1.58-bit FLUX
Authors: name: Chenglin Yang; name: Celong Liu; name: Xueqing Deng; name: Dongwon Kim; name: Xing Mei; name: Xiaohui Shen; name: Liang-Chieh Chen
Published: 2024-12-24 19:00:02

Abstract: We present 1.58-bit FLUX, the first successful approach to quantizing the
state-of-the-art text-to-image generation model, FLUX.1-dev, using 1.58-bit
weights (i.e., values in {-1, 0, +1}) while maintaining comparable performance
for generating 1024 x 1024 images. Notably, our quantization method operates
without access to image data, relying solely on self-supervision from the
FLUX.1-dev model. Additionally, we develop a custom kernel optimized for
1.58-bit operations, achieving a 7.7x reduction in model storage, a 5.1x
reduction in inference memory, and improved inference latency. Extensive
evaluations on the GenEval and T2I Compbench benchmarks demonstrate the
effectiveness of 1.58-bit FLUX in maintaining generation quality while
significantly enhancing computational efficiency.