State-of-the-Art Identity Consistency
Open-source SOTA in character identity preservation, ensuring subjects remain recognizable across complex edits
By Xiaohongshu · Open Source
Open Source SOTABilingual CN/ENApache 2.030GB VRAM
FireRed Image Edit
Transform photos with AI: Ghibli style, pixel art, photo colorization, outfit swap and more. Free, no sign-up, no watermark, powered by FireRed Image Edit 1.1.
FireRed Image Edit
Image to ImagePrompt
FireRed Image Edit
Local deployment guides
FireRed Image Edit technical guides
Practical, source-linked notes for developers running FireRed Image Edit 1.1 locally. These independent guides point back to the official FireRed Team model files and workflows.
FireRed Image Edit ComfyUI
Install the official workflow, place the transformer, text encoder, VAE, and optional Lightning LoRA in the correct folders, then run single- or multi-image edits.
Read guide →FireRed Image Edit FP8 vs GGUF
Compare BF16, community FP8 conversions, and GGUF quantization before choosing a model file for your available VRAM and quality target.
Read guide →FireRed Image Edit LoRA
Understand the official CoverCraft, Makeup, and Lightning adapters, what each one changes, and how to keep versions compatible.
Read guide →FireRed Image Edit alternatives
Compare Qwen Image Edit 2511, Nano Banana, and FLUX Kontext by deployment, editing workflow, source availability, and practical fit.
Read guide →
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By RedNote · Open Source
FireRed Universal Image Editing
A universal image editing model trained on 1.6 billion samples, achieving state-of-the-art high-fidelity editing across object manipulation, style transfer, virtual try-on, photo restoration and more. Open source under Apache 2.0.
Key Features
Key Features
State-of-the-art editing performance with ultimate engineering optimization
Multi-Element Fusion
Freely combine 10+ elements with Agent-powered automatic cropping and stitching — no more struggles with short prompts
Comprehensive Portrait Makeup
Dozens of styles from professional beauty retouching and yellow/olive skin tone brightening to Halloween witch makeup and creative looks
Text Style Reference
Maintains high-fidelity typography and stylized text comparable to closed-source solutions
Professional Photo Restoration
High-quality old photo repair and enhancement with superior detail recovery
Official Showcase
FireRed Image Edit Showcase
Explore the four core editing capabilities of FireRed: portrait editing, multi-image fusion, portrait makeup, and text style reference. All examples are from official documentation.
Portrait Editing
Portrait Editing
Complex portrait editing including background replacement, clothing changes, pose adjustment, and accessory modification
Official Editing Instructions
Open-Source SOTA
Benchmark Results
FireRed Image Edit establishes a new state-of-the-art among open-source models on ImgEdit, GEdit, and REDEdit benchmarks
Open-Source Models6 models
| Model | ImgEdit_O ↑ | GEdit_O ↑ (EN) | GEdit_O ↑ (CN) | REDEdit ↑ (EN) | REDEdit ↑ (CN) |
|---|---|---|---|---|---|
| Step1X-Edit-v1.2 | 3.95 | 7.480 | 7.467 | — | — |
| Qwen-Image-Edit-2509 | 4.31 | 7.480 | 7.467 | 3.99 | 4.00 |
| FLUX.2 [Dev] | 4.35 | 7.413 | 7.278 | 4.07 | 4.05 |
| LongCat-Image-Edit | 4.45 | 7.748 | 7.731 | 4.12 | 4.12 |
| Qwen-Image-Edit-2511 | 4.51 | 7.877 | 7.819 | 4.23 | 4.18 |
| FireRed-Image-Edit | 4.56 | 7.943 | 7.887 | 4.26 | 4.33 |
Data Highlights
FireRed by the Numbers
Trained at scale for production-grade image editing
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Testimonials
Community Feedback
What researchers and creators say about FireRed Image Edit
“FireRed's identity consistency in v1.1 is remarkable. Face and character preservation across edits rivals closed-source solutions, and the open-source availability accelerates our research.”
Dr. Wei Zhang: “FireRed's identity consistency in v1.1 is remarkable. Face and character preservation across edits rivals closed-source solutions, and the open-source availability accelerates our research.”
Sophia Martinez: “The multi-element fusion feature is a game-changer. Combining 10+ elements with automatic cropping and stitching saves hours of manual compositing work.”
Kenji Tanaka: “Photo restoration quality is outstanding. Old family photos come back to life with natural colors and sharp details. The 4.5-second inference makes batch processing practical.”
Emily Rogers: “The bilingual understanding is seamless. I write instructions in English, my colleague writes in Chinese, and FireRed handles both with equal precision. Truly impressive.”
Liu Chenxi: “Virtual try-on with FireRed has transformed our product photography pipeline. Realistic garment fitting on different body types without expensive photo shoots.”
Anna Kowalski: “The portrait makeup capabilities cover everything from subtle beauty retouching to bold creative looks. Dozens of styles available out of the box with consistent quality.”
Raj Patel: “Training on 1.6 billion samples really shows. The model generalizes across diverse editing scenarios without fine-tuning. The Lightning 8-step mode is perfect for real-time applications.”
Yuki Nakamura: “Font style reference and text rendering are best-in-class. FireRed preserves text styles with high fidelity, which is critical for our multilingual marketing materials.”
FAQ
Frequently Asked Questions
Common questions about FireRed Image Edit
A general-purpose image editing model by Xiaohongshu's Intelligent Creation Core Technology Team, built on Diffusion Transformer architecture with Qwen2.5-VL as vision-language encoder.
Yes. FireRed Edit and FireRed-Image-Edit both refer to the FireRed Image Edit model and its editing workflow. Some searches misspell the name as firerd image edit; the correct project name is FireRed Image Edit.
10+ categories: object add/remove/replace, attribute adjustment, background editing, style transfer, text editing, photo restoration, multi-image editing, virtual try-on, portrait makeup, and multi-element fusion.
30GB VRAM with optimized inference (distillation + quantization + static compilation), ~4.5s per sample.
Open-source SOTA on ImgEdit (4.56), GEdit EN (7.943), GEdit CN (7.887), REDEdit EN (4.26), REDEdit CN (4.33), surpassing some proprietary models.
Yes, native bilingual support for both Chinese and English editing instructions.
Automatic multi-image processing: ROI detection → crop & stitch → recaption. Supports 1-3 native input images, and 3+ via Agent.
Yes, full LoRA training code is released. Also provides LoRA Zoo with pre-trained styles (Makeup, Covercraft text style, etc.)
Apache 2.0, fully open source. Available on HuggingFace, ModelScope, and GitHub.
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