Exploring Quantization Backends in Diffusers — bitsandbytes (BnB) 4-bit/8-bit

AI Impact Summary

The Diffusers library now integrates quantization backends like bitsandbytes, GGUF, torchao, and native FP8 support, enabling more accessible large diffusion models. This post demonstrates using bitsandbytes (BnB) 4-bit and 8-bit quantization with the Flux-dev model, showcasing the subtle differences in image quality that can arise, particularly at lower bit precisions. The example code provides a practical demonstration of loading and running the quantized model, highlighting memory savings and inference time trade-offs.