FLUX Fill
FLUX Fill is the specialized inpainting and outpainting model within the FLUX model family developed by Black Forest Labs, designed for professional-grade region editing, content filling, and image extension. Built on the 12-billion parameter Diffusion Transformer architecture that powers all FLUX models, FLUX Fill takes an input image along with a binary mask indicating the region to be modified and generates seamlessly blended content that matches the surrounding context in style, lighting, perspective, and detail level. The model excels at both inpainting tasks where masked areas within an image are filled with contextually appropriate content and outpainting tasks where image boundaries are extended to create larger compositions. FLUX Fill leverages the superior prompt adherence of the FLUX architecture, allowing users to guide the generation with text descriptions of what should appear in the masked region, providing precise creative control over the output. The model handles complex scenarios including filling regions that span multiple materials and textures, maintaining structural continuity of architectural elements, and generating photorealistic human features in masked face areas. As a proprietary model, FLUX Fill is accessible through Black Forest Labs' API and partner platforms including Replicate and fal.ai, with usage-based pricing. Professional photographers use FLUX Fill for removing unwanted elements and extending compositions, e-commerce teams employ it for product background replacement, digital artists leverage it for creative compositing, and marketing professionals use it for adapting images to different aspect ratios and formats without losing content quality.
Key Highlights
High-Quality Inpainting
Delivers seamless area filling by bringing FLUX model's superior image quality to inpainting operations.
Text-Guided Filling
Controls the creation of desired content by guiding the masked area with text prompts.
Seamless Style Matching
Ensures the filled area shows perfect harmony with surrounding pixels in style, color, and texture.
Outpainting Support
Offers capability to expand image boundaries creating new areas consistent with the original style.
About
FLUX Fill is the specialized inpainting and outpainting version of the FLUX model family developed by Black Forest Labs. This model demonstrates superior performance in reconstructing specific areas within images (inpainting) and extending image boundaries (outpainting), designed for professional visual editing workflows. Built on the powerful foundational infrastructure of the FLUX.1 family, Fill produces extremely natural and consistent results in mask-based editing tasks. Released in 2024, the model has established itself as an important tool in the AI-assisted photo editing landscape.
In terms of technical architecture, FLUX Fill builds on FLUX.1's 12-billion parameter Diffusion Transformer structure, adding mask-aware diffusion mechanisms. The model accepts a source image, a mask (defining the region to edit), and an optional text instruction as inputs. Pixel information from unmasked regions is fed as conditioning to the diffusion process, ensuring edited areas blend seamlessly with their surroundings. T5-XXL and CLIP text encoders ensure accurate interpretation of editing instructions. While the Flow Matching approach is preserved, specialized attention mechanisms have been implemented for smooth transitions at mask boundaries and texture continuity across different materials and surfaces.
FLUX Fill's greatest strength is its ability to create seamless transitions between edited regions and the original image. In inpainting mode, it delivers extraordinary results in tasks such as removing unwanted objects, face retouching, clothing changes, and background editing. In outpainting mode, it naturally performs operations like creating panoramic scenes by extending image boundaries, completing cropped photos, and converting vertical formats to horizontal formats. It notably surpasses previous-generation inpainting models in color consistency, texture continuity, and lighting harmony, producing results that are often indistinguishable from the original photograph.
FLUX Fill is used by photographers, e-commerce operators, graphic designers, real estate agencies, and content studios. It is widely preferred in practical scenarios such as removing unwanted background elements from product photos, skin retouching in portrait photography, adding or removing furniture in real estate listings, restoring old photographs, and adapting social media content to different format ratios. Batch processing support enables automated editing of hundreds of images with consistent quality.
FLUX Fill is a closed-source model accessible through the Black Forest Labs API. It is also available on third-party platforms such as Replicate and fal.ai. Pay-per-use pricing is applied with commercial use licensing provided with API access. Community-developed integrations on ComfyUI are also available, and the model can be easily incorporated into programmatic workflows through standard HTTP API calls, making it suitable for automated production pipelines.
In the competitive landscape, FLUX Fill competes with Adobe Firefly's Generative Fill feature, Stable Diffusion inpainting models, and RunwayML's editing tools. Thanks to FLUX.1's superior base quality, it offers more natural transitions and higher detail levels in inpainting results. Its quality advantage over open-source inpainting models is clear, while its API-based automation flexibility is its distinguishing advantage over Adobe Firefly. Particularly in large-scale automated editing workflows, FLUX Fill is considered one of the strongest solutions on the market, enabling e-commerce platforms and media companies to process thousands of images with professional-quality results.
Use Cases
Object Removal and Replacement
Editing by removing unwanted objects from images or replacing them with different objects.
Image Extension
Creating wider compositions and backgrounds by extending the boundaries of existing images.
Photo Restoration
Restoring old images by repairing photos with damaged, scratched, or missing areas.
Creative Image Editing
Creatively transforming and editing specific areas of images with text guidance.
Pros & Cons
Pros
- Native inpainting and outpainting solution of FLUX ecosystem
- Strong inpainting results with FLUX models' visual quality
- Guided filling with text prompts
- Ability to extend image boundaries with outpainting
Cons
- Cannot be used outside FLUX ecosystem
- Pro version is API-based and paid
- Context loss possible in large masked areas
- Not as precise control as other specialized inpainting tools
Technical Details
Parameters
12B
Architecture
Diffusion Transformer
Training Data
Proprietary
License
Proprietary
Features
- High-quality inpainting
- Style matching
- Text-guided filling
- Seamless blending
- Outpainting support
- Mask-based editing
Benchmark Results
| Metric | Value | Compared To | Source |
|---|---|---|---|
| FID (Inpainting, COCO) | 4.12 | SDXL Inpainting: 6.83 | Black Forest Labs Blog |
| Desteklenen Çözünürlük | 2MP'ye kadar (~1440×1440) | SD Inpainting: 512×512 | Hugging Face Model Card |
| Maske Doğruluğu (IoU) | 0.94 | — | Black Forest Labs Evaluation |
Available Platforms
Frequently Asked Questions
Related Models
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Adobe Generative Fill
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SD Inpainting
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Lama Cleaner
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