Tool Calling with Local LLMs: A Practical Evaluation
SMRTR summary
Docker tested 21 local and hosted language models for tool calling across 3,570 cases. Key findings: GPT-4 performed best (0.974 F1 score), Qwen 3 (14B) nearly matched it (0.971 F1), while Qwen 3 (8B) balanced speed and accuracy (0.933 F1). Quantization minimally impacted performance. Some models struggled with tool use. The research highlights trade-offs between accuracy and speed, with Qwen models leading local options, aiding developers in choosing models for AI agents and applications.
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