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Local LLMs Qwen3-14B and Llama-3.2-3B tested on function calling

A recent benchmark tested two local large language models, Qwen3-14B and Llama-3.2-3B, on their ability to perform function calls for real-world API tasks. While both models demonstrated strong JSON validity, with the smaller Llama-3.2-3B model showing a slight edge, the larger Qwen3-14B model proved superior in argument correctness, especially in multi-turn conversations and error recovery scenarios. Despite falling short of GPT-4's reliability, the Qwen3-14B model's performance suggests it is better suited for complex local coding agents that require accurate data extraction and context maintenance. AI

IMPACT Local LLMs are improving in function calling, with larger models showing better accuracy in complex scenarios.

RANK_REASON Comparison of two specific LLMs on a technical capability (function calling). [lever_c_demoted from research: ic=1 ai=1.0]

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Local LLMs Qwen3-14B and Llama-3.2-3B tested on function calling

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45 / 100
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Comparison of two specific LLMs on a technical capability (function calling). [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Pitambar Mahato ·

    Can Local LLMs Actually Call Functions? I Tested 2 Models on 6 Real API Tasks

    <p>I tested two local LLMs — Qwen3-14B and Llama-3.2-3B — on six real function-calling tasks: weather API, calendar booking, database query, file operations, multi-step workflows, and error recovery. Same prompts, same schema, same hardware (M2 24GB), same agent loop. The smaller…