Liquid AI releases LFM2.5-2.6B, a small open-weight model for on-device AI agents
Liquid AI introduced LFM2.5-2.6B, a 2.6 billion-parameter open-weight language model optimized for agentic workloads on local hardware including phones, laptops, CPUs, and devices as small as a Raspberry Pi. The company says the model supports a 128,000-token context window, native tool calling, and deployment through common inference stacks, while using a revenue-gated commercial license for larger companies. Liquid AI also said MacPaw will use its models in a planned on-device AI stack for the Eney macOS assistant.
Why it matters: The release reflects growing demand for AI models that can run locally for privacy, latency, cost, and offline-use reasons rather than relying on cloud inference. If small models become more capable at tool use and workflow automation, they could expand enterprise adoption of on-device agents in regulated, embedded, and always-on computing environments.