Final vLLM wheel:"
-        ls -lh artifacts/rocm-vllm-wheel/
-    artifact_paths:
-      - "artifacts/rocm-vllm-wheel/*.whl"
-    env:
-      DOCKER_BUILDKIT: "1"
-      S3_BUCKET: "vllm-wheels"
-
-  # ROCm Job 3: Upload Wheels to S3
-  - label: ":s3: Upload ROCm Wheels to S3"
-    id: upload-rocm-wheels
-    depends_on:
-      - step: build-rocm-vllm-wheel
-        allow_failure: false
-    agents:
-      queue: cpu_queue_release
-    timeout_in_minutes: 60
-    commands:
-      # Download all wheel artifacts and run upload
-      - |
-        set -euo pipefail
-
-        # Download artifacts from current build
-        echo "Downloading artifacts from current build"
-        buildkite-agent artifact download "artifacts/rocm-base-wheels/*.whl" .
-        buildkite-agent artifact download "artifacts/rocm-vllm-wheel/*.whl" .
-
-        # Run upload script
-        bash .buildkite/scripts/upload-rocm-wheels.sh
-    env:
-      DOCKER_BUILDKIT: "1"
-      S3_BUCKET: "vllm-wheels"
-
-  # ROCm Job 4: Annotate ROCm Wheel Release
-  - label: ":memo: Annotate ROCm wheel release"
-    id: annotate-rocm-release
-    depends_on:
-      - upload-rocm-wheels
-    agents:
-      queue: cpu_queue_release
-    commands:
-      - "bash .buildkite/scripts/annotate-rocm-release.sh"
-    env:
-      S3_BUCKET: "vllm-wheels"
-
-  # ROCm Job 5: Generate Root Index for ROCm Wheels (for release only)
-  # This is the job to create https://wheels.vllm.ai/rocm/ index allowing
-  # users to install with `uv pip install vllm --extra-index-url https://wheels.vllm.ai/rocm/`
-  - block: "Generate Root Index for ROCm Wheels for Release"
-    key: block-generate-root-index-rocm-wheels
-    depends_on: upload-rocm-wheels
-
-  - label: ":package: Generate Root Index for ROCm Wheels for Release"
-    depends_on: block-generate-root-index-rocm-wheels
-    id: generate-root-index-rocm-wheels
-    agents:
-      queue: cpu_queue_release
-    commands:
-      - "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
-    env:
-      S3_BUCKET: "vllm-wheels"
-      VARIANT: "rocm721"
-
-  # ROCm Job 6: Build ROCm Release Docker Image
+  # ROCm nightly Docker image
  - label: ":docker: Build release image - x86_64 - ROCm"
    id: build-rocm-release-image
+    if: build.env("NIGHTLY") == "1"
    depends_on:
      - step: build-rocm-base-wheels
        allow_failure: false
@@ -625,11 +547,11 @@ steps:
    commands:
      - |
        set -euo pipefail
-        
+
        # Login to ECR
        aws ecr-public get-login-password --region us-east-1 | \
          docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7
-        
+
        # Get ECR image tag from metadata (set by build-rocm-base-wheels)
        ECR_IMAGE_TAG="$$(buildkite-agent meta-data get rocm-base-image-tag 2>/dev/null || echo '')"
        if [ -z "$${ECR_IMAGE_TAG}" ]; then
@@ -637,23 +559,23 @@ steps:
          echo "This should have been set by the build-rocm-base-wheels job"
          exit 1
        fi
-        
+
        echo "Pulling base Docker image from ECR: $${ECR_IMAGE_TAG}"
-        
+
        # Pull base Docker image from ECR
        docker pull "$${ECR_IMAGE_TAG}"
-        
+
        echo "Loaded base image: $${ECR_IMAGE_TAG}"
-        
+
        # Pass the base image ECR tag to downstream steps (nightly publish)
        buildkite-agent meta-data set "rocm-base-ecr-tag" "$${ECR_IMAGE_TAG}"
-        
+
        echo "========================================"
        echo "Building vLLM ROCm release image with:"
        echo "  BASE_IMAGE: $${ECR_IMAGE_TAG}"
        echo "  BUILDKITE_COMMIT: $${BUILDKITE_COMMIT}"
        echo "========================================"
-        
+
        # Build vLLM ROCm release image using cached base
        DOCKER_BUILDKIT=1 docker build \
          --build-arg max_jobs=16 \
@@ -666,10 +588,10 @@ steps:
          --target vllm-openai \
          --progress plain \
          -f docker/Dockerfile.rocm .
-        
+
        # Push to ECR
        docker push public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm
-        
+
        echo ""
        echo " Successfully built and pushed ROCm release image"
        echo "   Image: public.ecr.aws/q9t5s3a7/vllm-release-repo:$${BUILDKITE_COMMIT}-rocm"
@@ -696,3 +618,84 @@ steps:
    env:
      DOCKER_BUILDKIT: "1"
      DOCKERHUB_USERNAME: "vllmbot"
+
+  # =============================================================================
+  # Release: Publish Wheels & Build CPU Images (manual, requires release version)
+  # =============================================================================
+
+  - input: "Provide Release version here"
+    id: input-release-version
+    fields:
+      - text: "What is the release version?"
+        key: release-version
+
