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| # TODO: MXFP8/NVFP4 Support | |
| ## Status: Temporarily Disabled | |
| MXFP8 and NVFP4 quantization formats are temporarily disabled due to build issues with comfy-kitchen on HuggingFace Space infrastructure. | |
| ## Issue | |
| The comfy-kitchen CUDA build fails due to a CUDA 12.9/glibc header conflict: | |
| - `cospi`/`sinpi` function exception specification mismatch between CUDA's `math_functions.h` and system headers | |
| ## Planned Resolution | |
| Options being considered: | |
| 1. **Pre-built wheel**: Host a pre-compiled comfy-kitchen wheel | |
| 2. **Custom Dockerfile**: Build comfy-kitchen in a controlled environment | |
| 3. **PyTorch fallback**: Implement pure PyTorch quantization as fallback | |
| ## Currently Available Formats | |
| - FP8 Tensorwise (per-tensor scaling) | |
| - FP8 Block (per-block scaling, 64 or 128 block size) | |
| - INT8 Block (Triton-based, 128 block size) | |
| ## Reference | |
| - comfy-kitchen branch: `sc_mm_mxfp8_sync` | |
| - MXFP8 requires SM >= 10.0 (Blackwell GPU) | |
| - NVFP4 requires SM >= 10.0/12.0 (Blackwell GPU) | |