vllm - 💡(How to fix) Fix [Installation]: torch 2.11 is not supported [1 participants]

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vllm-project/vllm#38431Fetched 2026-04-08 01:45:41
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Root Cause

#27 8.133   × No solution found when resolving dependencies:
#27 8.133   ╰─▶ Because only the following versions of nvidia-cutlass-dsl are available:
#27 8.133           nvidia-cutlass-dsl<=4.4.0.dev1
#27 8.133           nvidia-cutlass-dsl==4.4.0
#27 8.133           nvidia-cutlass-dsl==4.4.1
#27 8.133           nvidia-cutlass-dsl==4.4.2
#27 8.133       and nvidia-cutlass-dsl==4.4.0.dev1 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude
#27 8.133       that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1.
#27 8.133       And because there is no version of
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 cannot be used.
#27 8.133       And because nvidia-cutlass-dsl==4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0 and all versions of
#27 8.133       nvidia-cutlass-dsl-libs-base depend on cuda-python==12.9.0, we
#27 8.133       can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.1 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because nvidia-cutlass-dsl==4.4.1 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.1 and
#27 8.133       nvidia-cutlass-dsl-libs-base>=4.4.1 depends on cuda-python==12.9.0,
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because only cuda-python==12.9.0 is available and
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0, we can
#27 8.133       conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-bindings<12.10.dev0. (1)
#27 8.133 
#27 8.133       Because cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0
#27 8.133       and only cuda-python==12.9.0 is available, we can conclude that
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because nvidia-cutlass-dsl-libs-base==4.4.2 depends on
#27 8.133       cuda-python==12.9.0 and nvidia-cutlass-dsl==4.4.2 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.2, we can conclude that
#27 8.133       nvidia-cutlass-dsl==4.4.2 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because we know from (1) that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2
#27 8.133       depends on cuda-bindings<12.10.dev0, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because torch==2.10.0+cu130 depends on cuda-bindings{sys_platform ==
#27 8.133       'linux'}==13.0.3 and only the following versions of torch are available:
#27 8.133           torch<2.10.0
#27 8.133           torch>=2.10.0+cu130
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1 and torch==2.10.0
#27 8.133       are incompatible.
#27 8.133       And because vllm==0.18.0+cu130 depends on torch==2.10.0 and
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1, we can conclude that vllm==0.18.0+cu130
#27 8.133       cannot be used.
#27 8.133       And because only vllm==0.18.0+cu130 is available and you require vllm,
#27 8.133       we can conclude that your requirements are unsatisfiable.
#27 8.133 
#27 8.133       hint: `torch` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (torch>=2.10.0,<2.10.0+cu130). A
#27 8.133       compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.
#27 8.133 
#27 8.133       hint: `nvidia-cutlass-dsl-libs-base` was requested with a pre-release
#27 8.133       marker (e.g., nvidia-cutlass-dsl-libs-base==4.4.0.dev1), but
#27 8.133       pre-releases weren't enabled (try: `--prerelease=allow`)
#27 8.133 
#27 8.133       hint: `cuda-python` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (all of:
#27 8.133           cuda-python>=12.8,<12.9.0
#27 8.133           cuda-python>12.9.0
#27 8.133       ). A compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.