+  - group: "Publish release 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"
+
+  - group: "Build release CPU Docker images"
+    steps:
+      - block: "Build release image for x86_64 CPU"
+        key: block-cpu-release-image-build
+        depends_on: ~
+
+      - label: "Build release image - x86_64 - CPU"
+        depends_on:
+          - block-cpu-release-image-build
+          - input-release-version
+        agents:
+          queue: cpu_queue_release
+        commands:
+          - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
+          - "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)"
+        env:
+          DOCKER_BUILDKIT: "1"
+
+      - block: "Build release image for arm64 CPU"
+        key: block-arm64-cpu-release-image-build
+        depends_on: ~
+
+      - label: "Build release image - arm64 - CPU"
+        depends_on:
+          - block-arm64-cpu-release-image-build
+          - input-release-version
+        agents:
+          queue: arm64_cpu_queue_release
+        commands:
+          - "aws ecr-public get-login-password --region us-east-1 | docker login --username AWS --password-stdin public.ecr.aws/q9t5s3a7"
+          - "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)"
+        env:
+          DOCKER_BUILDKIT: "1"
+
+  - block: "Generate Root Index for ROCm Wheels for Release"
+    key: block-generate-root-index-rocm-wheels
+    depends_on: upload-rocm-wheels
+
+  - label: ":package: Generate Root Index for ROCm Wheels for Release"
+    depends_on: block-generate-root-index-rocm-wheels
+    id: generate-root-index-rocm-wheels
+    agents:
+      queue: cpu_queue_release
+    commands:
+      - "bash tools/vllm-rocm/generate-rocm-wheels-root-index.sh"
+    env:
+      S3_BUCKET: "vllm-wheels"
+      VARIANT: "rocm721"
@@ -222,47 +222,3 @@ def test_model_specialization_with_evaluate_guards(
        torch.randn(1, 10).cuda(),
        is_01_specialization=True,
    )
-
-
-@pytest.mark.skipif(not is_torch_equal_or_newer("2.10.0"), reason="requires torch 2.10")
-def test_piecewise_backend_empty_sym_shape_indices():
-    """Test that PiecewiseBackend handles empty sym_shape_indices correctly.
-
-    When all inputs have static shapes (no torch.SymInt), sym_shape_indices
-    will be empty. The fix in PiecewiseBackend.__call__ handles this case
-    by using the first compiled range_entry.
-    """
-    gc.collect()
-    torch.accelerator.empty_cache()
-    torch.accelerator.synchronize()
-
-    # Use small max_model_len and max_num_batched_tokens to encourage
-    # static shape compilation with empty sym_shape_indices
-    llm = LLM(
-        model="Qwen/Qwen3-0.6B",
-        max_model_len=512,
-        max_num_batched_tokens=1,
-        compilation_config={
-            "mode": CompilationMode.VLLM_COMPILE,
-            "dynamic_shapes_config": {
-                "type": DynamicShapesType.BACKED.value,
-            },
-        },
-    )
-
-    sampling_params = SamplingParams(temperature=0, top_p=0.95, max_tokens=10)
-
-    # Generate with static shape inputs
-    output = llm.generate("Hello, my name is", sampling_params=sampling_params)
-    result = output[0].outputs[0].text
-    assert len(result) > 0, "Should generate non-empty output"
-
-    # Generate again to verify compilation works with empty sym_shape_indices
-    output = llm.generate("The capital of France is", sampling_params=sampling_params)
-    result = output[0].outputs[0].text
-    assert len(result) > 0, "Should generate non-empty output on second run"
-
-    del llm
-    gc.collect()
-    torch.accelerator.empty_cache()
-    torch.accelerator.synchronize()
@@ -1,150 +0,0 @@
-# SPDX-License-Identifier: Apache-2.0
-# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-"""Unit tests for tool_calls Iterable → list materialisation.
-
-Regression tests for https://github.com/vllm-project/vllm/issues/34792.
-
-Setting VLLM_LOGGING_LEVEL=debug caused tool calling to break for Mistral
-models because:
-  1. The OpenAI Python SDK types tool_calls as Iterable[...] in
-     ChatCompletionAssistantMessageParam.
-  2. Pydantic v2, when validating from Python objects (not from raw JSON),
-     wraps Iterable fields in a one-shot lazy iterator.
-  3. Debug logging called model_dump_json() which consumed that iterator.
-  4. The Mistral tokenizer then saw empty tool_calls and raised
-     "ValueError: Unexpected tool call id ...".
-"""
-
-import pytest
-
-from vllm.entrypoints.openai.chat_completion.protocol import ChatCompletionRequest
-
-
-def _make_tool_call(tc_id: str, name: str, args: str) -> dict:
-    return {
-        "id": tc_id,
-        "type": "function",
-        "function": {"name": name, "arguments": args},
-    }
-
-
-def _make_request(messages: list) -> ChatCompletionRequest:
-    return ChatCompletionRequest(
