Black Forest FLUX 3 Klein open-sourced: Official self-tests show it outperforms Qwen, but users say it is inferior to the older 4B version.
48 minutes ago
Beating AI News: German AI company Black Forest Labs has open-sourced its FLUX 3 Image Klein image generation model. Officially, it is listed as having 5.6 billion parameters, but this only accounts for the image generation component; an additional 4 billion parameters from Qwen3-VL are required for text instruction understanding, bringing the total to roughly 9.6 billion parameters. The new model supports native 4K output, image editing, and up to 10 reference images. Quantized versions can run on RTX graphics cards with as little as 8GB of VRAM, and an RTX 5090 takes approximately 4 seconds to generate a 1-megapixel image. Official internal evaluations show FLUX 3 Klein outperforms Qwen-Image 2.1 in both text-to-image and image editing capabilities. Compared to its own previous-generation FLUX.2 Klein 9B, its scores for these two tasks improved by 91 and 70 Elo points respectively. However, initial real-world tests on Reddit have been unfavorable: some users reported failed attempts at adjusting character poses and switching perspectives, with even some deeming the model’s performance inferior to the previous 4B version. In a separate third-party blind test of 200 real editing tasks, FLUX 3 Klein scored 6.93, slightly lower than Nano Banana 2.1’s 7.20, but costs only one-fifth as much per image. The test also found it prone to errors in character pose adjustment and multi-image composition. Black Forest Labs specifically notes that users should ideally use an additional language model to expand prompts before use, as short instructions often produce mediocre results. To this end, the team has released a 9-billion-parameter prompt expander. The model is licensed under the FLUX Kommunity License: individuals and enterprises with annual consolidated revenue under $5 million may use it for commercial image generation free of charge per the terms, but commercial fine-tuning requires separate authorization. API generation of a 1K image starts at $0.009.
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