Code Example

#27 8.133   × No solution found when resolving dependencies:
#27 8.133   ╰─▶ Because only the following versions of nvidia-cutlass-dsl are available:
#27 8.133           nvidia-cutlass-dsl<=4.4.0.dev1
#27 8.133           nvidia-cutlass-dsl==4.4.0
#27 8.133           nvidia-cutlass-dsl==4.4.1
#27 8.133           nvidia-cutlass-dsl==4.4.2
#27 8.133       and nvidia-cutlass-dsl==4.4.0.dev1 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude
#27 8.133       that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1.
#27 8.133       And because there is no version of
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 cannot be used.
#27 8.133       And because nvidia-cutlass-dsl==4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0 and all versions of
#27 8.133       nvidia-cutlass-dsl-libs-base depend on cuda-python==12.9.0, we
#27 8.133       can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.1 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because nvidia-cutlass-dsl==4.4.1 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.1 and
#27 8.133       nvidia-cutlass-dsl-libs-base>=4.4.1 depends on cuda-python==12.9.0,
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because only cuda-python==12.9.0 is available and
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0, we can
#27 8.133       conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-bindings<12.10.dev0. (1)
#27 8.133 
#27 8.133       Because cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0
#27 8.133       and only cuda-python==12.9.0 is available, we can conclude that
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because nvidia-cutlass-dsl-libs-base==4.4.2 depends on
#27 8.133       cuda-python==12.9.0 and nvidia-cutlass-dsl==4.4.2 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.2, we can conclude that
#27 8.133       nvidia-cutlass-dsl==4.4.2 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because we know from (1) that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2
#27 8.133       depends on cuda-bindings<12.10.dev0, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because torch==2.10.0+cu130 depends on cuda-bindings{sys_platform ==
#27 8.133       'linux'}==13.0.3 and only the following versions of torch are available:
#27 8.133           torch<2.10.0
#27 8.133           torch>=2.10.0+cu130
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1 and torch==2.10.0
#27 8.133       are incompatible.
#27 8.133       And because vllm==0.18.0+cu130 depends on torch==2.10.0 and
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1, we can conclude that vllm==0.18.0+cu130
#27 8.133       cannot be used.
#27 8.133       And because only vllm==0.18.0+cu130 is available and you require vllm,
#27 8.133       we can conclude that your requirements are unsatisfiable.
#27 8.133 
#27 8.133       hint: `torch` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (torch>=2.10.0,<2.10.0+cu130). A
#27 8.133       compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.
#27 8.133 
#27 8.133       hint: `nvidia-cutlass-dsl-libs-base` was requested with a pre-release
#27 8.133       marker (e.g., nvidia-cutlass-dsl-libs-base==4.4.0.dev1), but
#27 8.133       pre-releases weren't enabled (try: `--prerelease=allow`)
#27 8.133 
#27 8.133       hint: `cuda-python` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (all of:
#27 8.133           cuda-python>=12.8,<12.9.0
#27 8.133           cuda-python>12.9.0
#27 8.133       ). A compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.
RAW_BUFFERClick to expand / collapse

