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Redefining what’s possible on the edge.

Liquid’s edge-native stack delivers the fastest AI with zero cloud dependencies — powered by LFM2, built with LEAP, experienced in Apollo.

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LEAP: Liquid Edge AI Platform 02\
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LFM2: On-device foundation models

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AI designed with your business in mind.

Streamlined implementation

Liquid provides end-to-end AI expertise under one roof, offering customizable architectures and full access to the AI value chain, for seamless, high-performance deployment.

Customizable models

Liquid offers a full-stack toolkit empowering engineers to tailor Liquid Foundation Models, optimizing architecture, data, policy, and hardware for your business needs.

Compute efficient

Liquid maximizes compute efficiency by optimizing inference beyond traditional transformers, delivering faster AI with less power that fully leverages your hardware.

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AI for any scale, any environment.

Small language models

Small language models

LFMs are designed for efficiency, enabling deployment across a range of devices—from edge computing environments to cloud infrastructures—while maintaining high performance and a reduced memory footprint.

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Introducing LFM2: The Fastest On-Device Foundation Models on the Market\
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Purpose-built

AI that fits your hardware, 
your tasks, your needs.

Inspired by biological neural systems, our networks adapt and learn in real-time, enhancing efficiency and flexibility compared to traditional AI models. ​

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Foundation models

A fundamentally different architecture

Our Liquid Foundation Models (LFMs) leverage liquid neural networks, inspired by dynamical systems and signal processing, to process complex, sequential, and multimodal data with superior reasoning and flexibility.

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News

Keep up with Liquid

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Community\
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Hack the Edge San Francisco: Accelerating What’s Possible with Edge-Native AI \
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11.18.25

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Company\
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Liquid AI Announces Multi‑Year Partnership with Shopify to Bring Sub‑20ms Foundation Models to Core Commerce Experiences \
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11.13.25

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Product\
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LFM2-ColBERT-350M: One Model to Embed Them All \
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10.28.25

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