Stable Diffusion: “Torch Is Unable To Use GPU,” Meaning

Troubleshooting GPU Issues with Stable Diffusion's Torch

Stable Diffusion Torch Is Unable To Use GPU Meaning

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Stable Diffusion is among the best AI image creators, like the Dall-E and MidJourney. They are helping millions of users create images in no time with just a short text prompt description.

However, users sometimes face issues, especially python users, encountering different bugs or issues when starting the app. 

In the below read, we will discuss what the “Torch is unable to use GPU” is in python and how you can fix it.

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Torch is Unable to Use GPU

For python users, this error occurs when the GPU is not supporting the app fully for several reasons. Many users need help with this issue while running Stable Diffusion on their Python systems. There are many ways to solve this issue.

Users have been trying various issues like upgrading their Python framework or python to the latest 3.10.8 version, which has been helping them solve this issue.

Moreover, changing the GPU model to different settings is also helping many users in solving this issue.

How to Solve it

There are many ways to solve this error. You can also try the below steps to see if they work:

How to Solve the Stable Diffusion Torch Is Unable To Use GPU Issue?

  • Delete the “Venv” folder in the Stable Diffusion folder and start the web.ui-user.bat. This will take a few minutes, but I will reinstall “Venv .”Close Webui, as it will also crash.
  • Again, go to the Venv > script, click the folder path, and type CMD for the command window to open. Type: pip installs fastapi ==0.90.1 and type python.exe –m pip install –upgrade pip.

This will solve the issue.

Does Torch Support GPU?

The torch package can add support to the CUDA tensor types to implement similar functions as the CPU tensors. But they use GPU for the computations. You may always import it, as it is mostly lazily initialized.


The “Torch is unable to use GPU” can be an unfortunate error requiring rectification for the Stable Diffusion to run on a Python. However, users have been trying various ways to solve this issue, so you may see which one suits you the best by trying different ways, as mentioned above.