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NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation. #3862
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same issue as in lllyasviel/stable-diffusion-webui-forge#2601 @lllyasviel turns out pytorch 2.1.0 isn't compatible with 5000 series GPUs and has to be updated. Lines 30 to 32 in 59f183a
@agapess running Fooocus using Docker after adjusting requirenents_docker.txt to more recent versions might work, but is currently not supported. Docker quickstart: https://github.com/lllyasviel/Fooocus/blob/main/docker.md _Originally posted by @mashb1t in #3835 (reply in thread) |
How long do you reckon it will take until there is a version that supports the 5000 series? |
@tin-co as i've handed over code ownership again to lllyasviel, i really can't tell when he has time to patch it. Feel free to update to a more recent version of pytorch yourself, but as there are only a few basic unit tests which have nothing to do with image generation it's going to be a bumpy ride. |
Xformers need update but i managed to get it going, its pretty pointless for me without xformers to use my stable diffusion but at least its possible |
Is there any fix or workaround on Windows? , looks like with the 50xx Fooocus stop working total |
cuda has many errors, especially with the compatibility of versions with
pitorch, in general this is fixed by updating these two elements, in the
same way the version of pip usually affects it. In any case, you could run
it in Google Colab and see in the log the versions with which it works
safely and then create a development environment with docker, for example,
with version control of the dependencies and work with it
El mar, 4 de feb de 2025, 1:33 p. m., Slider-Override <
***@***.***> escribió:
… Is there any fix or workaround on Windows? , looks like with the 50xx
Fooocus stop working total
RuntimeError: CUDA error: no kernel image is available for execution on
the device
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Hi all! Update from our NVIDIA team. To use PyTorch for Linux x86_64 and Linux SBSA on NVIDIA 5080, 5090 Blackwell RTX GPUs use the latest nightly builds, or the command below. pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128 Stay tuned for further updates Thanks! |
I am using WSL - Ubuntu - everything else is set up and working in Comfyui - I have the latest pytorch nightly from pip install --pre torch torchvision torchaudio --index-url[ https://download.pytorch.org/whl/nightly/cu128] - but when I use Sageattention I get this: |
The nvidia solution has worked for me in Fooocus. I just had to activate Fooocus venv and type the pip command to update torch to the latest version. |
So Fooocus is working with 5080 / 5090 with Nvidia solution and no need for update Fooocus itself? |
No, you just need to activate the Python virtual environment where Fooocus is installed and type the pip command above (it installs the necessary PyTorch updates). For me it worked without problem. And how fast it is with Blackwell architecture! |
on linux or windows |
Linux, using Stability Matrix. Not familiar with windows, but the update concerns Python libraries, so I am not sure it was platform dependent. Pytorch is the key here. |
I need ”for dummies” - level instructions for these virtual enviroment / pip commands to do it, but lets see that when i get 5090 some day :) |
Manually Enable RTX 5090 Support Run the following before running your Python script: pip install cmake ninja git clone --recursive https://github.com/pytorch/pytorch Edit setup.py, find TORCH_CUDA_ARCH_LIST, and add: TORCH_CUDA_ARCH_LIST="8.6+PTX;9.0+PTX;12.0+PTX;12.6+PTX" MAX_JOBS=8 USE_CUDA=1 python setup.py install |
so if i want to use my 5090 on windows, for example i want to use stability matrix with foocus, or pinokio for f5 tts, i have to wait for some pythorch updates? i had similar issues, everything downloaded-> srtipt launched (foocus), gui started, but when i wanted to test the models on my new gpu it said: RuntimeError: CUDA error: no kernel image is available for execution on the device so what can i do to use my card? ps. im really not into coding, i have no idea what when where and how, i know only that i have to have a python on my pc for it to work and still dont know why, i just want to use AI tools (the nvidia marketing is like "its the best AI card" and i cant use AI) |
⚙️ Solution for Fooocus on Windows with NVIDIA 50xx Series (Tested on 5090 with Driver 572.42 Game Ready)This guide explains how to fix compatibility issues for Stability Matrix with Fooocus on Windows using an NVIDIA 50xx series GPU (like the 5090). 🔗 Prerequisites: CUDA 12.8You need CUDA 12.8 installed on your system for this to work.
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Thanks for the great writeup. I'm not a python dev myself, so sorry if i'm using the wrong terminology here, but the same approach works when using the python_embed version of Fooocus on Windows. And i want to confirm that it's working on an RTX 5080. |
Me to, i dont know how to code, its chat gpt generated. Its working very well, and i understood what and how it works, but its not my work. |
Thanks for the detalied guide! It worked for me for RTX 5080, though I think the "activate" command should be executed in the venv\Scripts folder instead |
yess i edited it, thanks for that |
Any solution for linux, I found https://download.pytorch.org/whl/nightly/xpu/torch-2.7.0.dev20250226%2Bxpu-cp310-cp310-linux_x86_64.whl |
For linux it's easy, just use the latest nightly build: |
I just wanted to
What I did is that I used Grok to walk me through. I just told it what I wanted to do, It gave me the commands to fix everything. I got Flux and Foocus to work |
is there an |
What exactly is your problem (and OS)? Fooocus should work just fine now with 50 series now |
Fooocus works fine without xformers using pytorch like |
Me too.who have good idea? |
iv got my 5090 , not working , lot of different error
RuntimeError: CUDA error: no kernel image is available for execution on the device
CUDA kernel errors might be asynchronously reported at some other API call, so the stacktrace below might be incorrect.
For debugging consider passing CUDA_LAUNCH_BLOCKING=1.
Compile with
TORCH_USE_CUDA_DSA
to enable device-side assertions.init.py:215: UserWarning:
NVIDIA GeForce RTX 5090 with CUDA capability sm_120 is not compatible with the current PyTorch installation.
The current PyTorch install supports CUDA capabilities sm_50 sm_60 sm_61 sm_70 sm_75 sm_80 sm_86 sm_90.
If you want to use the NVIDIA GeForce RTX 5090 GPU with PyTorch, please check the instructions at https://pytorch.org/get-started/locally/
Originally posted by @agapess in #3835 (comment)
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