-        model="test-model",
-        messages=messages,
-    )
-
-
-def test_tool_calls_list_preserved_after_model_dump():
-    """tool_calls in assistant messages must be readable after model_dump_json.
-
-    When the request is built from Python dicts (as in the Anthropic → OpenAI
-    conversion path), Pydantic v2 previously wrapped the Iterable tool_calls
-    in a one-shot iterator.  model_dump_json() consumed it, leaving subsequent
-    readers (e.g. the Mistral tokenizer) with an empty sequence.
-    """
-    tool_call = _make_tool_call("call_abc123", "get_weather", '{"city": "Paris"}')
-    messages = [
-        {"role": "user", "content": "What is the weather in Paris?"},
-        {"role": "assistant", "content": None, "tool_calls": [tool_call]},
-        {
-            "role": "tool",
-            "tool_call_id": "call_abc123",
-            "content": '{"temperature": 20}',
-        },
-    ]
-
-    req = _make_request(messages)
-
-    # Simulate debug logging: serialize the model (this was the trigger)
-    _ = req.model_dump_json()
-
-    # The assistant message must still have accessible tool_calls afterwards
-    assistant_msg = req.messages[1]
-    assert isinstance(assistant_msg, dict)
-    tool_calls = assistant_msg.get("tool_calls")
-    assert tool_calls is not None, "tool_calls must not be None after model_dump_json"
-    assert isinstance(tool_calls, list), "tool_calls must be a list"
-    assert len(tool_calls) > 0, "tool_calls must not be empty after model_dump_json"
-
-
-def test_tool_calls_from_generator_are_materialised():
-    """tool_calls passed as a generator must be converted to list on validation."""
-    tool_call = _make_tool_call("call_gen1", "search", '{"query": "vllm"}')
-
-    def tool_calls_gen():
-        yield tool_call
-
-    messages = [
-        {"role": "user", "content": "Search for vllm"},
-        {
-            "role": "assistant",
-            "content": None,
-            "tool_calls": tool_calls_gen(),  # one-shot generator
-        },
-    ]
-
-    req = _make_request(messages)
-    assistant_msg = req.messages[1]
-    assert isinstance(assistant_msg, dict)
-
-    # Iterate twice — must not raise or return empty on second pass
-    tool_calls_first = list(assistant_msg.get("tool_calls", []))
-    tool_calls_second = list(assistant_msg.get("tool_calls", []))
-
-    assert len(tool_calls_first) == 1, "First read must return the tool call"
-    assert len(tool_calls_second) == 1, "Second read must also return the tool call"
-
-
-def test_tool_calls_list_passthrough():
-    """tool_calls already provided as a list must remain a list."""
-    tool_call = _make_tool_call("call_list1", "calculate", '{"expr": "2+2"}')
-    messages = [
-        {"role": "user", "content": "Calculate 2+2"},
-        {"role": "assistant", "content": None, "tool_calls": [tool_call]},
-    ]
-
-    req = _make_request(messages)
-    assistant_msg = req.messages[1]
-    assert isinstance(assistant_msg, dict)
-    assert isinstance(assistant_msg.get("tool_calls"), list)
-
-
-def test_messages_without_tool_calls_unaffected():
-    """Messages without tool_calls must be handled correctly."""
-    messages = [
-        {"role": "system", "content": "You are a helpful assistant."},
-        {"role": "user", "content": "Hello!"},
-        {"role": "assistant", "content": "Hi there!"},
-    ]
-
-    req = _make_request(messages)
-    # None of the messages should have tool_calls injected
-    for msg in req.messages:
-        assert isinstance(msg, dict)
-        assert msg.get("tool_calls") is None or msg.get("tool_calls") == []
-
-
-@pytest.mark.parametrize("num_tool_calls", [1, 3])
-def test_multiple_tool_calls_materialised(num_tool_calls: int):
-    """Multiple tool calls in a single message are all preserved."""
-    tool_calls = [
-        _make_tool_call(f"call_{i}", f"func_{i}", f'{{"arg": {i}}}')
-        for i in range(num_tool_calls)
-    ]
-    messages = [
-        {"role": "user", "content": "Do things"},
-        {"role": "assistant", "content": None, "tool_calls": iter(tool_calls)},
-    ]
-
-    req = _make_request(messages)
-    assistant_msg = req.messages[1]
-    assert isinstance(assistant_msg, dict)
-
-    result_tool_calls = assistant_msg.get("tool_calls")
-    assert isinstance(result_tool_calls, list)
-    assert len(result_tool_calls) == num_tool_calls
-
-    # Verify after model_dump_json too
-    _ = req.model_dump_json()
-    assert len(assistant_msg.get("tool_calls", [])) == num_tool_calls
@@ -12,7 +12,6 @@ MODELS = [
    "TheBloke/TinyLlama-1.1B-Chat-v1.0-GPTQ",  # with g_idx
    "Qwen/Qwen1.5-0.5B-Chat-GPTQ-Int4",  # without g_idx
    "RedHatAI/Qwen3-1.7B-quantized.w4a16",  # with zp
-    "OPEA/Qwen2.5-0.5B-Instruct-int4-sym-inc",
 ]
 DTYPE = ["bfloat16"]

