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All-in-One Photo Editor for Portraits, Makeup, and Multi-Image Composition

Editing a face with most AI tools is a gamble — ask for a makeup change and the person often comes back looking like someone else. FireRed-Image-Edit-1.1 is built to keep the subject recognizably themselves through even dramatic edits, the way a skilled retoucher can restyle a portrait without changing who is in it. It rolls portrait retouching, makeup styling, multi-image blending, text-style transfer, and old-photo repair into one model, and ships with a speed-tuning kit so it is practical to run in real production. Built by the FireRedTeam.

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What it does

FireRed-Image-Edit-1.1 is a general-purpose image editing foundation model developed by FireRedTeam. It is an upgrade over FireRed-Image-Edit-1.0, with significant enhancements in identity consistency, multi-image conditioning, and domain-specialized editing. The model is designed to bridge the gap between open-source capabilities and closed-source production solutions, excelling at portrait editing, multi-subject composition, makeup styling, text style reference, and photo restoration. It is built for real-world creative production workflows and comes with an extensive engineering optimization suite for deployment at scale.

Problem it solves

• Identity consistency – Open-source state-of-the-art in character identity preservation, keeping subjects recognizable across complex and imaginative edits
• Multi-element fusion – Freely combines 10+ input elements with Agent-powered automatic cropping and stitching, eliminating the need for lengthy prompt engineering
• Portrait & makeup editing – Dozens of makeup and beauty styles, from professional retouching to creative Halloween looks and skin tone enhancement
• Text style reference – Maintains high-fidelity typography and stylized text rendering, on par with closed-source solutions
• Photo restoration – High-quality old photo repair with superior fine-grained detail recovery
• Production deployment – Designed for real-world use with ComfyUI support, GGUF format, LoRA training, and extreme speed optimization

Input/Output

• Input: One or more images + a natural-language editing instruction

  • Supports portrait editing, multi-image fusion, makeup styling, text-style reference, virtual try-on, photo restoration, and style transfer

  • The Agent workflow handles complex multi-image compositions automatically

    

    

• Output: A high-quality RGB image with the edits applied

  • If a reference image is provided, it is used as guidance (e.g. copy specific details from the reference)

  • If no reference image is provided, the result is generated from the text prompt alone

    

• Parameters:

  • Diffusion steps — 5–40 (higher = better quality, slower)
  • Output image size — width × height, 512–1600
  • Random seed (Advanced) — enter a number for reproducibility, or -1 to randomize

A sample workflow from community

Accuracy & Speed

• Technical Details (for engineers)

Model Source