black-forest-labs/flux-3-image-klein

选用指南

AI 根据 README 整理 · 2026/10/16 15:56:28

使用方式

通过命令行、Python API 或本地 Demo 使用，支持文本生成图像、图像编辑和边界框布局。

查看 README 依据

> `--no-pup` unless the prompt already is an upsampler caption ([Smaller GPUs](#smaller-gpus)). ### Text to image ```bash python scripts/cli.py "A man walking with his dog, afternoon sun" --model distilled --out out.png --seed 7 ``` Each generated image comes with a `.json` containing the prompt, size, number of steps, guidance value and seed; [examples/README.md](examples/README.md) has the command behind every image in this README. ### Edit an image ```bash python scripts/cli.py "put a red bandana around the dog's neck" --image examples/inputs/3.png --out out.png --seed 22 ```

models = Models({"distilled": str(dit_path("distilled"))}, pup=str(WEIGHTS / "pup"), pup_memory=0.35) image, record = generate(models, "distilled", "a red bicycle leaning on a white wall", images=[], seed=1) image.save("bicycle.png") image, record = generate(models, "distilled", "put a red bandana around the dog's neck", images=[Image.open("examples/inputs/3.png")], seed=22) image.save("bandana.png") ``` `Models` loads once; `generate` also takes `boxes`, `width`, `height`, `steps`, `guidance`, `pup`, `safety`. ## Demo ```bash

python scripts/app.py # http://127.0.0.1:7860; --share for a public link ``` Three tabs: **Layout** (draw boxes, type what goes in each), **Text to image**, **Edit**. `--offload`, `--fp8`, `--nvfp4` and `--no-pup` apply as in the CLI. ## Prompt upsampling The upsampler ([black-forest-labs/flux-3-image-klein-pup](https://huggingface.co/black-forest-labs/flux-3-image-klein-pup), a 9B vision-language model fine-tuned from Qwen3.5-9B) expands a short request into the detailed prompt the model

部署要求

需要 Python 3.12，安装时需指定 PyTorch CUDA 索引；BF16 和 FP8 模式需要 Ada、Hopper 或 Blackwell GPU，NVFP4 需要 Blackwell GPU。

查看 README 依据

 ### Editing examples  ### Layout examples  ### Typography  ### Base vs distilled Same prompt, same seed: distilled (16 steps) left, base (50 steps, CFG) right. On one H200 at 1 MP: about 3 s against 12 s per image.  ## Local installation To run FLUX 3 Image Klein in BF16 and FP8: ```bash python3.12 -m venv .venv && . .venv/bin/activate

pip install -e . --extra-index-url https://download.pytorch.org/whl/cu130 ``` To run FLUX 3 Image Klein in BF16, FP8 and NVFP4 (NVFP4 needs a Blackwell GPU): ```bash python3.12 -m venv .venv && . .venv/bin/activate pip install -e '.[nvfp4]' --extra-index-url https://download.pytorch.org/whl/cu130 --extra-index-url https://flashinfer.ai/whl/cu130 ``` The installation was tested on B200; see [Memory](#memory) for other GPUs. ### Weights The fast model with its prompt upsampler, 52 GB: ```bash

 ### FLUX 3 Image Klein Base, 50 steps  ## Memory Peak GPU memory (nvidia-smi) on a B200 at 1024x1024, text-to-image and an edit with one reference: | | bf16 | `--fp8` | `--nvfp4` | |---|---|---|---| | `cli.py --model distilled --no-pup` | 31 GB | 26 GB | 25 GB | | `cli.py --model base --no-pup` | 31 GB | 29 GB | 26 GB | The upsampler reserves `--pup-memory` of the GPU (default 0.35). `--fp8` needs Ada, Hopper or Blackwell; `--nvfp4`

已知限制

代码没有 int8 路径，在 RTX 30 系列及更老的 GPU 上需使用 ComfyUI 的 int8 文件；提示词上采样器默认启用，禁用会显著降低结果质量。

查看 README 依据

needs Blackwell and the `[nvfp4]` install, not with `--offload`. This code has no int8 path. On GPUs without FP8 (RTX 30 series and older) use the int8 files from [black-forest-labs/flux-3-image-klein-comfy](https://huggingface.co/black-forest-labs/flux-3-image-klein-comfy) in ComfyUI. ## Safety Off by default; `--safety` (CLI) or **Advanced, Safety checks** (demo). Prompts, reference images and outputs are checked for copyrighted characters, brands and public figures (VLM) and for NSFW content (classifier); anything flagged

| Generation and editing, self-hosting | FLUX 3 Image Klein (distilled): the same model in 16 steps without CFG, about 6x faster | | Fine-tuning, LoRA training, research | FLUX 3 Image Klein Base | | An 8 GB GPU (RTX 3070 class) | the int8 files in [ComfyUI](#run-it-elsewhere) | > [!IMPORTANT] > Do not use either model without the [prompt upsampler](#prompt-upsampling). The model is trained on the captions it > writes; a prompt sent as typed gives noticeably weaker results. It is on by default in the CLI, the demo and the > Python API. ### Text-to-image examples