@@ -124,8 +124,12 @@ def test_offloading_connector(request_runner, async_scheduling: bool):
        return [BlockHash(str(i).encode()) for i in int_hashes]

    def take_events() -> Iterable[OffloadingEvent]:
-        yield OffloadingEvent(keys=to_keys([1, 2, 3]), medium="A", removed=False)
-        yield OffloadingEvent(keys=to_keys([4, 5, 6]), medium="B", removed=True)
+        yield OffloadingEvent(
+            keys=to_keys([1, 2, 3]), block_size=16, medium="A", removed=False
+        )
+        yield OffloadingEvent(
+            keys=to_keys([4, 5, 6]), block_size=32, medium="B", removed=True
+        )

    runner.manager.take_events.side_effect = take_events
    events = list(runner.scheduler_connector.take_events())
@@ -133,7 +137,7 @@ def test_offloading_connector(request_runner, async_scheduling: bool):
    event = events[0]
    assert isinstance(event, BlockStored)
    assert event.block_hashes == to_hashes([1, 2, 3])
-    assert event.block_size == 0
+    assert event.block_size == 16
    assert event.medium == "A"
    assert event.token_ids == []
    assert event.parent_block_hash is None
@@ -59,6 +59,7 @@ def verify_load_output(

 def verify_events(
    events: Iterable[OffloadingEvent],
+    block_size: int,
    expected_stores: tuple[set[int], ...] = (),
    expected_evictions: tuple[set[int], ...] = (),
 ):
@@ -66,6 +67,7 @@ def verify_events(
    evictions: list[set[OffloadKey]] = []
    for event in events:
        assert event.medium == CPULoadStoreSpec.medium()
+        assert event.block_size == block_size
        if event.removed:
            evictions.append(set(event.keys))
        else:
@@ -96,7 +98,9 @@ def test_already_stored_block_not_evicted_during_prepare_store(eviction_policy):
              candidate to make room for [3, 4, 5]
        - After complete_store([2, 3, 4, 5]), block 2 must still be present.
    """
+    block_size = 256
    manager = CPUOffloadingManager(
+        block_size=block_size,
        num_blocks=4,
        cache_policy=eviction_policy,
        enable_events=True,
@@ -134,9 +138,10 @@ def test_cpu_manager():
    """
    Tests CPUOffloadingManager with lru policy.
    """
-    # initialize a CPU manager with a capacity of 4 blocks
+    # initialize a CPU backend with a capacity of 4 blocks
+    block_size = 256
    cpu_manager = CPUOffloadingManager(
-        num_blocks=4, cache_policy="lru", enable_events=True
+        block_size=block_size, num_blocks=4, cache_policy="lru", enable_events=True
    )

    # prepare store [1, 2]
@@ -158,7 +163,9 @@ def test_cpu_manager():

    # complete store [1, 2]
    cpu_manager.complete_store(to_keys([1, 2]))
-    verify_events(cpu_manager.take_events(), expected_stores=({1, 2},))
+    verify_events(
+        cpu_manager.take_events(), block_size=block_size, expected_stores=({1, 2},)
+    )

    # lookup [1, 2]
    assert cpu_manager.lookup(to_keys([1])) == 1
@@ -177,7 +184,9 @@ def test_cpu_manager():
    )

    # verify eviction event
-    verify_events(cpu_manager.take_events(), expected_evictions=({1},))
+    verify_events(
+        cpu_manager.take_events(), block_size=block_size, expected_evictions=({1},)
+    )

    # prepare store with no space
    assert cpu_manager.prepare_store(to_keys([1, 6])) is None
@@ -232,6 +241,7 @@ def test_cpu_manager():

    verify_events(
        cpu_manager.take_events(),
+        block_size=block_size,
        expected_stores=({3, 4, 5}, {6, 7, 8}),
        expected_evictions=({2, 3, 4}, {8}),
    )
@@ -244,6 +254,7 @@ class TestARCPolicy:
        self, num_blocks: int = 4, enable_events: bool = True
    ) -> tuple[CPUOffloadingManager, ARCCachePolicy]:
        manager = CPUOffloadingManager(
+            block_size=256,
            num_blocks=num_blocks,
            cache_policy="arc",
            enable_events=enable_events,
@@ -278,7 +289,9 @@ class TestARCPolicy:

        # complete store [1, 2]
        cpu_manager.complete_store(to_keys([1, 2]))
-        verify_events(cpu_manager.take_events(), expected_stores=({1, 2},))
+        verify_events(
+            cpu_manager.take_events(), block_size=256, expected_stores=({1, 2},)
+        )

        # lookup [1, 2]
        assert cpu_manager.lookup(to_keys([1])) == 1
@@ -534,8 +547,9 @@ def test_filter_reused_manager():
    """
    Tests FilterReusedOffloadingManager with a CPUOffloadingManager.
    """
+    block_size = 256
    lru_manager = CPUOffloadingManager(
-        num_blocks=4, cache_policy="lru", enable_events=True
+        block_size=block_size, num_blocks=4, cache_policy="lru", enable_events=True
    )

    manager = FilterReusedOffloadingManager(
@@ -26,7 +26,6 @@ def test_prefill_kv_computed_with_cache():
    # Case 1: With prefix cache (1200 tokens cached)
    iteration_stats.update_from_finished_request(
        finish_reason=FinishReason.STOP,
-        request_id="test-req-001",
        num_prompt_tokens=10000,
        max_tokens_param=100,
        req_stats=req_stats,
@@ -36,7 +35,6 @@ def test_prefill_kv_computed_with_cache():
    finished_req = iteration_stats.finished_requests[0]
    assert finished_req.num_prompt_tokens == 10000
    assert finished_req.num_cached_tokens == 1200
-    assert finished_req.request_id == "test-req-001"

    # Verify calculation: prefill KV = prompt tokens - cached tokens
    prefill_kv_computed = finished_req.num_prompt_tokens - max(
@@ -57,7 +55,6 @@ def test_prefill_kv_computed_no_cache():
    # Case 2: No prefix cache
    iteration_stats.update_from_finished_request(
        finish_reason=FinishReason.STOP,
-        request_id="test-req-002",
        num_prompt_tokens=2000,
        max_tokens_param=100,
        req_stats=req_stats,
@@ -67,7 +64,6 @@ def test_prefill_kv_computed_no_cache():
    finished_req = iteration_stats.finished_requests[0]
    assert finished_req.num_prompt_tokens == 2000
    assert finished_req.num_cached_tokens == 0
-    assert finished_req.request_id == "test-req-002"

