Flux Models
Explore the FLUX model family by Black Forest Labs — from the blazing-fast Schnell to the high-quality Dev, Kontext, Fill, and Redux variants.
12 modelos
FLUX.1 [dev]
The flagship 12B parameter FLUX model by Black Forest Labs. Offers cutting-edge quality with open weights for research and creative workflows.
FLUX.1 [schnell]
Ultra-fast FLUX variant — generates high-quality images in just 1-4 steps. Apache 2.0 licensed for personal, scientific, and commercial use.
FLUX.1 Dev (Civitai)
The official FLUX.1 Dev model hosted on Civitai. 23K+ favorites, 133M+ generations — the most popular Flux checkpoint on the platform.
FLUX.1 Fill [dev]
FLUX inpainting model — fills masked areas in images based on text descriptions. Perfect for object removal, replacement, and creative editing.
FLUX.1 Redux [dev]
Image variation adapter for FLUX models. Reproduces input images with controlled variations — ideal for style transfer and iterative refinement.
FLUX.1 Depth [dev]
Depth-conditioned FLUX model for structure-aware image generation. Uses depth maps to maintain spatial composition while generating new content.
FLUX.1 Canny [dev]
Edge-conditioned FLUX model — generates images following canny edge maps for precise outline control and consistent compositions.
FLUX.1 Kontext [dev]
Multimodal flow model that unifies text-to-image and image editing. Instant editing via text instructions with character consistency across scenes.
FLUX.1 SRPO
Community fine-tune of FLUX.1 Dev optimized for enhanced realism and detail. One of the most downloaded Flux variants on inference platforms.
FLUX.1 Krea [dev]
Krea-enhanced variant of FLUX.1 Dev with improved artistic diversity and style capabilities. Excellent for creative and artistic generation.
FLUX.2 [dev]
The next-generation FLUX model with multi-reference support (up to 10 images), improved photorealism, advanced text rendering, and stronger prompt following.
FLUX 2 Klein 9B Edit
Compact 9B parameter FLUX 2 model optimized for image editing tasks. Fast inference with strong editing capabilities in a smaller package.
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