# Multi-domain On-policy Distillation

Liquid AI released LFM2.5-24B-A2B, a reasoning agent model with 24B total parameters but only 2B active per token, built to run locally on device. It keeps the predecessor LFM2-24B-A2B architecture while growing context from 32K to 131K tokens and vocabulary from 65K to 128K, and it now emits an explicit chain of thought before answering. Across 16 benchmarks it competes with Qwen3.6-35B-A3B, which has roughly 50% more total and active parameters: 48.09 versus 38.19 on LiveClaw and 27.69 versus 8.72 on AutomationBench, while decoding 184 tokens/s on an M5 Max.

Liquid AI released LFM2.5-24B-A2B, a reasoning agent model with 24B total parameters but only 2B active per token, built to run locally on device. It keeps the predecessor LFM2-24B-A2B architecture while growing context from 32K to 131K tokens and vocabulary from 65K to 128K, and it now emits an explicit chain of thought before answering. Across 16 benchmarks it competes with Qwen3.6-35B-A3B, which has roughly 50% more total and active parameters: 48.09 versus 38.19 on LiveClaw and 27.69 versus 8.72 on AutomationBench, while decoding 184 tokens/s on an M5 Max.