    # Verify calculation: prefill KV = full prompt when no cache
    prefill_kv_computed = finished_req.num_prompt_tokens - max(
@@ -88,7 +84,6 @@ def test_prefill_kv_computed_edge_cases():
    # Case 3: Negative num_cached_tokens (shouldn't happen, but handle gracefully)
    iteration_stats.update_from_finished_request(
        finish_reason=FinishReason.STOP,
-        request_id="test-req-003",
        num_prompt_tokens=100,
        max_tokens_param=10,
        req_stats=req_stats,
@@ -101,13 +96,11 @@ def test_prefill_kv_computed_edge_cases():
        finished_req.num_cached_tokens, 0
    )
    assert prefill_kv_computed == 100  # Should treat negative as 0
-    assert finished_req.request_id == "test-req-003"

    # Case 4: All tokens cached (shouldn't happen in practice)
    iteration_stats2 = IterationStats()
    iteration_stats2.update_from_finished_request(
        finish_reason=FinishReason.STOP,
-        request_id="test-req-004",
        num_prompt_tokens=100,
        max_tokens_param=10,
        req_stats=req_stats,
@@ -119,7 +112,6 @@ def test_prefill_kv_computed_edge_cases():
        finished_req2.num_cached_tokens, 0
    )
    assert prefill_kv_computed2 == 0  # All cached, nothing computed
-    assert finished_req2.request_id == "test-req-004"


 def test_prompt_token_stats_all_computed():
@@ -144,46 +144,6 @@ def _xpu_mxfp8_quantize_fake(
    return x.to(dtype), x_s.to(torch.float8_e8m0fnu)


-def _xpu_mxfp4_quantize_impl(
-    x: torch.Tensor,
-) -> tuple[torch.Tensor, torch.Tensor]:
-    MXFP4_BLOCK_SIZE = 32
-    eps = 1e-10
-    assert x.ndim == 2, "input must be 2-D"
-    assert x.shape[-1] % MXFP4_BLOCK_SIZE == 0, (
-        f"last dimension {x.shape[-1]} must be divisible by group_size "
-        f"{MXFP4_BLOCK_SIZE}"
-    )
-    assert x.is_contiguous(), "input groups must be contiguous"
-
-    M, N = x.shape
-
-    # Packed FP4 output: two nibbles per byte
-    x_q = torch.empty(M, N // 2, device=x.device, dtype=torch.uint8)
-    x_s = torch.empty(M, N // MXFP4_BLOCK_SIZE, device=x.device, dtype=torch.float32)
-
-    torch.ops._C.per_token_group_quant_mxfp4(x, x_q, x_s, MXFP4_BLOCK_SIZE, eps)
-
-    x_q = x_q.view(torch.float4_e2m1fn_x2)
-    x_s = x_s.to(dtype=torch.float8_e8m0fnu, memory_format=torch.preserve_format)
-    return x_q, x_s
-
-
-def _xpu_mxfp4_quantize_fake(
-    x: torch.Tensor,
-) -> tuple[torch.Tensor, torch.Tensor]:
-    MXFP4_BLOCK_SIZE = 32
-    M, N = x.shape
-
-    # Packed FP4 output: two nibbles per byte
-    x_q = torch.empty(M, N // 2, device=x.device, dtype=torch.uint8)
-    x_s = torch.empty(M, N // MXFP4_BLOCK_SIZE, device=x.device, dtype=torch.float32)
-
-    x_q = x_q.view(torch.float4_e2m1fn_x2)
-    x_s = x_s.to(dtype=torch.float8_e8m0fnu, memory_format=torch.preserve_format)
-    return x_q, x_s
-
-
 # Global flag to ensure ops are registered only once
 _OPS_REGISTERED = False

@@ -595,12 +555,6 @@ class xpu_ops:
                fake_impl=_xpu_mxfp8_quantize_fake,
            )

-            direct_register_custom_op(
-                op_name="xpu_mxfp4_quantize",
-                op_func=_xpu_mxfp4_quantize_impl,
-                fake_impl=_xpu_mxfp4_quantize_fake,
-            )
-
            _OPS_REGISTERED = True


@@ -354,22 +354,12 @@ class PiecewiseBackend:
        return None

    def __call__(self, *args: Any) -> Any:
-        if self.sym_shape_indices:
-            runtime_shape = args[self.sym_shape_indices[0]]
-            range_entry = self._find_range_for_shape(runtime_shape)
-            assert range_entry is not None, (
-                f"Shape: {runtime_shape} out of considered ranges: "
-                f"{self.compile_ranges}"
-            )
-        else:
-            # All inputs have static shapes; use the only compiled range_entry
-            compiled_entries = [re for re in self.range_entries.values() if re.compiled]
-            assert len(compiled_entries) == 1, (
-                f"Expected exactly one compiled range_entry for static shape "
-                f"compilation, but found {len(compiled_entries)}"
-            )
-            range_entry = compiled_entries[0]
+        runtime_shape = args[self.sym_shape_indices[0]]
+        range_entry = self._find_range_for_shape(runtime_shape)

+        assert range_entry is not None, (
+            f"Shape: {runtime_shape} out of considered ranges: {self.compile_ranges}"
+        )
        assert range_entry.compiled, (
            "All ranges should be compiled or loaded up front in "
            "PiecewiseBackend.__init__. "
@@ -424,7 +424,7 @@ class OffloadingConnectorScheduler:
                    parent_block_hash=None,
                    token_ids=[],
                    lora_id=None,
-                    block_size=0,
+                    block_size=event.block_size,
                    medium=event.medium,
                    lora_name=None,
                )
@@ -290,7 +290,7 @@ class CustomChatCompletionMessageParam(TypedDict, total=False):
    tool_call_id: str | None
    """Tool call that this message is responding to."""

