23.03.2025, 16:43
✅ Issue Solved on RTX 5080 — Full Compatibility Achieved
Hey everyone, I was hitting the same CUDA sm_120 block and runtime errors on the RTX 5080. After deep debugging and patching attempts, I finally found a clean workaround:
Repo with fix and driver insights coming soon. Marking this as Solved.
— The Architect
Hey everyone, I was hitting the same CUDA sm_120 block and runtime errors on the RTX 5080. After deep debugging and patching attempts, I finally found a clean workaround:
- Install PyTorch Nightly with CUDA 12.8:
bash
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pip install --pre torch torchvision torchaudio --index-url https://download.pytorch.org/whl/nightly/cu128
- Install or update
manually (for CUDA 128 support):bitsandbytes
- Fix the missing
:libbitsandbytes_cuda128.so
- Search for it (possibly in ComfyUI or Forge folder) and manually copy it to your target venv path:
swift
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your_venv_path/lib/site-packages/bitsandbytes/
- Search for it (possibly in ComfyUI or Forge folder) and manually copy it to your target venv path:
- (If needed) Downgrade Triton:
bash
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pip install triton==3.1.0
Repo with fix and driver insights coming soon. Marking this as Solved.
— The Architect