# Run fast, private agents on-device with LFM2.5-24B-A2B

Published: 2026-10-13 · Updated: 2026-10-13 · Category: Model Release

Source page: https://www.sipply.dev/story/run-fast-private-agents-on-device-with-lfm2-5-24b-a2b-c4081009 · 中文: https://www.sipply.dev/zh/story/run-fast-private-agents-on-device-with-lfm2-5-24b-a2b-c4081009

## Summary

Hugging Face has unveiled the LFM2.5-24B-A2B, a new reasoning model designed for on-device applications. This model boasts 24 billion parameters but operates efficiently by activating only 2 billion parameters per token, allowing it to deliver competitive performance against larger models. Notably, it excels in benchmarks focused on tool use and instruction-following tasks, making it a promising option for developers looking to implement AI capabilities directly on devices.

## Key takeaways

- LFM2.5-24B-A2B is designed for efficient on-device operation.
- The model utilizes only 2 billion active parameters per token.
- It demonstrates strong performance in tool use and instruction following.

## Why it matters

The introduction of LFM2.5-24B-A2B signifies a step forward in making powerful AI models accessible for on-device applications, enhancing privacy and responsiveness.

- **Product managers:** Product managers should consider the implications of on-device AI for user experience, as it can lead to faster response times and improved privacy for end-users.
- **Developers:** Developers can leverage this model to create applications that require less reliance on cloud computing, thus improving performance and reducing latency in AI-driven functionalities.
- **Students and job seekers:** For students and job-seekers, understanding and working with cutting-edge models like LFM2.5-24B-A2B can provide valuable skills in AI and machine learning, which are increasingly in demand in the job market.

## Sources

- [Run fast, private agents on-device with LFM2.5-24B-A2B](https://huggingface.co/blog/LiquidAI/lfm25-24b-a2b) (Hugging Face Blog, 2026-10-13)

## 中文

### 在设备上快速运行私有代理，使用LFM2.5-24B-A2B

Hugging Face推出了LFM2.5-24B-A2B，这是一种专为设备应用设计的新推理模型。该模型拥有240亿个参数，但每个token仅激活20亿个参数，从而实现高效运行，能够与更大模型的性能竞争。值得注意的是，它在工具使用和遵循指令的基准测试中表现出色，成为开发者在设备上直接实现AI功能的有前景的选择。

**要点：**

- LFM2.5-24B-A2B旨在高效地在设备上运行。
- 该模型每个token仅使用20亿个活跃参数。
- 它在工具使用和遵循指令方面表现强劲。

**为什么重要：** LFM2.5-24B-A2B的推出标志着在设备应用中使强大AI模型可用的一步，增强了隐私性和响应速度。

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