A beginner's guide to the Flux-2-Dev model by Black-Forest-Labs on Replicate

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This is a simplified guide to an AI model called Flux-2-Dev maintained by Black-Forest-Labs. If you like these kinds of analysis, you should join AImodels.fyi or follow us on Twitter.

Model overview

flux-2-dev is a 32-billion parameter flow matching transformer model developed by Black Forest Labs for generating and editing images from text descriptions and reference images. The model represents a significant step forward in open-weight image generation, offering quality comparable to proprietary systems while remaining accessible for research and development. For users seeking even more advanced capabilities, flux-2-pro provides support for eight reference images, while flux-2-flex offers maximum quality with ten reference images. Those prioritizing speed can explore flux-schnell, the fastest option for rapid iterations.

Model inputs and outputs

The model accepts text prompts describing desired imagery, optional reference images for guidance, and various configuration parameters to control generation. It outputs high-quality images in multiple formats with customizable dimensions and aspect ratios. The flexible input system allows both pure text-to-image generation and guided image-to-image transformations with up to four reference images.

Inputs

Prompt: Text description of the image to generate
Input images: Optional list of up to four reference images (JPEG, PNG, GIF, or WebP) for guided generation
Aspect ratio: Image proportions (1:1, 16:9, 3:2, 2:3, 4:5, 5:4, 9:16, 3:4, 4:3, custom, or match input image)
Width and height: Custom dimensions in pixels for text-to-image generation (multiples of 32)
Seed: Random seed for reproducible results
Output format: Image file format (WebP, JPG, or PNG)
Output quality: Quality setting from 0 to 100 (not applicable for PNG)