We present ComfyMind, a collaborative AI system designed to enable robust and scalable general-purpose generation, built on the ComfyUI platform. We evaluate ComfyMind on three public benchmarks: ComfyBench, GenEval, and Reason-Edit, which span generation, editing, and reasoning tasks. Results show that ComfyMind consistently outperforms existing open-source baselines and achieves performance comparable to GPT-Image-1. ComfyMind paves a promising path for the development of open-source general-purpose generative AI systems.
- [2025/05/30] Our online demo has been released. https://envision-research.hkust-gz.edu.cn/ComfyMind/
- [2025/05/24] Our paper is submitted to arXiv.
- Clone the repository, create and activate conda environment:
git clone https://github.com/LitaoGuo/ComfyMind.git
cd ComfyMind
conda create -n comfymind python=3.12
conda activate comfymind- Install dependencies:
pip install -r requirements.txt- ComfyUI Installation
- ComfyUI-Manager offers custom nodes management and installation.
- Hugging Face offers Models Installation
config.yaml to set your APIs:
python main.py \
--instruction "The generation instruction" \
--resource1 "<optional>path/to/the/reference1" \
--resource2 "<optional>path/to/the/reference2"
--save_path "path/to/save/result"python main_gradio.pyIf you find our work helpful, please consider citing our paper:
@misc{guo2025comfymindgeneralpurposegenerationtreebased,
title={ComfyMind: Toward General-Purpose Generation via Tree-Based Planning and Reactive Feedback},
author={Litao Guo and Xinli Xu and Luozhou Wang and Jiantao Lin and Jinsong Zhou and Zixin Zhang and Bolan Su and Ying-Cong Chen},
year={2025},
eprint={2505.17908},
archivePrefix={arXiv},
primaryClass={cs.AI},
url={https://arxiv.org/abs/2505.17908},
}We would like to thank the authors of the following projects for their excellent works.
This code is released under the MIT License.
If you have any questions, please raise an issue or contact us at guolitauo@gmail.com.