Models & Releases

Liquid AI Releases LFM2.5-VL-3B: A 3B Vision-Language Model That Reads Screens, Grounds Objects, and Calls Tools On-Device

Yesterday, Liquid AI released LFM2.5-VL-3B. It is a 3.1B-parameter vision-language model built for on-device deployment. The model reads digital screens across mobile, web, and desktop. It grounds objects to coordinates, parses documents and charts, and calls tools from text or image input. Liquid AI reports an average of 69.4 across 28 vision benchmarks. That matches InternVL-3.5-4B and sits 0.7 points behind Qwen3.5-4B, both 4.7B models. The model is non-reasoning, so it answers directly and

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Liquid AI released LFM2.5-VL-3B, a 3.1-billion-parameter vision-language model designed to run on individual devices rather than remote servers. The model can read screens on phones and computers, identify objects and their locations, extract text from documents, and execute tool commands, all while using roughly 3 gigabytes of memory. It performs comparably to larger models on standard benchmarks and shows particular strength in screen and document understanding tasks, making it relevant for applications like automated testing, invoice processing, and offline translation. The model is available under a license that permits free commercial use for companies earning under 10 million dollars annually, while larger enterprises must negotiate paid licenses.

Explainer: How to Actually Read an AI Benchmark (Without Being Fooled)

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