obsxrver/ComfyUI-Native-INT8_ConvRot

ComfyUI-Native-Int8-ConvRot

Int8 ConvRot models, converted to the format ComfyUI Expects.

Int8 ConvRot is the best quantization method so far in terms of Quality:Performance ratio. In my personal experience Int8 ConvRot models provide a similar level of quality to BF16 at a generation time matching or beating FP8_Scaled

'INT8 ConvRot is row-wise INT8 with parameters and activations rotated before quantization via ConvRot.' https://github.com/BobJohnson24/ComfyUI-INT8-Fast/blob/main/Metrics.md

Quality Ranking:

GGUF Q8 > INT8 ConvRot > MXFP8 > FP8 >= INT8 Row > INT8 Tensorwise

References:

1. https://www.reddit.com/r/StableDiffusion/comments/1uimp1j/so_is_int8convrot_the_new_hot_thing/
2. https://github.com/BobJohnson24/ComfyUI-INT8-Fast/blob/main/Metrics.md
3. https://huggingface.co/Comfy-Org/Boogu-Image/discussions/10#6a404ed359b6d5b4e834a644
4. https://github.com/Comfy-Org/ComfyUI/pull/14636
5. https://huggingface.co/bertbobson/ComfyUI-INT8_ConvRot