Introducing LFM2.5: The Next Generation of On-Device AI | Liquid AI
Today, we're excited to announce the LFM2.5-1.2B model family, our most capable release yet for edge AI deployment. It builds on the LFM2 device-optimized architecture and…
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Introducing Liquid Labs: Defining the Frontier of Intelligence through Innovation | Liquid AI
Research has been core to Liquid AI from the start. Today, we’re giving that work a formal name: Liquid Labs, our team driving fundamental breakthroughs in…
LFM2: Advancing Open Science in AI | Liquid AI
At Liquid AI, we believe that scientific progress accelerates when knowledge is shared openly. Today, we're pleased to release the full technical report for LFM2, our…
Hack the Edge San Francisco: Accelerating What’s Possible with Edge-Native AI | Liquid AI
This weekend, more than 70 engineers, researchers, and builders converged at Liquid AI’s San Francisco office for Hack the Edge, a 48-hour sprint co-hosted with AMD.…
Liquid AI Announces Multi‑Year Partnership with Shopify to Bring Sub‑20ms Foundation Models to Core Commerce Experiences | Liquid AI
In a multi‑million‑dollar agreement, Liquid AI teamed up with Shopify to license Liquid’s LFMs for search and a new co‑developed generative recommender system that has outperformed…
LFM2-ColBERT-350M: One Model to Embed Them All | Liquid AI
Today, we release LFM2-ColBERT-350M, a late interaction retriever with excellent multilingual performance. It allows you to store documents in one language (for example, a product description…
Agentic Robotics at the Edge: Liquid AI, AMD, and Robotec.ai Demonstrate LFM2-VL-3B in Embedded Autonomy | Liquid AI
Together, Liquid AI, AMD, and Robotec.ai have deployed compact foundation models for autonomous agentic robotics: showcasing a specialized 3-billion parameter Liquid vision-language model (LFM2-VL-3B), running efficiently…
How Liquid AI Uses ExecuTorch to Power Efficient, Flexible On-Device Intelligence | Liquid AI
When we needed to deploy our hybrid LFM models on-device, we faced a critical challenge: existing inference engines couldn't handle the unique combination of attention and…
LFM2-VL-3B: A New Efficient Vision-Language for the Edge | Liquid AI
We’re excited to release LFM2-VL-3B, the newest and most capable addition to our family of vision LFMs (450M and 1.6B). Built on the LFM2-2.6B backbone, this…
LFM2-8B-A1B: An Efficient On-device Mixture-of-Experts | Liquid AI
We are releasing LFM2-8B-A1B, our first on-device Mixture-of-Experts (MoE) with 8.3B total parameters and 1.5B active parameters per token. By activating only a sparse subset of…