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You Don’t Need GPT-5 for Agents: The 1.2B Model That Beats Giants
Artificial Intelligence   Latest   Machine Learning

You Don’t Need GPT-5 for Agents: The 1.2B Model That Beats Giants

Last Updated on February 17, 2026 by Editorial Team

Author(s): MohamedAbdelmenem

Originally published on Towards AI.

Forget GPT-5 for agent tasks. LFM 2.5 runs at 359 tokens/sec in 900MB. Here’s why it works and how to fine-tune it for your use case.

1400x overtraining. 900MB memory. 359 tokens/sec.

You Don’t Need GPT-5 for Agents: The 1.2B Model That Beats Giants

Three lines of code. Zero cloud round trips. Infinite agents. Start here. Made By Author.

The article discusses the performance of the Liquid LFM 2.5 AI model, emphasizing its efficiency in tasks that normally require significantly larger models. It highlights how this smaller model surpassed traditional scaling laws, achieving faster inference speeds and lower operational costs, thus reshaping expectations in AI economics. The author argues that speed and task efficiency are now more critical than raw size or training costs, signaling a transformative shift in how AI agents are developed and deployed in real-world applications.

Read the full blog for free on Medium.

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