-    tool_calls: list[ChatCompletionMessageToolCallParam] | None
+    tool_calls: Iterable[ChatCompletionMessageToolCallParam] | None
    """The tool calls generated by the model, such as function calls."""

    reasoning: str | None
@@ -321,7 +321,7 @@ class ConversationMessage(TypedDict, total=False):
    name: str | None
    """The name of the function to call"""

-    tool_calls: list[ChatCompletionMessageToolCallParam] | None
+    tool_calls: Iterable[ChatCompletionMessageToolCallParam] | None
    """The tool calls generated by the model, such as function calls."""

    reasoning: str | None
@@ -357,47 +357,6 @@ class ChatCompletionRequest(OpenAIBaseModel):

    # --8<-- [end:chat-completion-extra-params]

-    @model_validator(mode="before")
-    @classmethod
-    def _materialize_tool_calls_before(cls, data: Any) -> Any:
-        """Eagerly convert tool_calls generators/iterators to lists.
-
-        Must run before Pydantic field validation so that one-shot
-        generators are not consumed during union type matching of
-        ChatCompletionAssistantMessageParam (which types tool_calls
-        as Iterable[...]).
-        """
-        if not isinstance(data, dict):
-            return data
-        messages = data.get("messages")
-        if not isinstance(messages, list):
-            return data
-        for msg in messages:
-            if not isinstance(msg, dict):
-                continue
-            tool_calls = msg.get("tool_calls")
-            if tool_calls is not None and not isinstance(tool_calls, list):
-                msg["tool_calls"] = list(tool_calls)
-        return data
-
-    @model_validator(mode="after")
-    def _materialize_tool_calls_after(self) -> "ChatCompletionRequest":
-        """Convert Pydantic ValidatorIterator wrappers back to lists.
-
-        Even after the "before" validator converts iterables to lists,
-        Pydantic re-wraps them in a ValidatorIterator when validating
-        against ChatCompletionAssistantMessageParam's Iterable[...] type.
-        This "after" pass materialises those wrappers so downstream code
-        (tokenizers, model_dump_json) always sees plain lists.
-        """
-        for msg in self.messages:
-            if not isinstance(msg, dict):
-                continue
-            tool_calls = msg.get("tool_calls")
-            if tool_calls is not None and not isinstance(tool_calls, list):
-                msg["tool_calls"] = list(tool_calls)
-        return self
-
    def build_chat_params(
        self,
        default_template: str | None,
@@ -414,7 +414,6 @@ class INCConfig(QuantizationConfig):

    def apply_xpu_w4a16_quant_layer(self, layer, prefix: str):
        weight_bits, group_size, sym = self.get_layer_config(layer, prefix)
-
        if not self.check_quantized(weight_bits):
            if isinstance(layer, (LinearBase, ParallelLMHead)):
                return UnquantizedLinearMethod()
@@ -438,27 +437,6 @@ class INCConfig(QuantizationConfig):
            )
        return None

-    def apply_cpu_w4a16_quant_layer(self, layer, prefix: str):
-        weight_bits, group_size, sym = self.get_layer_config(layer, prefix)
-        if not self.check_quantized(weight_bits):
-            if isinstance(layer, (LinearBase, ParallelLMHead)):
-                return UnquantizedLinearMethod()
-            else:
-                return None
-
-        if weight_bits != 4:
-            raise NotImplementedError(
-                f"INC on CPU only supports 4-bit quantization, "
-                f"got weight_bits={weight_bits}."
-            )
-        if not sym:
-            raise NotImplementedError(
-                "INC W4A16 on CPU only supports symmetric quantization for now."
-            )
-        if isinstance(layer, (LinearBase, ParallelLMHead)):
-            return self.apply_gptq_quant_layer(layer, prefix)
-        return None
-
    def get_quant_method(self, layer: torch.nn.Module, prefix: str):
        if prefix and self.extra_config:
            for layer_name in self.extra_config:
@@ -468,21 +446,11 @@ class INCConfig(QuantizationConfig):
                    return UnquantizedLinearMethod()
        if current_platform.is_xpu():
            return self.apply_xpu_w4a16_quant_layer(layer, prefix)
-        is_gptq = "gptq" in self.packing_format or "gptq" in self.backend
-        if current_platform.is_cpu() and is_gptq:
-            return self.apply_cpu_w4a16_quant_layer(layer, prefix)
-        if is_gptq:
+        if "gptq" in self.packing_format or "gptq" in self.backend:
            return self.apply_gptq_quant_layer(layer, prefix)
        if "awq" in self.packing_format or "awq" in self.backend:
            return self.apply_awq_quant_layer(layer, prefix)

