Up until today, all capable generative image editing models were only available as proprietary tools. Today, that changes. We release FLUX.1 Kontext [dev], our developer version of FLUX.1 Kontext [pro], which delivers proprietary-level image editing performance in a 12B parameter model that can run on consumer hardware.
Making model weights openly accessible is fundamental to technological innovation. FLUX.1 Kontext [dev] is now available as an open-weight model under the FLUX.1 Non-Commercial License, providing free access for research and non-commercial use. FLUX.1 Kontext [dev] is compatible with the existing FLUX.1 [dev] inference code and comes with day-0 support for popular inference frameworks like ComfyUI, HuggingFace Diffusers and TensorRT.
The model weights are available on HuggingFace. Our partners FAL, Replicate, Runware, DataCrunch and TogetherAI and ComfyUI provide ready-to-use API endpoints and code for cloud-based and/or local inference.
The technical report is available on arxiv.
Setting New Standards in Open Image Editing
FLUX.1 Kontext [dev] focuses exclusively on editing tasks. The model enables iterative editing, excels at character preservation across a diverse set of scenes and environments, and allows both precise local and global edits.
At Black Forest Labs, we remain committed to providing researchers and developers with best-in-class open tools that are competitive with existing proprietary solutions. To validate the performance of FLUX.1 Kontext [dev], we conducted extensive evaluation across multiple image editing benchmarks.
Human preference evaluations on KontextBench, our newly released image editing benchmark, demonstrate that FLUX.1 Kontext [dev] outperforms existing open image editing models, (Bytedance Bagel, HiDream-E1-Full) and closed models (Google's Gemini-Flash Image) across many categories. Independent evaluations run by Artificial Analysis confirm these findings.
Optimized for NVIDIA Blackwell Architecture
We have collaborated with NVIDIA to build optimized TensorRT weights specifically designed for the new NVIDIA Blackwell architecture which brings greatly improved inference speed and reduces memory usage while maintaining high-quality image editing performance.
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