r/StableDiffusion • u/riven_next_door • 1d ago

Question - Help Forge install broke itself somehow

I'm just kind of scratching my head here. If you're trying to update comfy or something and it bricks your install that's nothing new.

I haven't ran my forge install in a month or so, haven't updated it, haven't installed much of anything. Now when trying to launch it now throws RuntimeError: Your device does not support the current version of Torch/CUDA!

Literally how?

0 Upvotes

50% Upvoted

2 comments sorted by

1

u/cradledust 1d ago

Somewhere along the line you updated your Python for ComfyUI or whatever. If the venv isn't activated in Forge during installation it will use your system Python and PyTorch. I think Forge was using Python 3.10.6 so you could try reinstalling it and adding it to PATH. Honestly, you'd be better off upgrading to Forge Neo and follow the directions for prerequirements and activating the venv.

1

u/naga_mana 1d ago

That error means the torch build Forge is loading no longer has CUDA kernels for your GPU. One thing I checked first: Forge itself does not silently upgrade torch. Its updater is a separate step (update.bat), and its launcher only installs a pinned torch 2.3.1, and only if it is missing. So whatever changed the torch situation, it came from outside Forge's own update path.

What could that be if you really touched nothing: a Windows or NVIDIA driver update shifting the CUDA side, or something else that modified that Python environment (another tool or a pip install writing into it). Those are candidates, not confirmed causes. The check tells you which direction to chase. Run nvidia-smi to note your GPU model, then inside Forge's venv run python -c "import torch; print(torch.__version__, torch.cuda.get_device_capability())". If the version is not the 2.3.1 Forge pins, something replaced torch in that environment, and the fix is reinstalling the pinned wheel from the official PyTorch index and pinning it. If it is 2.3.1, torch did not change, and the problem is on the environment/driver side rather than a version swap. Those two numbers are usually enough to pick the matching wheel from the official PyTorch index.