LFM2:3B in space, on Cluster Gate2: ✨
“This image is a highly detailed, close-up view of Earth as seen from space, likely captured by a satellite or space telescope. The Earth is depicted as a large, circular sphere with a predominantly blue hue, indicating the vast oceans that cover most of its surface. The blue is interspersed with swirling white clouds, which are particularly prominent over the landmasses, suggesting the presence of weather systems and atmospheric activity.
The overall composition of the image highlights the beauty and complexity of our planet, showcasing the dynamic interplay between the oceans, atmosphere, and landmasses."
Congratulations to @DPhiSpace for this incredible milestone! 🌎
We’re entering a multi-year partnership with @MercedesBenz to scale embedded, on-device intelligence for their third- and fourth-generation MBUX.
Our goal: to make the driver/vehicle relationship even more natural and effortless.
Read more about our partnership: https://t.co/Glpu87KuJs
Today, we release LFM2.5-350M. Agentic loops at 350M parameters.
A 350M model trained for reliable data extraction and tool use, where models at this scale typically struggle.
<500MB when quantized, built for environments where compute, memory, and latency are constrained.
🧵
AI is beginning to move beyond the clouds…
Registration is open for Hack #05: AI in Space, in collaboration with @DPhiSpace. A hackathon exploring what becomes possible when AI operates closer to satellites, orbital systems, and space-based data.
For developers, researchers, and builders interested in the future of AI in space.
Register → https://t.co/3HMcL2E9zo
Learn more → https://t.co/Y0Qs1KN01j 🚀
Join the conversation → https://t.co/j4hJBMRdJI
> 385ms average tool selection.
> 67 tools across 13 MCP servers.
> 14.5GB memory footprint.
> Zero network calls.
LocalCowork is an AI agent that runs on a MacBook. Open source.
🧵
In the AI era, “discoverable” = “queryable.”
If a website or webapp has dynamic data (locations, inventory, pricing, availability) an API isn’t a nice-to-have anymore. It’s how AI agents discover and route users to services and products.
My Clawdbot lives in a Mac mini inside a G4 iMac. I asked it to create an animated face for itself and it just did it. Even added a sleeping animation I didn’t ask for initially.
Incredible @steipete
Today, we’re announcing our partnership with @Shopify to bring Liquid Foundation Models (LFMs) to core commerce experiences. Shopify will license LFMs to enhance search and recommendations, improving relevance, conversions, and customer experience at scale.
The first production deployment is a sub‑20ms LFM that enhances search.
Shopify and Liquid have also co-developed a generative recommender model with a novel HSTU architecture. In controlled tests, the model beat the previous stack, leading to higher conversion rates from recommendations. 👇
Introducing Liquid Nanos ⚛️ — a new family of extremely tiny task-specific models that deliver GPT-4o-class performance while running directly on phones, laptops, cars, embedded devices, and GPUs with the lowest latency and fastest generation speed.
> model size: 350M to 2.6B
> built on LFM2, our v2 efficient model architecture
> perform competitively with models up to hundreds of times larger
> enable core agentic tasks: precise data extraction, multilingual translation, tool call, math, and RAG. 1/n
Big step for on-device AI:
Liquid AI’s Edge Platform, LEAP, now supports @AMD Ryzen™ and Ryzen AI™ processors, bringing powerful, low-latency AI directly to laptops.
Here’s what it means for developers and enterprises 🧵
Every time I try an “AI plugin” for Zotero, I’m reminded that dreams and reality are very different things. Would love to see a make a Zotero-Cursor hybrid
we will be having 3 grand hackathons soon at @liquidai offices in Boston, SF, and Tokyo. This is called “Bohemian Rhapsody, the Liquid edition”. you will build a wild ai agent with a swarm of tiny models to match/surpass frontier models in the real-world app of choice.
join our discord channel to learn more: liquid-ai
what do you want as the prize pool?
Today, we release LEAP, our new developer platform for building with on-device AI — and Apollo, a lightweight iOS application for vibe checking small language models directly on your phone.
With LEAP and Apollo, AI isn’t tied to the cloud anymore. Run it locally when you want, for speed, privacy, and reliability, using LEAP’s end-to-end toolkit for on-device AI.
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Try LFM2 with llama.cpp today!
We released today a collection of GGUF checkpoints for developers to run LFM2 everywhere with llama.cpp
Select the most relevant precision for your use case and start building today.
https://t.co/9MIIajq6i1
Today, we release the 2nd generation of our Liquid foundation models, LFM2.
LFM2 set the bar for quality, speed, and memory efficiency in on-device AI.
Built for edge devices like phones, laptops, AI PCs, cars, wearables, satellites, and robots, LFM2 delivers the fastest on-device gen-AI experience on the market. 1/