How To Fix Stable Diffusion RuntimeError: Torch is not able to use GPU

Stuck with an AMD GPU and the pesky «Torch is not able to use GPU» error in Stable Diffusion? Don’t despair! Here’s your quick guide to bypass the hurdles and unleash your AI creativity.

Problem: A1111, the popular Stable Diffusion interface, isn’t optimized for AMD GPUs. PyTorch, its backbone, prefers NVIDIA’s CUDA.

How To Fix Stable Diffusion RuntimeError: Torch is not able to use GPU

  • DirectML Fork: Embrace the DirectML fork of A1111. This community-built version thrives on AMD hardware. (Link in original article)
  • SDNext/ROCm: Venture into SDNext, a robust fork with better AMD support. For the advanced, consider ROCm on Linux (check GPU compatibility).
  • Manage Expectations: Even with an active GPU, speed bumps might occur. Monitor usage with AMD’s control center or Task Manager. Remember, SDNext might offer smoother performance.


  • PyTorch 1.7: Using this version? Add «—use-directml» to your command line arguments. This might unlock your AMD potential.


Don’t go it alone! Dive into resources like YouTube and AMD’s community forums. Learn from others’ experiences and troubleshoot like a pro.

Conquering AI challenges takes patience and a bit of trial and error. Embrace the journey, and soon you’ll be seamlessly generating stunning art with your AMD GPU and Stable Diffusion. Happy diffusing!

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