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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/mercedes…

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. 1/ 🧵

Today we release 𝚍𝟷-𝚞𝚕𝚝𝚛𝚊, our most powerful decision model. > built for hard decision problems. > d1-ultra is multimodal > supports 44 languages > #1 on the @ArtificialAnlys Decision Index (65) > leads all eight categories of our 112-evaluation suite 1/

Please when @liquidai @maximelabonne

Announcing d1, our first decision model. It's the first model to outperform Jev on @huggingface's Decision Index. > wins on multilingual evals > more robust against prompt injection > handles longer inputs more effectively > built for fast, structured decision-making in software environments > Liquid API: console.liquid.ai > Available on OpenRouter soon

this guy literally explained the truth about the "ADHD superpower"

slowly, @liquidai will power more machines than @AnthropicAI not if, when. their 450M-param model already runs wildfire risk detection on satellite imagery, on-device, sub-250ms, no cloud round trip needed small models doing real jobs while everyone argues about agent skills

ADHD is closely linked to a delayed body clock. Early evidence suggests correcting this delay can also improve ADHD symptoms.

*in 2026 AI will cure cancer* AI in 2026:

They haven’t even released the king yet. 👑