Model overview
> **FLUX 3 Image Klein Prompt Upsampler** is Black Forest Labs' 9B vision-language model, a full fine-tune of Qwen3.5-9B with the vision tower frozen, that expands a short image request into the detailed prompt FLUX 3 Image Klein works best with. The card says Klein is not meant to run without an upsampler in front of it, because short prompts sent as typed give generic output. One model covers three modes, selected by the system prompt: text-to-image, editing with up to 10 reference images, and layout with optional bounding boxes. Output prompts spell out medium and style, scene, lighting and camera, and each subject's colors, materials and position, with any text to render kept verbatim in quotes. For edits it looks at the references and writes the instruction around what is in them, covering what changes and what stays. Bounding boxes are kept exactly, in a box table after the prompt, and the prompt cites each box by id. Training had two stages: supervised training on pairs of short requests and expanded prompts, then preference tuning on pairs of the model's own prompts, rendered with FLUX 3 Image Klein at the same seed and ranked on the resulting image. The card gives no benchmark numbers. Its one example turns "A man walking with his dog, afternoon sun" into a 220-word prompt. It is loaded by default in the official inference code and has an `enable_prompt_upsampler` switch in ComfyUI. With Diffusers, you run the Transformers block yourself and pass the caption as `prompt`. The limitations section says output is English only, though the request can be in any language, the prompts are tuned only for FLUX 3 Image Klein, and references are downscaled (at most 1 MP for one), so small details can be described wrongly. The model does not refuse requests, and the inference code offers optional prompt and image safety checks (`--safety`). The weights, a 18.8 GB bfloat16 file, are released under Apache 2.0.
Key features
特点摘要待依据来源补齐，不凭模型名称推断能力。
Limitations & considerations
Sources are insufficient to establish specific limitations. Verify task performance, latency, data policies, licensing and version lifecycle.
Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
暂无已采集的可核验公开评分。模型未上榜不代表能力较低。
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Sources & traceability
许可证：apache-2.0。模型介绍与第三方评测均以原来源的具体版本和方法为准。