vllm-project · youkaichao · Aug 29, 2025 · Jul 2, 2025 · Jul 2, 2025 · Jul 8, 2025
@@ -45,8 +45,8 @@ set(HIP_SUPPORTED_ARCHS "gfx906;gfx908;gfx90a;gfx942;gfx950;gfx1030;gfx1100;gfx1
 # requirements.txt files and should be kept consistent.  The ROCm torch
 # versions are derived from docker/Dockerfile.rocm
 #
-set(TORCH_SUPPORTED_VERSION_CUDA "2.7.1")
-set(TORCH_SUPPORTED_VERSION_ROCM "2.7.0")
+set(TORCH_SUPPORTED_VERSION_CUDA "2.8.0")
+set(TORCH_SUPPORTED_VERSION_ROCM "2.8.0")
 
 #
 # Try to find python package with an executable that exactly matches

diff --git a/docker/Dockerfile b/docker/Dockerfile
@@ -160,6 +160,10 @@ RUN --mount=type=cache,target=/root/.cache/uv \
     uv pip install --system -r requirements/cuda.txt \
     --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')
 
+# Build from source to unblock PyTorch 2.8.0 update
+RUN --mount=type=cache,target=/root/.cache/uv \
+    uv pip install --system --no-build-isolation "git+https://github.com/state-spaces/[email protected]"
+
 # cuda arch list used by torch
 # can be useful for both `dev` and `test`
 # explicitly set the list to avoid issues with torch 2.2
@@ -376,6 +380,13 @@ RUN --mount=type=bind,from=build,src=/workspace/dist,target=/vllm-workspace/dist
     uv pip install --system dist/*.whl --verbose \
         --extra-index-url ${PYTORCH_CUDA_INDEX_BASE_URL}/cu$(echo $CUDA_VERSION | cut -d. -f1,2 | tr -d '.')
 
+# TODO (huydhn): Remove this once xformers is released for 2.8.0
+RUN --mount=type=cache,target=/root/.cache/uv bash - <<'BASH'
+    . /etc/environment
+    export TORCH_CUDA_ARCH_LIST='7.0 7.5 8.0 8.9 9.0 10.0 12.0'
+    uv pip install --system --no-build-isolation "git+https://github.com/facebookresearch/[email protected]"
+BASH
+
 # If we need to build FlashInfer wheel before its release:
 # $ # Note we remove 7.0 from the arch list compared to the list below, since FlashInfer only supports sm75+
 # $ export TORCH_CUDA_ARCH_LIST='7.5 8.0 8.9 9.0a 10.0a 12.0'
@@ -483,6 +494,10 @@ ENV UV_INDEX_STRATEGY="unsafe-best-match"
 # Use copy mode to avoid hardlink failures with Docker cache mounts
 ENV UV_LINK_MODE=copy
 
+# Build from source to unblock PyTorch 2.8.0 update
+RUN --mount=type=cache,target=/root/.cache/uv \
+    uv pip install --system --no-build-isolation "git+https://github.com/state-spaces/[email protected]"
+
 # install development dependencies (for testing)
 RUN --mount=type=cache,target=/root/.cache/uv \
     CUDA_MAJOR="${CUDA_VERSION%%.*}"; \

diff --git a/pyproject.toml b/pyproject.toml
@@ -6,7 +6,7 @@ requires = [
     "packaging>=24.2",
     "setuptools>=77.0.3,<80.0.0",
     "setuptools-scm>=8.0",
-    "torch == 2.7.1",
+    "torch == 2.8.0",
     "wheel",
     "jinja2",
 ]

diff --git a/requirements/build.txt b/requirements/build.txt
@@ -4,7 +4,8 @@ ninja
 packaging>=24.2
 setuptools>=77.0.3,<80.0.0
 setuptools-scm>=8
-torch==2.7.1
+torch==2.8.0
 wheel
 jinja2>=3.1.6
 regex
+build
diff --git a/requirements/cpu.txt b/requirements/cpu.txt
@@ -9,17 +9,16 @@ packaging>=24.2
 setuptools>=77.0.3,<80.0.0
 --extra-index-url https://download.pytorch.org/whl/cpu
 torch==2.6.0+cpu; platform_machine == "x86_64" # torch>2.6.0+cpu has performance regression on x86 platform, see https://github.com/pytorch/pytorch/pull/151218
-torch==2.7.0; platform_system == "Darwin"
-torch==2.7.0; platform_machine == "ppc64le"
-torch==2.6.0; platform_machine == "aarch64" # for arm64 CPUs, torch 2.7.0 has a issue: https://github.com/vllm-project/vllm/issues/17960
+torch==2.8.0; platform_system == "Darwin"
+torch==2.8.0; platform_machine == "ppc64le" or platform_machine == "aarch64"
 
