Liquid Foundation Models

Models built for real-world constraints.

We’ve redefined what’s possible with our proprietary architecture, designed for efficiency, speed, and real-world deployment on any device.

From wearables to robotics, phones, laptops, cars, and more, LFMs run seamlessly on GPUs, CPUs, or NPUs, making intelligence accessible everywhere.

Explore LFMs

All our models leverage Liquid Neural Networks, a proprietary architecture rooted in dynamical systems and signal processing, to deliver frontier-grade intelligence at a fraction of the compute, on any hardware, on or off the cloud.

Every LFM is free to download, run, and fine-tune — including commercially — until your company passes $10M in annual revenue. See pricing & licensing

Customize your model with us

Vision-Language Models

Multimodal models using vision and text inputs and outputs with capabilities designed for low latency and device aware deployment.

Audio Model

End-to-end foundation model for audio and text generation. Designed for low latency, it enables responsive, high-quality conversations with only 1.5 billion parameters.

Built for efficient inference everywhere you need it.

Unmatched speed, quality, and memory-efficiency on the edge, or in the cloud.

Whether deploying on smartphones, laptops, vehicles, or any other device, LFMs run efficiently on CPU, GPU, and NPU hardware. Designed for millisecond latency, on-device resilience, and data privacy, LFMs unlock the full potential of local, cloud, and hybrid AI across industries.

Prefill performance on the Samsung Galaxy S24, showing tokens per second across context lengths from 128 to 8192 for LFM2-350M, LFM-700M, LFM-1.2B compared against Phi-1.5, Qwen3-1.7B, Llama-3.2-1B-Instruct, and Qwen3-0.6B.

Fig. 1. Prefill performance on CPU in ExecuTorch