Welcome FLUX.3 Image Klein in Diffusers
Black Forest Labs has introduced FLUX.3 Image Klein, now available in Diffusers. This model supports both text-to-image and multi-reference image-to-image generation. A key new feature is "layout control," which allows users to define bounding boxes in prompts to specify object placement or to move parts of a reference image. This enables precise manipulation of image elements, as demonstrated by moving a "miniature grey amigurumi knight" within an image while preserving other elements.
时间与来源
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发布当时偏移：UTC+02026年10月15日 00:00 UTC
收录当时偏移：UTC+02026年10月15日 16:00 UTC
- 发布
- 2026年10月15日 00:00
- 收录
- 2026年10月15日 16:00
- 来源类型
- 官方发布
- 档位
- 当事方
- 信源状态
- 正常
档位是按信源手工设定的编辑判断，不是逐条打分。
讨论趋势
百分比基于采集到的讨论信号，不代表新增评论数或独立参与人数。曲线仅用于同一话题在不同时段的比较。
Black Forest Labs FLUX.3 Image Klein is here, and it runs in Diffusers from day one. One model does text-to-image and multi-reference image-to-image, and it adds something new, the layout control. You write bounding boxes into the prompt to say where each part of the image should go, or which parts of a reference image to move.
Both open checkpoints are in the FLUX.3 Image Klein collection :
Checkpoint What it is Defaults
black-forest-labs/flux-3-image-klein Time step distilled, for fast inference 16 steps, no CFG
black-forest-labs/flux-3-image-klein-base Base model 50 steps, CFG
You can head on to the Hugging Face space and generate some images right now!
TL;DR
- One model for text-to-image, multi-reference image-to-image, and bounding-box layout control.
- The distilled checkpoint makes a 1024 × 1024 image in about 2 seconds on an H100.
- NVFP4 and FP8 weights load with from_single_file, for smaller GPUs.
- LoRA training scripts for both text-to-image and image editing.
- Ships as a Modular Diffusers pipeline, so you can pop blocks out or add your own.
Contents
- Getting started
- What FLUX.3 can do
- Base model and quantized variants
- LoRA finetuning
- What it costs to run
- The architecture
- Modular Diffusers
- Try it
Getting started
Install the latest diffusers and transformers (for the Qwen3-VL text encoder):
pip install -U diffusers transformers