FLUX
What is FLUX?
FLUX is a powerful open-source AI image generation model that produces high-quality images from text prompts, with particularly strong ability to follow complex instructions and render text correctly within images.
At a glance
- Type of model
- Transformer-based text-to-image generation model
- Developed by
- Black Forest Labs
- Key capability
- High-quality image generation with strong prompt adherence, accurate text rendering, and reliable anatomical correctness
- How it fits in AI workflow
- Used by developers and creators as a foundation model for image generation, custom fine-tuning, and building AI-powered creative tools, particularly in open-source and self-hosted environments where commercial model restrictions or costs are limiting factors
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How it compares
Both are open-source image generation models developed with significant involvement from the same core research team. Stable Diffusion uses a U-Net architecture and established the open-source generation ecosystem. FLUX uses a newer transformer architecture and was developed as a deliberate architectural advancement, with particular improvements in prompt adherence, text rendering within images, and anatomical accuracy. FLUX generally produces stronger results on complex prompts, while the Stable Diffusion ecosystem has a larger library of existing fine-tuned models and ControlNet implementations built up over a longer history.
Pro tip
FLUX's strong prompt adherence means that being specific and detailed in prompts produces notably better results than with earlier models that would often reinterpret vague instructions freely. Rather than relying on the model to fill in gaps creatively, providing precise descriptions of subject, lighting, composition, and style tends to reward FLUX with accurate, detailed outputs. When text needs to appear in a generated image, FLUX handles this far better than most open-source predecessors: specifying exact text content in quotes within the prompt typically produces readable results.
Types and variations
- FLUX.
- 1 Pro is the highest-quality commercial variant, optimised for professional production use where output fidelity is paramount.
- FLUX.
- 1 Dev is the developer-focused variant available for experimentation, research, and building custom applications under an open licence.
- FLUX.
- 1 Schnell is the speed-optimised variant designed for rapid prototyping and fast iteration with significantly reduced generation times.
- FLUX 2 and FLUX Kontext are subsequent releases that build on the original architecture with additional capability improvements in specific areas.
- Fine-tuned variants trained on specific styles, characters, or domains also proliferate in the open-source community.
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Try MorphicCommon use cases
- Developers use FLUX as the foundation model for building AI-powered creative applications and tools, taking advantage of its open licence for integration into products without commercial restrictions.
- Creators use it for image generation workflows that require strong text rendering, such as creating branded imagery, text-heavy compositions, or instructional visuals.
- Fine-tuners use the Dev variant as a base for training custom LoRA models that specialise the base model for specific styles or subjects.
- Researchers use FLUX to explore new prompting techniques and generation approaches, contributing improvements back to the open-source community.
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Direct scenes, design characters, and ship full films
All-in-one AI creative platform with simple, transparent pricing, no speed throttles, and an infinite Canvas for max creativity.
FAQs
FLUX is an open-source AI image generation model developed by Black Forest Labs, released in 2024 as a next-generation alternative to Stable Diffusion. It uses a transformer-based architecture and is notable for strong prompt adherence, high image quality, accurate text rendering within images, and reliable anatomical correctness: areas where earlier open-source models had significant limitations.
FLUX was developed by Black Forest Labs, a company founded by several key researchers who had previously been central to the development of Stable Diffusion at Stability AI. The team brought their experience with open-source diffusion model research to FLUX, building it on a new transformer-based architecture rather than the U-Net backbone used in Stable Diffusion.
FLUX is released as a family of models optimised for different use cases. FLUX.1 Pro is the highest quality commercial variant for professional production. FLUX.1 Dev is open for developer experimentation and custom application building. FLUX.1 Schnell is speed-optimised for rapid prototyping and iteration. FLUX 2 and FLUX Kontext are subsequent releases adding further capability improvements.
FLUX uses a newer transformer-based architecture compared to Stable Diffusion's U-Net backbone, and generally produces stronger results on complex prompts with multiple elements, better handles text rendering within images, and maintains more accurate human anatomy. Stable Diffusion has a larger library of existing fine-tuned models and community tools built up over a longer release history. Both are open-source and developed with involvement from overlapping research teams.
Text rendering within generated images is one of FLUX's standout improvements over earlier open-source models. When text content is specified clearly in the prompt: typically by placing the desired text in quotation marks within the description — FLUX is capable of producing readable, coherent text within the generated image, which had been a significant weakness of models like Stable Diffusion.
FLUX model availability depends on the specific variant. FLUX.1 Dev and FLUX.1 Schnell are released under licences that make them accessible for developer experimentation and personal use. FLUX.1 Pro is available through commercial APIs. The terms differ between variants, so reviewing Black Forest Labs' current licence documentation for each model is recommended before building commercial products or applications.
FLUX's Dev variant supports fine-tuning, and the open-source community has developed LoRA training pipelines that allow creators and developers to train custom models on top of the FLUX base for specific styles, characters, or visual domains. Fine-tuned FLUX models are widely shared on platforms like Hugging Face and Civitai, expanding the available library of specialised generation capabilities beyond the base model.
Running FLUX locally requires a reasonably capable GPU with sufficient VRAM: the FLUX.1 Dev and Schnell models typically require at least 8GB of VRAM for generation at standard resolutions, with 12GB or more providing more comfortable headroom. The Schnell variant's speed optimisation makes it more practical on mid-range hardware. Quantised versions of the models have been developed by the community that reduce memory requirements at some cost to output quality.
