This repository contains Nunchaku-quantized versions of FLUX.1-Kontext-dev, capable of editing images based on text instructions. It is optimized for efficient inference while maintaining minimal loss in performance.

Model Details

Model Description

• Developed by: Nunchaku Team
• Model type: image-to-image
• License: flux-1-dev-non-commercial-license
• Quantized from model: FLUX.1-Kontext-dev

Model Files

• svdq-int4_r32-flux.1-kontext-dev.safetensors: SVDQuant quantized INT4 FLUX.1-Kontext-dev model. For users with non-Blackwell GPUs (pre-50-series).
• svdq-fp4_r32-flux.1-kontext-dev.safetensors: SVDQuant quantized NVFP4 FLUX.1-Kontext-dev model. For users with Blackwell GPUs (50-series).

Model Sources

• Inference Engine: nunchaku
• Quantization Library: deepcompressor
• Paper: SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models
• Demo: svdquant.mit.edu

Usage

• Diffusers Usage: See flux.1-kontext-dev.py. Check our tutorial for more advanced usage.
• ComfyUI Usage: See nunchaku-flux.1-kontext-dev.json.