 # required for the image processor of minicpm-o-2_6, this must be updated alongside torch
 torchaudio; platform_machine != "ppc64le" and platform_machine != "s390x"
-torchaudio==2.7.0; platform_machine == "ppc64le"
+torchaudio==2.8.0; platform_machine == "ppc64le"
 
 # required for the image processor of phi3v, this must be updated alongside torch
 torchvision; platform_machine != "ppc64le" and platform_machine != "s390x"
-torchvision==0.22.0; platform_machine == "ppc64le"
+torchvision==0.23.0; platform_machine == "ppc64le"
 datasets # for benchmark scripts
 
 # Intel Extension for PyTorch, only for x86_64 CPUs

diff --git a/requirements/cuda.txt b/requirements/cuda.txt
@@ -6,9 +6,10 @@ numba == 0.61.2; python_version > '3.9'
 
 # Dependencies for NVIDIA GPUs
 ray[cgraph]>=2.48.0 # Ray Compiled Graph, required for pipeline parallelism in V1.
-torch==2.7.1
-torchaudio==2.7.1
+torch==2.8.0
+torchaudio==2.8.0
 # These must be updated alongside torch
-torchvision==0.22.1 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
+torchvision==0.23.0 # Required for phi3v processor. See https://github.com/pytorch/vision?tab=readme-ov-file#installation for corresponding version
+# TODO (huydhn): Re-enable this once xformers is released for 2.8.0
 # https://github.com/facebookresearch/xformers/releases/tag/v0.0.31
-xformers==0.0.31; platform_system == 'Linux' and platform_machine == 'x86_64'  # Requires PyTorch >= 2.7
+# xformers==0.0.31; platform_system == 'Linux' and platform_machine == 'x86_64'  # Requires PyTorch >= 2.7
diff --git a/requirements/rocm-build.txt b/requirements/rocm-build.txt
@@ -1,10 +1,10 @@
 # Common dependencies
 -r common.txt
 
---extra-index-url https://download.pytorch.org/whl/rocm6.2.4
-torch==2.7.0
-torchvision==0.22.0
-torchaudio==2.7.0
+--extra-index-url https://download.pytorch.org/whl/rocm6.3
+torch==2.8.0
+torchvision==0.23.0
+torchaudio==2.8.0
 
