[Bug]: Unable to run Qwen3.5 on RTX5090

[YiJunSachs]

Your current environment

The output of python collect_env.py

CUDA:12.8
Torch: 2.10
VLLM: 0.17.0

🐛 Describe the bug

Running log:
(EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100] torch.AcceleratorError: CUDA error: the provided PTX was compiled with an unsupported toolchain. (EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100] Search for cudaErrorUnsupportedPtxVersion in https://docs.nvidia.com/cuda/cuda-runtime-api/group__CUDART__TYPES.html for more information. (EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100] CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect. (EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100] For debugging consider passing CUDA_LAUNCH_BLOCKING=1 (EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100] Compile with TORCH_USE_CUDA_DSA to enable device-side assertions. (EngineCore_DP0 pid=384010) ERROR 03-09 13:22:08 [core.py:1100]

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[NovaShen555]

use nightly version
https://docs.vllm.ai/projects/recipes/en/latest/Qwen/Qwen3.5.html

[NovaShen555]

same issue ?
#36234

[Banner-Wang]

I fixed the issue by installing vLLM with the PyTorch nightly CUDA 12.8 wheels:

pip install --pre --upgrade vllm --extra-index-url https://download.pytorch.org/whl/nightly/cu128

[YiJunSachs]

I fixed the issue by installing vLLM with the PyTorch nightly CUDA 12.8 wheels:

pip install --pre --upgrade vllm --extra-index-url https://download.pytorch.org/whl/nightly/cu128

Thanks,bro.It can start the service successfully. But have u encountered the situation that the inference process logs RuntimeError: Triton Error [CUDA]: out of memory