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language:
  - en
  - zh
license: apache-2.0
pipeline_tag: image-to-image
library_name: diffusers
arxiv: 2602.13344

🤗 HuggingFace | 🖥️ Demo | 📄 Technical Report | 💻 Code

🔥 FireRed-Image-Edit

FireRed-Image-Edit is a general-purpose image editing model that delivers high-fidelity and consistent editing across a wide range of scenarios. It is introduced in the paper FireRed-Image-Edit-1.0 Technical Report.

✨ Key Features

Strong Editing Performance: FireRed-Image-Edit delivers leading open-source results with accurate instruction following, high image quality, and consistent visual coherence.
Native Editing Capability: Built directly from text-to-image foundation model and endowed with editing capabilities.
Text Style Preservation: Maintains text styles with high fidelity, achieving performance comparable to closed-source solutions.
Photo Restoration: High-quality old photo restoration and enhancement.
Multi-Image Editing: Flexible editing of multiple images such as virtual try-on.

📰 News

2026.02.14: We released FireRed-Image-Edit-1.0 model weights. Check more details in the Model Zoo section.
2026.02.10: We released the Technical Report of FireRed-Image-Edit-1.0.

🎨 Showcase

Some real outputs produced by FireRed-Image-Edit across general editing.

🗂️ Model Zoo

Models	Task	Description	Download Link
FireRed-Image-Edit-1.0	Image-Editing	General-purpose image editing model	🤗 HuggingFace
FireRed-Image-Edit-1.0-Distilled	Image-Editing	Distilled version of FireRed-Image-Edit-1.0 for faster inference	To be released
FireRed-Image	Text-to-Image	High-quality text-to-image generation model	To be released

🏗️ Model Architecture

⚡️ Quick Start

Install the latest version of diffusers

pip install git+https://github.com/huggingface/diffusers

Use the following code snippets to generate or edit images.

python inference.py \
    --input_image ./examples/edit_example.png \
    --prompt "在书本封面Python的下方，添加一行英文文字2nd Edition" \
    --output_image output_edit.png \
    --seed 43

📊 Benchmark

To better validate the capabilities of our model, we propose a benchmark called REDEdit-Bench. Our main goal is to build more diverse scenarios and editing instructions that better align with human language, enabling a more comprehensive evaluation of current editing models. We collected over 3,000 images from the internet, and after careful expert-designed selection, we constructed 1,673 bilingual (Chinese–English) editing pairs across 15 categories.

Inference and Evaluation Code

We provide the inference and evaluation code for REDEdit-Bench. Please refer to the redbench_infer.py and redbench_eval.py scripts in the src/tools directory for more details.

Results on ImgEdit

Model	Overall ↑	Add	Adjust	Extract	Replace	Remove	BG	Style	Hybrid	Action
🔹 Proprietary Models
Nano-Banana	4.29	4.62	4.41	3.68	4.34	4.39	4.40	4.18	3.72	4.83
Seedream4.0	4.30	4.33	4.38	3.89	4.65	4.57	4.35	4.22	3.71	4.61
Seedream4.5	4.32	4.57	4.65	2.97	4.66	4.46	4.37	4.92	3.71	4.56
Nano-Banana-Pro	4.37	4.44	4.62	3.42	4.60	4.63	4.32	4.97	3.64	4.69
🔹 Open-source Models
FLUX.1 Kontext [Dev]	3.71	3.99	3.88	2.19	4.27	3.13	3.98	4.51	3.23	4.18
Step1X-Edit-v1.2	3.95	3.91	4.04	2.68	4.48	4.26	3.90	4.82	3.23	4.22
Qwen-Image-Edit-2509	4.31	4.34	4.27	3.42	4.73	4.36	4.37	4.91	3.56	4.80
FLUX.2 [Dev]	4.35	4.50	4.18	3.83	4.65	4.65	4.31	4.88	3.46	4.70
LongCat-Image-Edit	4.45	4.44	4.53	3.83	4.80	4.60	4.33	4.92	3.75	4.82
Qwen-Image-Edit-2511	4.51	4.54	4.57	4.13	4.70	4.46	4.36	4.89	4.16	4.81
FireRed-Image-Edit	4.56	4.55	4.66	4.34	4.75	4.58	4.45	4.97	4.07	4.71

📜 License Agreement

The code and the weights of FireRed-Image-Edit are licensed under Apache 2.0.

📝 TODO:

Release FireRed-Image-Edit-1.0 model.
Release REDEdit-Bench, a comprehensive benchmark for image editing evaluation.
Release FireRed-Image-Edit-1.0-Distilled model, a distilled version of FireRed-Image-Edit-1.0 for few-step generation.
Release FireRed-Image model, a text-to-image generative model.

🖊️ Citation

We kindly encourage citation of our work if you find it useful.

@article{firered2026rededit,
      title={FireRed-Image-Edit: A General-Purpose Image Editing Model}, 
      author={Super Intelligence Team},
      year={2026},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://huggingface.co/papers/2602.13344}, 
}

🤝 Acknowledgements

We would like to thank the developers of the amazing open-source projects, including Qwen-Image, Diffusers and HuggingFace.

FireRedTeam
/

FireRed-Image-Edit-1.0