 triton==3.2
 cmake>=3.26.1,<4

diff --git a/requirements/test.in b/requirements/test.in
@@ -22,9 +22,9 @@ sentence-transformers # required for embedding tests
 soundfile # required for audio tests
 jiwer # required for audio tests
 timm # required for internvl test
-torch==2.7.1
-torchaudio==2.7.1
-torchvision==0.22.1
+torch==2.8.0
+torchaudio==2.8.0
+torchvision==0.23.0
 transformers_stream_generator # required for qwen-vl test
 mamba_ssm==2.2.5 # required for plamo2 test
 matplotlib # required for qwen-vl test
@@ -54,4 +54,4 @@ runai-model-streamer==0.11.0
 runai-model-streamer-s3==0.11.0
 fastsafetensors>=0.1.10
 pydantic>=2.10 # 2.9 leads to error on python 3.10
-terratorch==1.1rc2 # required for PrithviMAE test
+terratorch==1.1rc2 # required for PrithviMAE test
diff --git a/requirements/test.txt b/requirements/test.txt
@@ -544,42 +544,42 @@ numpy==1.26.4
     #   tritonclient
     #   vocos
     #   xarray
-nvidia-cublas-cu12==12.8.3.14
+nvidia-cublas-cu12==12.8.4.1
     # via
     #   nvidia-cudnn-cu12
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cuda-cupti-cu12==12.8.57
+nvidia-cuda-cupti-cu12==12.8.90
     # via torch
-nvidia-cuda-nvrtc-cu12==12.8.61
+nvidia-cuda-nvrtc-cu12==12.8.93
     # via torch
-nvidia-cuda-runtime-cu12==12.8.57
+nvidia-cuda-runtime-cu12==12.8.90
     # via torch
-nvidia-cudnn-cu12==9.7.1.26
+nvidia-cudnn-cu12==9.10.2.21
     # via torch
-nvidia-cufft-cu12==11.3.3.41
+nvidia-cufft-cu12==11.3.3.83
     # via torch
-nvidia-cufile-cu12==1.13.0.11
+nvidia-cufile-cu12==1.13.1.3
     # via torch
-nvidia-curand-cu12==10.3.9.55
+nvidia-curand-cu12==10.3.9.90
     # via torch
-nvidia-cusolver-cu12==11.7.2.55
+nvidia-cusolver-cu12==11.7.3.90
     # via torch
-nvidia-cusparse-cu12==12.5.7.53
+nvidia-cusparse-cu12==12.5.8.93
     # via
     #   nvidia-cusolver-cu12
     #   torch
-nvidia-cusparselt-cu12==0.6.3
+nvidia-cusparselt-cu12==0.7.1
     # via torch
-nvidia-nccl-cu12==2.26.2
+nvidia-nccl-cu12==2.27.3
     # via torch
-nvidia-nvjitlink-cu12==12.8.61
+nvidia-nvjitlink-cu12==12.8.93
     # via
     #   nvidia-cufft-cu12
     #   nvidia-cusolver-cu12
     #   nvidia-cusparse-cu12
     #   torch
-nvidia-nvtx-cu12==12.8.55
+nvidia-nvtx-cu12==12.8.90
     # via torch
 omegaconf==2.3.0
     # via
@@ -1074,7 +1074,7 @@ tomli==2.2.1
     # via schemathesis
 tomli-w==1.2.0
     # via schemathesis
-torch==2.7.1+cu128
+torch==2.8.0+cu128
     # via
     #   -r requirements/test.in
     #   accelerate
@@ -1104,7 +1104,7 @@ torch==2.7.1+cu128
     #   torchvision
     #   vector-quantize-pytorch
     #   vocos
-torchaudio==2.7.1+cu128
+torchaudio==2.8.0+cu128
     # via
     #   -r requirements/test.in
     #   encodec
@@ -1117,7 +1117,7 @@ torchmetrics==1.7.4
     #   pytorch-lightning
     #   terratorch
     #   torchgeo
-torchvision==0.22.1+cu128
+torchvision==0.23.0+cu128
     # via
     #   -r requirements/test.in
     #   lightly
@@ -1159,7 +1159,7 @@ transformers==4.55.0
     #   transformers-stream-generator
 transformers-stream-generator==0.0.5
     # via -r requirements/test.in
-triton==3.3.1
+triton==3.4.0
     # via
     #   mamba-ssm
     #   torch

diff --git a/tests/distributed/test_sequence_parallel.py b/tests/distributed/test_sequence_parallel.py
@@ -292,7 +292,7 @@ def _compare_sp(
     # TODO support other models
     # [LANGUAGE GENERATION]
     "meta-llama/Llama-3.2-1B-Instruct",
-    "RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8"
+    "RedHatAI/Meta-Llama-3.1-8B-Instruct-FP8",
 ]
 
 

diff --git a/tests/entrypoints/openai/test_vision.py b/tests/entrypoints/openai/test_vision.py
@@ -36,11 +36,11 @@
     ],
     [
         "The image shows a Venn diagram with three over",
-        "The image shows a Venn diagram with three intersect",
+        "This image shows a Venn diagram with three over",
     ],
     [
         "This image displays a gradient of colors ranging from",
-        "The image displays a gradient of colors ranging from",
+        "This image displays a gradient of colors transitioning from",
     ],
 ]
 

@@ -87,6 +87,9 @@ def test_chatglm3_lora_tp4(chatglm3_lora_files):
 @multi_gpu_test(num_gpus=4)
 @create_new_process_for_each_test()
 def test_chatglm3_lora_tp4_fully_sharded_loras(chatglm3_lora_files):
+    # https://github.com/NVIDIA/nccl/issues/1790, set a lower value for
+    # gpu_memory_utilization here because NCCL >= 2.26.3 seems to use
+    # more GPU memory causing vLLM to OOM
     llm = vllm.LLM(MODEL_PATH,
                    max_model_len=1024,
                    enable_lora=True,
@@ -95,7 +98,8 @@ def test_chatglm3_lora_tp4_fully_sharded_loras(chatglm3_lora_files):
                    tensor_parallel_size=4,
                    trust_remote_code=True,
                    fully_sharded_loras=True,
-                   enable_chunked_prefill=True)
+                   enable_chunked_prefill=True,
+                   gpu_memory_utilization=0.85)
     output1 = do_sample(llm, chatglm3_lora_files, lora_id=1)
     for i in range(len(EXPECTED_LORA_OUTPUT)):
         assert output1[i] == EXPECTED_LORA_OUTPUT[i]