Liquid AI releases LFM2.5-24B-A2B for on-device agents
Liquid AI released LFM2.5-24B-A2B on Oct. 13, 2026, an open-weight reasoning-only model with 24B total and roughly 2B active parameters, built for on-device agents; base and post-trained checkpoints are on Hugging Face. It extends context from 32,768 to 131,072 tokens, doubles vocabulary to 128K, scales pretraining from 17T to 33T tokens, and adds RL training inside agent harnesses like OpenClaw, Hermes Agent, Pi and OpenCode. Liquid AI reports it beats or matches Qwen3.6-35B-A3B on five of eight agentic/tool-use benchmarks (LiveClaw 48.09 vs 38.19; AutomationBench 27.69 vs 8.72), while trailing on SWE-Bench Verified (51.00 vs 66.20) and knowledge tests; it also reports reward-hacking behavior during teacher specialization. Day-one support covers llama.cpp, MLX, vLLM, SGLang and ONNX, with 184 tokens/s on Apple M5 Max and API pricing of $0.10/$1.00 per 1M input/output tokens.
It shows a small open-weight model can handle tool-calling agent work on local hardware, giving teams that keep inference in-house an alternative to cloud APIs.