-        raise NotImplementedError(
-            f"Unsupported quantization configuration for layer '{prefix}'. "
-            f"Platform: CPU={current_platform.is_cpu()}. "
-            f"Platform: XPU={current_platform.is_xpu()}. "
-            f"Format: {self.packing_format}, Backend: {self.backend}."
-        )
-
    @classmethod
    def override_quantization_method(
        cls, hf_quant_cfg, user_quant, hf_config=None
@@ -162,7 +162,3 @@ try:
    quant_dequant_mxfp4 = torch.ops.vllm.quant_dequant_mxfp4
 except AttributeError as error:
    raise error
-
-
-def xpu_mxfp4_quantize(x: torch.Tensor) -> tuple[torch.Tensor, torch.Tensor]:
-    return torch.ops.vllm.xpu_mxfp4_quantize(x)
@@ -1050,17 +1050,9 @@ class MiniCPMVBaseModel(nn.Module, SupportsMultiModal, SupportsPP):
                quant_config=quant_config,
                prefix=maybe_prefix(prefix, "resampler"),
            )
-            self._resampler_moved = False

        self.make_empty_intermediate_tensors = self.llm.make_empty_intermediate_tensors

-    def _ensure_resampler_device(self) -> None:
-        if self._resampler_moved:
-            return
-        # Only move device, DO NOT touch dtype (fp8 quant needs its own dtype)
-        self.resampler.to(current_platform.device_type)
-        self._resampler_moved = True
-
    def _parse_and_validate_vision_input(
        self,
        modality: str,
@@ -1179,9 +1171,7 @@ class MiniCPMVBaseModel(nn.Module, SupportsMultiModal, SupportsPP):

    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
        loader = AutoWeightsLoader(self)
-        loaded = loader.load_weights(weights)
-        self._ensure_resampler_device()
-        return loaded
+        return loader.load_weights(weights)

    def get_mm_mapping(self) -> MultiModelKeys:
        """
@@ -1286,7 +1276,9 @@ class MiniCPMV2_0(MiniCPMVBaseModel):
                prefix=prefix,
            )

-        return resampler.to(dtype=torch.get_default_dtype())
+        return resampler.to(
+            device=current_platform.device_type, dtype=torch.get_default_dtype()
+        )

    def get_vision_hidden_states(self, data: MiniCPMVImagePixelInputs) -> torch.Tensor:
        pixel_values = data["pixel_values"]
@@ -1367,7 +1359,9 @@ class MiniCPMV2_5(MiniCPMVBaseModel, SupportsLoRA):
                prefix=prefix,
            )

-        return resampler.to(dtype=torch.get_default_dtype())
+        return resampler.to(
+            device=current_platform.device_type, dtype=torch.get_default_dtype()
+        )

    def get_vision_hidden_states(self, data: MiniCPMVImagePixelInputs) -> torch.Tensor:
        pixel_values = data["pixel_values"]
@@ -1458,8 +1452,11 @@ class MiniCPMV2_6(MiniCPMVBaseModel, SupportsLoRA):
                quant_config=quant_config,
                prefix=prefix,
            )
-
-        return resampler.to(dtype=torch.get_default_dtype())
+        target_device = current_platform.device_type
+        target_dtype = torch.get_default_dtype()
+        if any(p.is_meta for p in resampler.parameters()):
+            return resampler.to_empty(device=target_device).to(dtype=target_dtype)
+        return resampler.to(device=target_device, dtype=target_dtype)

    def get_vision_hidden_states(self, data: MiniCPMVImagePixelInputs) -> torch.Tensor:
        pixel_values = data["pixel_values"]
@@ -1494,9 +1491,7 @@ class MiniCPMV2_6(MiniCPMVBaseModel, SupportsLoRA):

    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
        loader = AutoWeightsLoader(self, skip_prefixes=["apm.", "audio", "tts"])
-        loaded = loader.load_weights(weights)
-        self._ensure_resampler_device()
-        return loaded
+        return loader.load_weights(weights)


 class MiniCPMV4_0(MiniCPMVBaseModel, SupportsLoRA):
@@ -1556,7 +1551,10 @@ class MiniCPMV4_0(MiniCPMVBaseModel, SupportsLoRA):
                quant_config=quant_config,
                prefix=prefix,
            )
-        return resampler.to(dtype=torch.get_default_dtype())
+
+        return resampler.to(
+            device=current_platform.device_type, dtype=torch.get_default_dtype()
+        )

    def get_vision_hidden_states(self, data: MiniCPMVImagePixelInputs) -> torch.Tensor:
        pixel_values = data["pixel_values"]
@@ -1591,9 +1589,7 @@ class MiniCPMV4_0(MiniCPMVBaseModel, SupportsLoRA):

