media MarkTechPost · 2h ago · releases

Liquid AI releases LFM2.5-VL-3B, a 3B on-device vision-language model with tool calling

from English

Liquid AI has released LFM2.5-VL-3B, a 3.1B-parameter vision-language model designed for efficient on-device deployment. The model reads digital screens across mobile, web, and desktop environments, grounds objects to coordinates, parses documents, and executes tool calls from text or image inputs.

Performance: Averages 69.4 across 28 vision benchmarks, matching InternVL-3.5-4B and trailing Qwen3.5-4B by 0.7 points.
New Capabilities: Introduces function calling (ToolSandbox 59.5, BFCL v4 32.5) and improved grounding (RefCOCO-avg 87.9).
Efficiency: Fits in ~3 GB of memory, decoding 228 tokens/s on Apple M5 Max.
Licensing: Free commercial use for companies under $10M annual revenue; larger enterprises must negotiate a license.

The model is non-reasoning to keep latency low and ships in native, GGUF, ONNX, and MLX formats with support for llama.cpp, MLX, vLLM, SGLang, and ONNX runtimes.

Importance 2/3 MarkTechPost Multimodal Open weights

Benchmarks

Benchmark	Model	Score
IFEval	LFM2.5-VL-3B	82.3%
MathVista	LFM2.5-VL-3B	68.5%
Berkeley Function-Calling Leaderboard	LFM2.5-VL-3B	32.5%

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