A Blog post by Liquid AI on Hugging Face
Liquid AI debuts LFM2.5-2.6B (2.6B parameters, 128K context, native tool calling), deployable on CPU/Raspberry Pi without GPU or cloud. Tech leaders gain electricity-only inference, on-device privacy for compliance, and edge deployment for agent automation—a cost-efficient tradeoff optimized for task-specific agentic workloads over cloud models.
One test found it performed 3.7 times faster than DeepSeek-V4-Flash, the model has skyrocketed to the top of OpenRouter since its release last week.
Liquid AI released LFM2.5-2.6B, a 2.69B-parameter agentic model with 128K context under open weights, running locally at 220 tok/s on M5 Max in under 2.5GB. Local inference eliminates per-token cloud costs and vendor lock-in—enabling on-device agents for automotive, robotics, healthcare, and regulated sectors without API dependencies.
Liquid AI released LFM2.5-2.6B, a 2.69B parameter on-device agentic model with 128K context, tool calling and open weights