LFM2.5 model family is Liquid AI's most capable release yet for edge AI deployment. It builds on the LFM2 device-optimized architecture and represents a significant leap forward in building reliable agents on the edge.

LFM2-Audio defines a new class of audio foundation models: lightweight, multimodal, and real-time. By unifying audio understanding and generation in one compact system, it enables conversational AI on devices where speed, privacy, and efficiency matter most.

Liquid Nanos are a family of small, specialized foundation models from Liquid AI. They are designed to run on-device for tasks like data extraction, RAG, and tool use, delivering frontier-grade performance without the cloud.

LFM2-VL is a new series of open-weight vision-language models from Liquid AI. Designed for on-device deployment, they offer up to 2x faster inference on GPU and come in 450M and 1.6B parameter sizes.

LFM2 by Liquid AI is a new class of open foundation models designed for on-device speed and efficiency. Its hybrid architecture delivers 2x faster CPU performance than Qwen3 and SOTA results in a tiny footprint.