ComfyUI Extension: ComfyUI-nunchaku

Authored by nunchaku-ai

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Nunchaku ComfyUI Node. Nunchaku is the inference that supports SVDQuant. SVDQuant is a new post-training training quantization paradigm for diffusion models, which quantize both the weights and activations of FLUX.1 to 4 bits, achieving 3.5× memory and 8.7× latency reduction on a 16GB laptop 4090 GPU. See more details: https://github.com/mit-han-lab/nunchaku

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README

<div align="center" id="nunchaku_logo"> <img src="https://huggingface.co/datasets/nunchaku-ai/cdn/resolve/main/logo/v2/nunchaku-compact-transparent.png" alt="logo" width="220"></img> </div> <h3 align="center"> <a href="http://arxiv.org/abs/2411.05007"><b>Paper</b></a> | <a href="https://nunchaku.tech/docs/ComfyUI-nunchaku/"><b>Docs</b></a> | <a href="https://hanlab.mit.edu/projects/svdquant"><b>Website</b></a> | <a href="https://hanlab.mit.edu/blog/svdquant"><b>Blog</b></a> | <a href="https://demo.nunchaku.tech/"><b>Demo</b></a> | <a href="https://huggingface.co/nunchaku-ai"><b>Hugging Face</b></a> | <a href="https://modelscope.cn/organization/nunchaku-tech"><b>ModelScope</b></a> </h3> <div align="center"> <a href="https://trendshift.io/repositories/13942" target="_blank"><img src="https://trendshift.io/api/badge/repositories/13942" alt="nunchaku-ai/nunchaku | Trendshift" style="width: 120px; height: 26px;" width="120" height="26"/></a> <a href=https://discord.gg/Wk6PnwX9Sm target="_blank"><img src=https://img.shields.io/badge/dynamic/json?url=https%3A%2F%2Fdiscord.com%2Fapi%2Finvites%2FWk6PnwX9Sm%3Fwith_counts%3Dtrue&query=%24.approximate_member_count&logo=discord&logoColor=white&label=Discord&color=green&suffix=%20total height=22px></a> <a href=https://huggingface.co/datasets/nunchaku-ai/cdn/resolve/main/nunchaku/assets/wechat.jpg target="_blank"><img src=https://img.shields.io/badge/WeChat-07C160?logo=wechat&logoColor=white height=22px></a> <a href=https://deepwiki.com/nunchaku-ai/ComfyUI-nunchaku target="_blank"><img src=https://deepwiki.com/badge.svg height=22px></a> </div>

This repository provides the ComfyUI plugin for Nunchaku, an efficient inference engine for 4-bit neural networks quantized with SVDQuant. For the quantization library, check out DeepCompressor.

Join our user groups on Discord and WeChat for discussions—details here. If you have any questions, run into issues, or are interested in contributing, feel free to share your thoughts with us!

Nunchaku ComfyUI Plugin

comfyui

News

  • [2026-01-12] 🚀 v1.2.0 Released! Enjoy a 20–30% Z-Image performance boost, seamless LoRA support with native ComfyUI nodes, and INT4 support for 20-series GPUs!
  • [2025-12-26] 🚀 v1.1.0: Support 4-bit Tongyi-MAI/Z-Image-Turbo! Download on Hugging Face or ModelScope, and try it with this workflow!
  • [2025-09-24] 🔥 Released 4-bit 4/8-step Qwen-Image-Edit-2509 lightning models at Hugging Face! Try them out with this workflow!
  • [2025-09-24] 🔥 Released 4-bit Qwen-Image-Edit-2509! Models are available on Hugging Face. Try them out with this workflow!
  • [2025-09-09] 🔥 Released 4-bit Qwen-Image-Edit together with the 4/8-step Lightning variants! Models are available on Hugging Face. Try them out with this workflow!
<details> <summary>More</summary>
  • [2025-09-04] 🚀 Official release of Nunchaku v1.0.0! Qwen-Image now supports asynchronous offloading, cutting Transformer VRAM usage to as little as 3 GiB with no performance loss. You can also try our pre-quantized 4/8-step Qwen-Image-Lightning models on Hugging Face or ModelScope.
  • [2025-08-23] 🚀 v1.0.0 adds support for Qwen-Image! Check this workflow to get started. LoRA support is coming soon.
  • [2025-07-17] 📘 The official ComfyUI-nunchaku documentation is now live! Explore comprehensive guides and resources to help you get started.
  • [2025-06-29] 🔥 v0.3.3 now supports FLUX.1-Kontext-dev! Download the quantized model from Hugging Face or ModelScope and use this workflow to get started.
  • [2025-06-11] Starting from v0.3.2, you can now easily install or update the Nunchaku wheel using this workflow!
  • [2025-06-07] 🚀 Release Patch v0.3.1! We bring back FB Cache support and fix 4-bit text encoder loading. PuLID nodes are now optional and won’t interfere with other nodes. We've also added a NunchakuWheelInstaller node to help you install the correct Nunchaku wheel.
  • [2025-06-01] 🚀 Release v0.3.0! This update adds support for multiple-batch inference, ControlNet-Union-Pro 2.0 and initial integration of PuLID. You can now load Nunchaku FLUX models as a single file, and our upgraded 4-bit T5 encoder now matches FP8 T5 in quality!
  • [2025-04-16] 🎥 Released tutorial videos in both English and Chinese to assist installation and usage.
  • [2025-04-09] 📢 Published the April roadmap and an FAQ to help the community get started and stay up to date with Nunchaku’s development.
  • [2025-04-05] 🚀 Release v0.2.0! This release introduces multi-LoRA and ControlNet support, with enhanced performance using FP16 attention and First-Block Cache. We've also added 20-series GPU compatibility and official workflows for FLUX.1-redux!
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