Native device foundation models

Advanced intelligence for processors outside of data centers. Built for the latency, privacy, and hardware constraints of the physical world.

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Mercedes-Benz and Liquid AI partner to scale embedded in-car intelligence

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AI for everyone

Maximum intelligence. Minimum compute.

Enterprise Solutions

End-to-end custom AI tailored to your business

We deliver full-scale custom AI solutions tailored to your business’ needs, hardware and data. Our unique process for developing efficient models is rooted in our proprietary device-aware model architecture search, allowing us to quickly provide the best fit model for latency, privacy and security critical needs - on device, in the cloud, or hybrid.

startup solutions

Own your moat with specialized AI

Amplify your startup’s growth and create competitive advantage with customized LFMs. Through our startup program, selected startups gain access to our full stack along with guidance from our product and engineering teams to specialize and deploy the best model for your business.

Developer Solutions

Specialize and deploy LFMs anywhere

Through our developer tools and community we’re making building, specializing and deploying highly efficient powerful AI accessible to everyone, from devs just getting started to experts building at scale.

Liquid Foundation Models

The most efficient models on the market

Our LFMs are purpose-built 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, while delivering best-in-class performance. So you get AI that works - everywhere you need it.

Our LFM2 family includes a range of modalities and parameter sizes and are rapidly customizable to deliver AI that’s just right for your use case.

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Lightweight scientific foundation models for pharmaceutical research

With Insilico Medicine, we produced LFM2-2.6B-MMAI – a single checkpoint trained to perform at state-of-the-art levels across multiple drug discovery subdomains, not a patchwork of separate point models.

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