The 2.6 billion parameter LFM 2.5 model optimizes local agent deployment on edge devices. It outperforms larger models on key benchmarks while maintaining a small memory footprint. Liquid AI designed this architecture for high-efficiency inference. Developers can now run complex agentic workflows on consumer hardware without relying on cloud APIs.