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,
LFMs are built to be customized. We think specialized intelligence is what enables more than half of enterprise AI usecases with predicable economics.
This is an incredible work by the @huggingface team on tuning our LFM2.5-24B-A2B for more efficient agentic behavior in
LFM2.5-24B adapters for Pi and Claude Code!
We release LoRA adapters trained on top of LFM2.5-24B - more efficient agentic development on opensource harnesses (up to 40% less tool calls on Pi!)!
huggingface.co/collections/ha…
d1 just got an upgrade! Meet 𝚍𝟷.𝟷.
It brings significantly better decision quality than d1, getting closer to d1-ultra while running faster and costing less than half as much.
> built for fast, structured decision-making
> $0.02 / 1M input tokens
> lower latency than
Today, we announce 𝙻𝚒𝚚𝚞𝚒𝚍 𝚁𝙸𝙿𝙻 (real-time inference pipeline), our ultra low-latency inference engine built to put LFMs directly in the request path of real-time workloads like search, ads, fraud, recommendations, and payments.
> complete generated responses end-to-end
Are decision based models more pro-China?
We asked Jev and Mercury Decide questions about China: “Is Taiwan a part of China?”, “Does China commit crimes against humanity?” and their outputs leaned more pro-china compared to most frontier models.
Their responses resemble those