Your current environment

#27 8.133   × No solution found when resolving dependencies:
#27 8.133   ╰─▶ Because only the following versions of nvidia-cutlass-dsl are available:
#27 8.133           nvidia-cutlass-dsl<=4.4.0.dev1
#27 8.133           nvidia-cutlass-dsl==4.4.0
#27 8.133           nvidia-cutlass-dsl==4.4.1
#27 8.133           nvidia-cutlass-dsl==4.4.2
#27 8.133       and nvidia-cutlass-dsl==4.4.0.dev1 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude
#27 8.133       that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1.
#27 8.133       And because there is no version of
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0.dev1, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.0 cannot be used.
#27 8.133       And because nvidia-cutlass-dsl==4.4.0 depends on
#27 8.133       nvidia-cutlass-dsl-libs-base==4.4.0 and all versions of
#27 8.133       nvidia-cutlass-dsl-libs-base depend on cuda-python==12.9.0, we
#27 8.133       can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.1 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because nvidia-cutlass-dsl==4.4.1 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.1 and
#27 8.133       nvidia-cutlass-dsl-libs-base>=4.4.1 depends on cuda-python==12.9.0,
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-python==12.9.0.
#27 8.133       And because only cuda-python==12.9.0 is available and
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0, we can
#27 8.133       conclude that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2 depends on
#27 8.133       cuda-bindings<12.10.dev0. (1)
#27 8.133 
#27 8.133       Because cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0
#27 8.133       and only cuda-python==12.9.0 is available, we can conclude that
#27 8.133       cuda-python==12.9.0 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because nvidia-cutlass-dsl-libs-base==4.4.2 depends on
#27 8.133       cuda-python==12.9.0 and nvidia-cutlass-dsl==4.4.2 depends
#27 8.133       on nvidia-cutlass-dsl-libs-base==4.4.2, we can conclude that
#27 8.133       nvidia-cutlass-dsl==4.4.2 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because we know from (1) that nvidia-cutlass-dsl>=4.4.0.dev1,<4.4.2
#27 8.133       depends on cuda-bindings<12.10.dev0, we can conclude that
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1 depends on cuda-bindings<12.10.dev0.
#27 8.133       And because torch==2.10.0+cu130 depends on cuda-bindings{sys_platform ==
#27 8.133       'linux'}==13.0.3 and only the following versions of torch are available:
#27 8.133           torch<2.10.0
#27 8.133           torch>=2.10.0+cu130
#27 8.133       we can conclude that nvidia-cutlass-dsl>=4.4.0.dev1 and torch==2.10.0
#27 8.133       are incompatible.
#27 8.133       And because vllm==0.18.0+cu130 depends on torch==2.10.0 and
#27 8.133       nvidia-cutlass-dsl>=4.4.0.dev1, we can conclude that vllm==0.18.0+cu130
#27 8.133       cannot be used.
#27 8.133       And because only vllm==0.18.0+cu130 is available and you require vllm,
#27 8.133       we can conclude that your requirements are unsatisfiable.
#27 8.133 
#27 8.133       hint: `torch` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (torch>=2.10.0,<2.10.0+cu130). A
#27 8.133       compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.
#27 8.133 
#27 8.133       hint: `nvidia-cutlass-dsl-libs-base` was requested with a pre-release
#27 8.133       marker (e.g., nvidia-cutlass-dsl-libs-base==4.4.0.dev1), but
#27 8.133       pre-releases weren't enabled (try: `--prerelease=allow`)
#27 8.133 
#27 8.133       hint: `cuda-python` was found on https://download.pytorch.org/whl/cu130,
#27 8.133       but not at the requested version (all of:
#27 8.133           cuda-python>=12.8,<12.9.0
#27 8.133           cuda-python>12.9.0
#27 8.133       ). A compatible version may be available on a subsequent index (e.g.,
#27 8.133       https://pypi.org/simple). By default, uv will only consider versions
#27 8.133       that are published on the first index that contains a given package, to
#27 8.133       avoid dependency confusion attacks. If all indexes are equally trusted,
#27 8.133       use `--index-strategy unsafe-best-match` to consider all versions from
#27 8.133       all indexes, regardless of the order in which they were defined.

How you are installing vllm

uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu${CUDA_VERSION}-cp38-abi3-manylinux_2_35_${CPU_ARCH}.whl --extra-index-url https://download.pytorch.org/whl/cu${CUDA_VERSION}"

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extent analysis

Fix Plan

The issue is caused by incompatible dependencies between nvidia-cutlass-dsl and torch. To fix this, we need to ensure that the versions of these packages are compatible.

  • Step 1: Pin the version of torch We need to install a version of torch that is compatible with nvidia-cutlass-dsl. We can do this by specifying the version of torch in the installation command.

uv pip install torch==2.0.0+cu130 --extra-index-url https://download.pytorch.org/whl/cu130


*   **Step 2: Install `vllm` with the correct version of `torch`**
    After installing the correct version of `torch`, we can install `vllm` using the following command:

    ```bash
uv pip install https://github.com/vllm-project/vllm/releases/download/v${VLLM_VERSION}/vllm-${VLLM_VERSION}+cu${CUDA_VERSION}-cp38-abi3-manylinux_2_35_${CPU_ARCH}.whl --extra-index-url https://download.pytorch.org/whl/cu${CUDA_VERSION}
  • Step 3: Verify the installation After installing vllm, we can verify that it is working correctly by running a simple test:

import vllm


    If this command runs without any errors, then `vllm` has been installed correctly.

### Verification
To verify that the fix worked, we can check the versions of `torch` and `nvidia-cutlass-dsl` that are installed:

```bash
pip show torch
pip show nvidia-cutlass-dsl

These commands should show that the versions of torch and nvidia-cutlass-dsl are compatible.

Extra Tips

  • Make sure to always specify the version of torch when installing vllm to ensure that the versions are compatible.

  • If you encounter any issues during installation, try cleaning the cache and reinstalling:

uv pip cache purge uv pip install --no-cache-dir ...

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