FLUX 3 Image Klein
Model page • Weights • Demo
This repository contains the reference inference code for FLUX 3 Image Klein, the 5.6B open weights image model from Black Forest Labs: text-to-image, editing with up to 10 reference images, and layout control with bounding boxes, through one model. It ships with a prompt upsampler; do not use the model without it.
Performance
Leads in quality and speed among open weights models: the Pareto frontier of Elo rating against latency, for text-to-image and for image editing.
Elo from our internal evaluations; median API latency for a 1 MP image.
Model overview
| Name | Steps | Guidance | Resolution | Text-to-image | Editing (up to 10 references) | Bounding boxes | License |
|---|---|---|---|---|---|---|---|
| FLUX 3 Image Klein | 16 | none | up to 4K | ✅ | ✅ | ✅ | FLUX Kommunity License |
| FLUX 3 Image Klein Base | 50 | CFG 3.5 | up to 4K | ✅ | ✅ | ✅ | FLUX Kommunity License |
| FLUX 3 Image Klein Prompt Upsampler | Apache 2.0 |
Which model should I use?
| Need | Recommended |
|---|---|
| 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 |
Important
Do not use either model without the prompt upsampler. 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
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:
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):
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 for other GPUs.
Weights
The fast model with its prompt upsampler, 52 GB:
hf download black-forest-labs/flux-3-image-klein --local-dir weights/flux-3-image-klein --exclude 'variants/*'
hf download black-forest-labs/flux-3-image-klein-pup --local-dir weights/pup
hf download Falconsai/nsfw_image_detection --local-dir weights/nsfw-classifierEverything, 107 GB:
hf download black-forest-labs/flux-3-image-klein-base --local-dir weights/flux-3-image-klein-base hf download black-forest-labs/flux-3-image-klein --local-dir weights/flux-3-image-klein hf download black-forest-labs/flux-3-image-klein-pup --local-dir weights/pup hf download Falconsai/nsfw_image_detection --local-dir weights/nsfw-classifier
WEIGHTS_DIR points at another root (default ./weights). The quantized DiTs live under variants/fp8r and
variants/nvfp4 in each repository; the text encoder and autoencoder ship with both. weights/pup is the
prompt upsampler, which the model needs.
Run the CLI
Important
The commands below send the prompt through the upsampler before the model. Do not pass
--no-pup unless the prompt already is an upsampler caption (Smaller GPUs).
Text to image
python scripts/cli.py "A man walking with his dog, afternoon sun" --model distilled --out out.png --seed 7Each generated image comes with a .json containing the prompt, size, number of steps, guidance value and seed; examples/README.md has the command behind every
image in this README.
Edit an image
python scripts/cli.py "put a red bandana around the dog's neck" --image examples/inputs/3.png --out out.png --seed 22Up to 10 references; the first one sets the output size:
python scripts/cli.py "print the dog from the second image onto the mug" \
--image examples/inputs/2.png --image examples/inputs/3.png --out out.png --seed 23Place elements with bounding boxes
python scripts/cli.py "hot-air balloons over a green valley at sunrise" \
--boxes examples/inputs/balloons_boxes.json --out out.png --seed 1Format in Bounding boxes.
Smaller GPUs
--fp8 (Ada, Hopper, Blackwell) or --nvfp4 (Blackwell) load the quantized DiTs. When the upsampler and the model do
not fit on the GPU together, run the upsampler on its own first and pass its caption with --no-pup:
python -m flux3.pup --prompt "A man walking with his dog, afternoon sun" --out prompt.txt python scripts/cli.py "$(cat prompt.txt)" --model distilled --fp8 --no-pup --out out.png
Numbers in Memory.
From Python
from PIL import Image from flux3.generate import Models, generate from flux3.pipeline import WEIGHTS, dit_path 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
python scripts/app.py # http://127.0.0.1:7860; --share for a public linkThree 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,
a 9B vision-language model fine-tuned from Qwen3.5-9B) expands a short request into the detailed prompt the model
works best with, before it reaches the text encoder. It is on by default in the CLI, the demo and generate. Do not use
the model without it, for text-to-image, editing and layout alike: --no-pup sends the prompt as typed, and the results
are noticeably weaker.
| input prompt | what the model saw |
|---|---|
double exposure portrait: a young East Asian man facing the camera, a larger translucent profile of him facing left layered over him, muted blues, film grain, silver hoop earring |
"Digital double-exposure portrait in a muted blue monochrome palette, framed as a head-and-shoulders composition with visible 35mm film grain. Centered in the foreground, a young East Asian man in his twenties faces the camera directly ... a polished silver hoop earring hangs from his left ear. His face remains sharply defined beneath a larger translucent profile of the same man layered across it, facing left ..." (214 words, examples/upsampling/double_exposure_s1.json) |
python scripts/cli.py "double exposure portrait: a young East Asian man facing the camera, a larger translucent profile of him facing left layered over him, muted blues, film grain, silver hoop earring" \
--model distilled --width 832 --height 1248 --seed 1 --out out.pngUpsample without generating:
python -m flux3.pup --prompt "double exposure portrait: a young East Asian man facing the camera, a larger translucent profile of him facing left layered over him, muted blues, film grain, silver hoop earring" --out prompt.txtBounding boxes
boxes.json is a list of boxes, [y_min, x_min, y_max, x_max] in 0 to 1, top-left origin:
[{"id": "obj_1", "desc": "a red hot-air balloon", "bbox": [0.08, 0.10, 0.45, 0.42]},
{"id": "obj_2", "desc": "a lighthouse on a cliff", "bbox": [0.30, 0.60, 0.95, 0.90]}]For edits, a box is {"id", "desc", "from": "ref_image_0" | "target", "src_bbox", "tgt_bbox"}: where it is in
a reference, where it goes in the output, or both.
Run it elsewhere
| ComfyUI | black-forest-labs/flux-3-image-klein-comfy: bf16, int8 and NVFP4 files for both models. The int8 files run on 8 GB GPUs such as the RTX 3070 |
| Diffusers | from launch day |
| SGLang, vLLM | from launch day |
Benchmarks
Seconds per image, one image per run, fastest build per GPU: NVFP4 on Blackwell data-center and DGX parts, int8 on the RTX cards (the ComfyUI files, Run it elsewhere).
FLUX 3 Image Klein, 16 steps
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
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 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
is refused. Saved images carry EXIF tags (Software: AI generated, Make: Black Forest Labs).
License
The code in this repository is released under the Apache License 2.0. The FLUX 3 Image Klein weights are under the FLUX Kommunity License; the prompt upsampler is Apache 2.0.
Citation
@misc{flux-3-image-klein-2026, author={Black Forest Labs}, title={{FLUX 3 Image Klein}}, year={2026}, howpublished={\url{https://bfl.ai/models/flux-3-image-klein}}, }