INT8 Mix Quantization of One Obsession v24 by maxfeifei8, I got really curious about how INT8 quantization would fare with Illustrious. Turns out pretty good.

70 layers in INT8 and rest in INT8 Convrot for the diffusion model.

v2.0

• Text Encoders are now quantized with a mix of INT8 and INT8 Convrot, total checkpoint size is now down to 3.92 GB

• A patch is required to run the model as ComfyUI does not support quantization methods for the SDXL Clip Loaders. YOU WILL GET GARBAGE OUTPUT WITHOUT IT.

• Same prompt and seed from v1.0 so you can compare the images in terms of quality

v1.0

• Text Encoders are untouched

• Checkpoint runs natively on ComfyUI

Clone the below repo into your ComfyUI's custom_nodes folder. No need to add any nodes, it initializes and patches the CLIP Loader at runtime, please let me know if you encounter any issues.

https://github.com/bakapotatolord/ComfyUI-PotatoForge-Encoder-Quant

Sample images once again just the first stage (T2V), used prompts from the original model.

Tested on:

• NVIDIA GTX 1660 Super 6 GB

• 32 GB System RAM

Test settings:

• 25 steps

• CFG 4.5

• Euler Ancestral / Normall

• 696 × 1048 resolution

• Approximately 2.5 s/it on a GTX 1660 Super, about 45% faster than the usual model