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[Docs] Fix the outdated URL for installing from vLLM binaries (#21523)

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Signed-off-by: Kay Yan <kay.yan@daocloud.io>
Co-authored-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>
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Kay Yan 2025-07-29 19:56:27 +08:00 committed by GitHub
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3
docs/contributing/ci/update_pytorch_version.md
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@ -57,8 +57,7 @@ cc the PyTorch release team to initiate discussion on how to address them.
## Update CUDA version
The PyTorch release matrix includes both stable and experimental [CUDA versions](https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-matrix). Due to limitations, only the latest stable CUDA version (for example,
`torch2.7.0+cu12.6`) is uploaded to PyPI. However, vLLM may require a different CUDA version,
The PyTorch release matrix includes both stable and experimental [CUDA versions](https://github.com/pytorch/pytorch/blob/main/RELEASE.md#release-compatibility-matrix). Due to limitations, only the latest stable CUDA version (for example, torch `2.7.1+cu126`) is uploaded to PyPI. However, vLLM may require a different CUDA version,
such as 12.8 for Blackwell support.
This complicates the process as we cannot use the out-of-the-box
`pip install torch torchvision torchaudio` command. The solution is to use

8
docs/getting_started/installation/gpu/cuda.inc.md
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@ -38,10 +38,10 @@ We recommend leveraging `uv` to [automatically select the appropriate PyTorch in
As of now, vLLM's binaries are compiled with CUDA 12.8 and public PyTorch release versions by default. We also provide vLLM binaries compiled with CUDA 12.6, 11.8, and public PyTorch release versions:
```bash
# Install vLLM with CUDA 11.8.
export VLLM_VERSION=0.6.1.post1
export PYTHON_VERSION=312
uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu118-cp${PYTHON_VERSION}-cp${PYTHON_VERSION}-manylinux1_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu118
# Install vLLM with a specific CUDA version (e.g., 11.8 or 12.6).
export VLLM_VERSION=$(curl -s https://api.github.com/repos/vllm-project/vllm/releases/latest | jq -r .tag_name | sed 's/^v//')
export CUDA_VERSION=118 # or 126
uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu${CUDA_VERSION}-cp38-abi3-manylinux1_x86_64.whl --extra-index-url https://download.pytorch.org/whl/cu${CUDA_VERSION}
```
[](){ #install-the-latest-code }