Liquid AI

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@liquidai

Build efficient general-purpose AI at every scale.

Cambridge, MA liquid.ai Joined March 2023

73 Following 46K Followers 1.6K Posts

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Liquid AI @liquidai Oct 27

Introducing 𝙻𝙵𝙼𝟹: our new generation of Liquid Foundation Models. With a new tri-hybrid architecture and new multimodal encoders, the LFM3 family is the ideal model suite for specialized intelligence.

> 6 model instances, across text, audio, vision, and omni modalities, generative and decision models.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱: text, 256k context window.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱: vision-language model with video-input support for spatial understanding
> 𝙻𝙵𝙼𝟹-𝙰𝚞𝚍𝚒𝚘-𝟸𝙱: tool calls, voice chat, reasoning in 18 languages.
> 𝙻𝙵𝙼𝟹-𝙾𝚖𝚗𝚒-𝟸𝙱: an omni model combines vision, audio, and language.
> 𝚍𝟷-𝟸𝙱 and 𝚍𝟷-𝙾𝚖𝚗𝚒-𝟸𝙱: decision models with typed outputs and calibrated probabilities in a single pass. Omni adds audio input.
> fine-tune on 1 GPU.
> a new tri-hybrid architecture
> architecture optimized for 14 processor classes across GPUs, CPUs, and NPUs.
> 𝙻𝙵𝙼𝟹-𝚅𝙻-𝟸𝙱 is a beast. It performs competitively with Gemma 4 12B (6x larger), and Gemini 3.5 Flash Lite, and GPT-5.6 Luna, with 1.9B parameters.
> 𝙻𝙵𝙼𝟹-𝟷.𝟽𝙱 is #1 on the Pareto frontier of device intelligence 𝚙𝚒𝚙𝚎𝚝𝚝𝚎.𝚕𝚒𝚚𝚞𝚒𝚍.𝚊𝚒

Every modality for specialized intelligence. Pick the one that fits your use case, customize it, and run it on-device.

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Liquid AI @liquidai 2d

Liquid 🤝 @MercedesBenz

Ramin Verified account @ramin_m_h 2d

Today @WSJ covered our work with @MercedesBenz. our flagship LFMs are now rolling out in vehicles in North America, running directly on the hardware inside the car to power in-car assistance! 🌊

this is one of the first deployments of local generative AI in the real world at scale! ✨

seeing our technology become part of someone’s everyday life is one of the most rewarding feelings of building Liquid.

years of work become a small, useful part of someone’s day. they don’t need to know which model is running. they just need it to understand them and work seamlessly.

this is really hard and it took us years of fundamental work from first principles to made happen with a brilliant team of engineers from Mercedes and Liquid.

I believe on-device AI will fundamentally change our relationship with the technology around us. embedded AI is about change of ownership.

With Mercedes-Benz, we are now in production and are building toward deployment at scale. The on-device AI revolution is taking shape in products people actually use, and I’m proud that @liquidai is helping lead it.

To our team and our partners at @MercedesBenzUSA and HQ: thank you for the care, persistence, and trust it takes to make this real.

It feels good to see the work out in the world.

wsj.com/cio-journal/me…
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Liquid AI @liquidai 3d

multimodal local conversational AI on iphone 18 Pro Max at 80 tok/s ✨

Xenova Verified account @xenovacom 3d

Real-time, local conversational AI is how we will democratize intelligence.

We just ported LFM3-Omni-2B by @LiquidAI to run fully offline on my iPhone 18 Pro Max at ~80 tok/s, powered by custom WebGPU kernels in a React Native app.

Should we release this on the App Store? 👀

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Liquid AI @liquidai 3d

Liquid 🤝 @Modular ✨

Modular Verified account @Modular 3d

LFM3 from @liquidai is now running on MAX. 🧑‍🚀

All 6 models in the suite are supported, across text, audio, vision, and omni. The implementations are open source, so you can read the code, run it, and build on it: max.modular.com/api/python/pip…

Which modality are you trying first: text, audio, vision, or omni?
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Liquid AI @liquidai 3d

Adding vision to a language model is more than one extra modality. With large images or long video, the vision encoder can use more compute than the language model itself, so efficient models need a different design. Our VLM team, including @rshubert98, @TianshuYu6, @sina_semnani, and @iamsamstevens, explains how they teach LFMs to see, from mid-training to the custom vision encoder built for LFM3.

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