Flux.3 Image Klein Is Out: Specs, Pricing and Access

What is FLUX 3 Image Klein?

FLUX 3 Image Klein is a 5.6B parameter open weights image model from Black Forest Labs for text-to-image generation, image editing and multi-reference generation. It shares core capabilities with the full FLUX 3 Image model, including native 4K generation and bounding boxes. BFL released it on November 3, 2026.

BFL's own account said the same day that the model had reached 1M+ downloads and is "designed for precise editing." A Reddit post from u/MonkeyBoyPoop says BFL updated its documentation to clarify that Klein is primarily built for editing. The Hugging Face card describes it the same way.

The release includes a base model for fine-tuning and a step distilled model for low-latency generation. FP8, INT8 and NVFP4 builds were developed with NVIDIA support.

FLUX 3 Image Klein release date and availability

FLUX 3 Image Klein is available now. BFL announced it on November 3, 2026, with weights on Hugging Face, an endpoint in the BFL API, and ready-made ComfyUI workflows and Diffusers support.

The distilled checkpoint is the one served through the BFL API. The base checkpoint is on Hugging Face only. Both repositories are publicly accessible but require you to accept the license conditions before downloading files.

BFL says LoRA training works from day one in Diffusers and Ostris's AI Toolkit, and that NVIDIA's NeMo AutoModel ships recipes for the released checkpoints.

FLUX 3 Image Klein key features and specs

Klein handles editing, text-to-image and multi-reference composition in one model, taking a prompt and up to 10 reference images and returning one image. Output goes up to 4K. Qwen3-VL-4B-Instruct serves as the text encoder.

Translucent bounding frames placed over a product scene on a gridded layout

The 5.6B figure refers to the image transformer only. The text encoder is separate.

Bounding boxes sit on a 0 to 1000 grid in the prompt. You can place elements, then recolor, move, replace or remove them. BFL states that boxes guide placement and scale and do not act as a hard pixel mask. Text rendering inside images is also listed as a feature.

The prompt upsampler requirement

BFL repeats one instruction across its docs: always run a prompt upsampler. Klein is trained on full scene captions, and a short prompt sent as typed gives generic output.

BFL offers flux-3-image-klein-pup, which the reference code and ComfyUI workflows run by default. Any LLM with a system prompt that expands the request into one full scene caption also works. The Diffusers pipeline does not call the upsampler itself.

FLUX 3 Image Klein pricing and free access

Through the BFL API, FLUX 3 Image Klein costs $0.008 to $0.036 per image depending on output resolution. Text-to-image and editing are priced the same. The weights are free to download, subject to the FLUX Kommunity License.

A desktop PC with a graphics card beside printed ad mockups

The license permits non-commercial use and provides a commercial-output exception for Qualifying Users, subject to its terms. BFL's materials do not spell out who qualifies in the text available here, so check LICENSE.md before using self-hosted outputs in paid campaigns.

Can you run FLUX 3 Image Klein locally?

Yes. BFL says the generator weights need 11.2 GB in BF16 and 5.6 GB in FP8, and the INT8 build runs on NVIDIA GeForce RTX GPUs with as little as 8GB of VRAM through ComfyUI or Diffusers. The docs also say it fits down to an RTX 3090.

BFL reports that the distilled model with the INT8 build generates a 1MP image in about 4 seconds on an RTX 5090 and under 9 seconds on an RTX 4070 in ComfyUI. NVIDIA measured those figures. Quantized files are smaller than total GPU memory use, so leave headroom for the text encoder and upsampler.

FLUX 3 Image Klein vs competing models

In BFL's internal evaluations, Klein ranks first in text-to-image, multi-reference generation and image editing among the open weights models compared. It also rates above the closed models Ideogram V4.5 and FLUX.2 [pro]. These are the maker's own numbers, not independent benchmarks.

Through the API, BFL says Klein has lower latency than Qwen-Image 2.1, FLUX.2 [pro], Ideogram V4.5 and Krea 2. BFL timed Klein on its own servers and timed the other models from the client, so the latency comparison is not like for like.

How to use FLUX 3 Image Klein for AI video and static ads

For ad teams, Klein's most relevant strengths are editing and multi-reference input. Swapping a background, recoloring a product or moving and replacing elements with bounding boxes are jobs the model is built for, at a low per-image cost.

Practical fits, based on the specs:

• Product variants: feed up to 10 references (product, packaging, scene) and compose one image.
• Static ad resizing and layout tests: use bounding boxes to hold element placement across versions.
• Video start frames: generate or edit a clean first frame at up to 4K before sending it to a video model.
• Brand look: train a LoRA from the base checkpoint.

Teams that want to compare it against other models can try it in the AdGraam AI Playground. For repeatable edit, upscale and video chains, Flow Builder fits. Our guide to making static ads with AI covers the broader workflow.

What to watch next

Three things are open. Independent benchmarks will show whether BFL's internal rankings hold on ad-style prompts. The license terms for commercial output need a careful read. And the prompt upsampler requirement adds a step to any pipeline that skips BFL's default workflows.

BFL also says it works with teams on customizations for lower latency, but has not published details. For another open image model, see our piece on P-H3-Image from Pruna.