The German AI startup Black Forest Labs (BFL), founded by former Stability AI engineers, is continuing to build out its suite of open source AI image generators with the release of FLUX.2 [klein], a new pair of small models — one open and one non-commercial — that emphasizes speed and lower compute requirements, with the models generating images in less than a second on a Nvidia GB200. The [klein] series, released yesterday, includes two primary parameter counts: 4 billion (4B) and 9 billion (9B).The model weights are available on Hugging Face and code on Github.While the larger models in the FLUX.2 family ([max] and [pro]), released in November of 2025, chase the limits of photorealism and “grounding search” capabilities, [klein] is designed specifically for consumer hardware and latency-critical workflows.In great news for enterprises, the 4B version is available under an Apache 2.0 license, meaning they — or any organization or developer — can use the [klein] models for their commercial purposes without paying BFL or any intermediaries a dime. However, a number of AI image and media creation platforms including Fal.ai have begun offering it for extremely low cost as well through their application programming interfaces (APIs) and as a direct-to-user tool. Already, it’s won strong praise from early users for its speed. What it lacks for in overall image quality, it seems to make up for in its fast generation capability, open license, affordability and small footprint — benefitting enterprises who want to run image models on their own hardware or at extremely low cost. So how did BFL do it and how can it benefit you? Read on to learn more.The “Pareto Frontier” of LatencyThe technical philosophy behind [klein] is what BFL documentation describes as defining the “Pareto frontier” for quality versus latency. In simple terms, they have attempted to squeeze the maximum possible visual fidelity into a model small enough to run on a home gaming PC without a noticeable lag.The performance metrics released by the company paint a picture of a model built for interactivity rather than just batch …
