State-of-the-Art Identity Consistency
Open-source SOTA in character identity preservation, ensuring subjects remain recognizable across complex edits
A general-purpose image editing model that delivers high-fidelity and consistent editing across a wide range of scenarios. Open-source SOTA with accurate instruction following, high image quality, and consistent visual coherence.
By RedNote · Open Source
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.
State-of-the-art editing performance with ultimate engineering optimization
Open-source SOTA in character identity preservation, ensuring subjects remain recognizable across complex edits
Freely combine 10+ elements with Agent-powered automatic cropping and stitching — no more struggles with short prompts
Dozens of styles from professional beauty retouching and yellow/olive skin tone brightening to Halloween witch makeup and creative looks
Maintains high-fidelity typography and stylized text comparable to closed-source solutions
High-quality old photo repair and enhancement with superior detail recovery
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.
Complex portrait editing including background replacement, clothing changes, pose adjustment, and accessory modification
Open-Source SOTA
FireRed Image Edit establishes a new state-of-the-art among open-source models on ImgEdit, GEdit, and REDEdit benchmarks
| 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 |
Trained at scale for production-grade image editing
ImgEdit Overall Score
GEdit Score (EN)
End-to-End Inference
VRAM Requirement
What researchers and creators say about FireRed Image Edit
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.”
Common questions about FireRed Image Edit
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