KBlueLeaf/5090wheels

utils wheels for RTX5090

As title, lot of third party librarys which are important for running NN lack prebuilt wheel for RTX5090, so I decide to compile them bymyself and upload them here.

Use At Your Own Risks, Check Official Release To See if There Are Any Official Supports On Your HW Regularly

Inlcuded Library

• Flash Attention
• Xformers (with cutlass/flash attention built-in)
• NATTEN
• SageAttention
• vLLM

IMPORTANT NOTE

1. I only ensure those wheels can works on RTX50 series (sm120) GPUs, if your platform is mixed with different sm/cu arch GPUs, you may still need to compile them by yourself
2. Env
   • Pytorch: 2.7.0
   • CUDA: 12.8(12.8.1)
   • CUDNN: 9.8
   • Compiler: GCC13
   • Tested platform: Ubuntu 22.04 and 24.04
   • CPU arch: amd64 (x86-64)
3. Not all the wheels are fully functional (due to deps things or source implementation), for example, cutlass w8a8 scaled mm is not working in vllm, you need to use VLLM_TEST_FORCE_FP8_MARLIN=1 to make VLLM works normally with fp8 weight quantization. If you are using flash attention, you need VLLM_FLASH_ATTN_VERSION=2 to make it work on 5090
4. If you meet any problem or need wheels for specific setup you can open discussion, but I can't ensure I will do it or not.

Tips

• Install triton==3.3.1 for better RTX50 series support
• Install nvidia-nccl-cu12==2.26.5 for correct multi-gpu deps for RTX50 series
  • Torch 2.7.0 use 2.26.2 in their requirements which is not compatibile with RTX50 series, you should install this from pypi directly with pip isntall nvidia-nccl-cu12>2.26.2
• I build all those wheel with python -m build -n -w . which is more suitable in modern python packaging, I recommend all the user who want to compile those wheel by themselves follow this scheme. (No matter the project use pyproject or setup.py, build package will works)