local model

Liquid AI

2026-10-14 08:00:18

Liquid AI updates 24B local model, posts higher Agent scores than larger Qwen model

Liquid AI has introduced LFM2.5-24B-A2B, a new local model aimed at improving on-device Agent reasoning and tool use. The model keeps the same 24 billion total parameters as its predecessor while activating only about 2 billion parameters per run. Compared with LFM2-24B-A2B, the new release expands pretraining data from 17 trillion to 33 trillion tokens and increases context length from 32K to 131K. Liquid AI said the model is trained to reason before answering and was reinforced directly inside Agent frameworks including OpenClaw, Hermes Agent, Pi, and OpenCode to practice multi-step tool calling and result handling. In the company’s demo, Hermes Agent ran on a MacBook without using a cloud model API, searched trending Hugging Face projects, compiled a briefing, and continued after follow-up prompts. Liquid AI’s tests said the model generated 184 tokens per second on Apple’s M5 Max, with peak speed reaching 1.7x that of comparable MoE models. On Agent benchmarks, it scored 48.09 on LiveClaw versus 38.19 for Qwen3.6-35B-A3B, and 27.69 on AutomationBench, more than three times Qwen’s result. On SWE-bench Verified, however, it scored 51%, below Qwen’s 66.2%.

1030

Nous Research

2026-09-05 19:17:44

Nous Research Adds One-Click Local Model Setup for Hermes Desktop

Nous Research has introduced a one-click local model setup feature for its open-source agent Hermes Desktop. The tool automatically reads hardware configurations, selects compatible models, downloads weights, and configures the inference runtime, streamlining local AI model deployment. It is free under the MIT license, supports macOS, Windows, and Linux, and requires no account.

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