LFM2.5 is a new family of hybrid models designed for on-device deployment. It builds on the LFM2 architecture with extended pre-training and reinforcement learning.
- On-device personal assistant: Designed to power real-life applications, chaining tool calls, and following complex instructions on all devices.
- Compressed performance: Competitive with much larger dense and MoE models on instruction following and agentic tasks.
- Unmatched throughput: Fastest in its size class on both CPU and GPU inference