AIBullisharXiv – CS AI · Mar 117/10
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Small Language Models for Efficient Agentic Tool Calling: Outperforming Large Models with Targeted Fine-tuning
Researchers demonstrated that a fine-tuned small language model (SLM) with 350M parameters can significantly outperform large language models like ChatGPT in tool-calling tasks, achieving a 77.55% pass rate versus ChatGPT's 26%. This breakthrough suggests organizations can reduce AI operational costs while maintaining or improving performance through targeted fine-tuning of smaller models.
🏢 Meta🏢 Hugging Face🧠 ChatGPT