    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
        loader = AutoWeightsLoader(self, skip_prefixes=["apm.", "audio", "tts"])
-        loaded = loader.load_weights(weights)
-        self._ensure_resampler_device()
-        return loaded
+        return loader.load_weights(weights)


 class MiniCPMV4_5(MiniCPMVBaseModel, SupportsLoRA):
@@ -1653,8 +1649,11 @@ class MiniCPMV4_5(MiniCPMVBaseModel, SupportsLoRA):
                quant_config=quant_config,
                prefix=prefix,
            )
-
-        return resampler.to(dtype=torch.get_default_dtype())
+        target_device = current_platform.device_type
+        target_dtype = torch.get_default_dtype()
+        if any(p.is_meta for p in resampler.parameters()):
+            return resampler.to_empty(device=target_device).to(dtype=target_dtype)
+        return resampler.to(device=target_device, dtype=target_dtype)

    def get_vision_hidden_states(self, data: MiniCPMVImagePixelInputs) -> torch.Tensor:
        pixel_values = data["pixel_values"]
@@ -1693,9 +1692,7 @@ class MiniCPMV4_5(MiniCPMVBaseModel, SupportsLoRA):

    def load_weights(self, weights: Iterable[tuple[str, torch.Tensor]]) -> set[str]:
        loader = AutoWeightsLoader(self, skip_prefixes=["apm.", "audio", "tts"])
-        loaded = loader.load_weights(weights)
-        self._ensure_resampler_device()
-        return loaded
+        return loader.load_weights(weights)


 _SUPPORT_VERSION = {
@@ -37,7 +37,6 @@ from vllm.model_executor.models.nemotron_h import NemotronHForCausalLM
 from vllm.model_executor.models.parakeet import ParakeetExtractor, ProjectedParakeet
 from vllm.model_executor.models.radio import RadioModel, calc_seq_lens
 from vllm.model_executor.models.utils import (
-    WeightsMapper,
    init_vllm_registered_model,
    maybe_prefix,
 )
@@ -904,12 +903,6 @@ class NemotronH_Nano_VL_V2(
    requires_sequential_video_encoding = True
    """Temporarily needed for dynamic res video w/ conv3d, doesn't support bs>1 yet"""

-    hf_to_vllm_mapper = WeightsMapper(
-        orig_to_new_prefix={
-            "language_model.backbone": "language_model.model",
-        },
-    )
-
    @classmethod
    def get_placeholder_str(cls, modality: str, i: int) -> str | None:
        if modality.startswith("image"):
@@ -1031,9 +1031,7 @@ class FlashAttentionImpl(AttentionImpl):
            window_size=sliding_window_size,
            softcap=self.logits_soft_cap,
            fa_version=self.vllm_flash_attn_version,
-            q_descale=layer._q_scale.expand(descale_shape)
-            if self.supports_quant_query_input
-            else None,
+            q_descale=layer._q_scale.expand(descale_shape),
            k_descale=layer._k_scale.expand(descale_shape),
            v_descale=layer._v_scale.expand(descale_shape),
            num_splits=1 if self.batch_invariant_enabled else 0,
@@ -799,7 +799,6 @@ class OutputProcessor:
        assert req_state.stats is not None
        iteration_stats.update_from_finished_request(
            finish_reason=finish_reason,
-            request_id=req_state.external_req_id,
            num_prompt_tokens=req_state.prompt_len,
            max_tokens_param=req_state.max_tokens_param,
            req_stats=req_state.stats,
@@ -79,6 +79,7 @@ class PrepareStoreOutput:
@dataclass
 class OffloadingEvent:
    keys: list[OffloadKey]
+    block_size: int
    medium: str
    # True if blocks are removed, False if stored
    removed: bool
@@ -33,10 +33,12 @@ class CPUOffloadingManager(OffloadingManager):

    def __init__(
        self,
+        block_size: int,
        num_blocks: int,
        cache_policy: Literal["lru", "arc"] = "lru",
        enable_events: bool = False,
    ):
+        self.block_size: int = block_size
        self.medium: str = CPULoadStoreSpec.medium()
        self._num_blocks: int = num_blocks
        self._num_allocated_blocks: int = 0
@@ -143,6 +145,7 @@ class CPUOffloadingManager(OffloadingManager):
            self.events.append(
                OffloadingEvent(
                    keys=to_evict,
+                    block_size=self.block_size,
                    medium=self.medium,
                    removed=True,
                )
@@ -185,6 +188,7 @@ class CPUOffloadingManager(OffloadingManager):
            self.events.append(
                OffloadingEvent(
                    keys=stored_keys,
+                    block_size=self.block_size,
                    medium=self.medium,
                    removed=False,
                )
@@ -60,7 +60,12 @@ class CPUOffloadingSpec(OffloadingSpec):
                kv_events_config is not None and kv_events_config.enable_kv_cache_events
            )

+            assert len(self.gpu_block_size) == 1
+            gpu_block_size = self.gpu_block_size[0]
+            offloaded_block_size = gpu_block_size * self.block_size_factor
+
            self._manager = CPUOffloadingManager(
+                block_size=offloaded_block_size,
                num_blocks=self.num_blocks,
                cache_policy=self.eviction_policy,  # type: ignore[arg-type]
                enable_events=enable_events,
@@ -225,7 +225,6 @@ class FinishedRequestStats:
    """Stats associated with a finished request."""

    finish_reason: "FinishReason"
-    request_id: str | None = None
    e2e_latency: float = 0.0
    num_prompt_tokens: int = 0
    num_generation_tokens: int = 0
@@ -428,7 +427,6 @@ class IterationStats:
    def update_from_finished_request(
        self,
        finish_reason: "FinishReason",
-        request_id: str,
        num_prompt_tokens: int,
        max_tokens_param: int | None,
        req_stats: RequestStateStats,
@@ -460,7 +458,6 @@ class IterationStats:

        finished_req = FinishedRequestStats(
            finish_reason=finish_reason,
-            request_id=request_id,
            e2e_latency=e2e_latency,
            num_prompt_tokens=num_prompt_tokens,
            num_generation_tokens=req_stats.num_generation_tokens,