Model reference · open weights
flux-3-image-klein is an open-weight image model from Black Forest Labs. flux-3-image-klein (BF16) weighs 11.4 GB; the smallest configuration that runs it is RTX 4090 24 GB.
For self-hosting, compare this build's requirements below with the GPU you plan to rent.
Summary of the black-forest-labs/flux-3-image-klein model card, 2026-10-16
What it is
| Released by | Black Forest Labs |
|---|---|
| Released | 2026-10-13 |
| Parameters | 5.5B |
| VRAM | 11.4 GB for the weights |
What it runs on
| Card | One image | Memory |
|---|---|---|
| RTX 3060 12 GB … RTX 4060 Ti 16 GB | does not fit | |
| RTX 3090 24 GB | fits | 23.4 GB |
| RTX 4090 24 GB | fits | 23.4 GB |
| RTX 5090 32 GB | fits | 31.0 GB |
| L40S 48 GB | fits | 44.0 GB |
| A100 80 GB | fits | 78.2 GB |
| H100 80 GB | fits | 78.1 GB |
| RTX PRO 6000 Blackwell 96 GB | fits | 93.8 GB |
| DGX Spark (GB10) 128 GB unified | fits | 107 GB |
| H200 141 GB | fits | 138 GB |
| B200 180 GB | fits | 176 GB |
Builds
| Build | Params | Precision | Weights | Smallest setup |
|---|---|---|---|---|
| flux-3-image-klein (above) ↗ | 5.5B | BF16 | 11.4 GB | RTX 4090 24 GB |
| flux-3-image-klein-base ↗ packaged by unsloth |
5.5B | BF16 | 11.4 GB | RTX 4090 24 GB |
| flux-3-image-klein-base-FP8 ↗ packaged by unsloth |
5.5B | FP8 | 23.1 GB | RTX 4060 Ti 16 GB |
| flux-3-image-klein-base-GGUF ↗ packaged by unsloth 10 builds: Q2_K_XL 2.6 GB … BF16 11.1 GB the transformer alone, to use with the text encoders and VAE |
GGUF | 3.6 GB | RTX 3060 12 GB |
From the model card
Ungated mirror of black-forest-labs/flux-3-image-klein-base, republished by Unsloth so it can be downloaded without a Hub gate. The weights are unmodified. See NOTICE.md and LICENSE.md in this repo for the terms, which are the upstream terms and are unchanged.
FLUX 3 Image Klein is a 5.6B open weights model for text-to-image generation and image editing. It takes a prompt and up to 10 reference images and returns one image. Text-to-image, single-reference edits and multi-reference compositions run through the same model, with Qwen3-VL-4B-Instruct as the text encoder.
The 5.6B parameter label refers to the image transformer; the text encoder is separate.
This repository holds the undistilled base checkpoint, for fine-tuning, LoRA training and research. You can find the distilled checkpoint here: FLUX 3 Image Klein.
Inference code, prompt upsampling and the bounding box format: black-forest-labs/flux-3-image-klein on GitHub.
Do not use the model without a prompt upsampler. FLUX 3 Image Klein takes full scene captions, for text-to-image, editing and layout with boxes alike; a short prompt sent as typed gives generic output. Use ours, flux-3-image-klein-pup, which the reference code loads by default, or any LLM you prefer with a system prompt that expands the request into one full scene caption (system_prompts.json has ours). Diffusers runs neither on its own; see Prompt upsampling.
This repository includes the BF16 transformer and FP8 and NVFP4 variants, together with the Qwen3-VL-4B-Instruct text encoder and image autoencoder.
| Checkpoint | Format | Steps | Guidance | Built for |
|---|---|---|---|---|
| Klein Base | undistilled, bfloat16 | 50 | 3.5 | fine-tuning, LoRA training, research |
| Klein | distilled, bfloat16 | 16 | none | generation and editing, self-hosting; the checkpoint behind the BFL API |
Download the root BF16 package and shared components without downloading the quantized variants:
from huggingface_hub import snapshot_download
snapshot_download(
repo_id="black-forest-labs/flux-3-image-klein-base",
local_dir="weights/flux-3-image-klein-base",
allow_patterns=[
"model.safetensors", "config.json", "manifest.json",
"ae.safetensors", "text_encoder/*",
"README.md", "LICENSE.md", "NOTICE.md",
],
)
To download a quantized transformer instead, replace the three root transformer patterns (model.safetensors, config.json, and manifest.json) with variants/fp8r/* or variants/nvfp4/*. Keep ae.safetensors and text_encoder/* for the shared components.
These files contain the model package, not a complete inference application. Use an inference implementation that supports this checkpoint format. Quantized packages need a loader that supports their format; their file size is not a measure of total GPU memory use.
The distilled checkpoint is served on the BFL API as FLUX 3 Image Klein. The reference inference code is black-forest-labs/flux-3-image-klein.
From the reference implementation checkout, install the package and download the two components the CLI loads besides this checkpoint. The CLI reads its weights from weights/ (set WEIGHTS_DIR for another root), where the download above puts this repository.
pip install -e .
# safety classifier, always loaded
hf download Falconsai/nsfw_image_detection --local-dir weights/nsfw-classifier
# prompt upsampler (18.8 GB), on by default; --no-pup sends the prompt as typed, for captions written by another LLM
hf download black-forest-labs/flux-3-image-klein-pup --local-dir weights/pup
# text-to-image
python scripts/cli.py 'A chunky knitted diorama: three white cable-knit icebergs with tiny pale blue houses, a cream banner embroidered "KNITTED ICEBERG VILLAGE", a giant magenta knitted whale tail bursting from a yarn sea' \
--model base --out knitted.png
# image editing; repeat --image for multiple references
python scripts/cli.py 'the same scene at night under a knitted full moon, embroidered stars above the peaks' \
--model base --image knitted.png --out knitted_night.png
FLUX 3 Image Klein uses a modular pipeline. Pass prompt for text-to-image generation, or pass image with a prompt for editing; image can be one image or a list of reference images. The model takes full scene captions, not short prompts: a request sent as typed gives generic output. Every request below goes through the prompt upsampler first, a separate 9B model ([black-forest-labs/flux-3-image-klein-pup](https://huggingface.co/blac
Quoted from the model card on Hugging Face. The full card is behind the Hugging Face link above.
Running it yourself
Rent a machine by the hour. How to run this model is on its model card.