Best LLM for Function Calling / Tool Use

Ranked on tool-selection accuracy, multi-tool consistency, and price. Tool-use quality compounds in agent loops.

Updated April 2026. Top 3 this month: DeepSeek: R1 0528, Qwen: Qwen3.5 Plus 2026-02-15, DeepSeek: DeepSeek V3.

How we rank

Function calling is the connective tissue of agent systems. A model that picks the wrong tool once in 20 calls is unacceptable for any non-trivial automation. We weight tool-selection accuracy and multi-tool benchmarks heavily, then price.

Pillars and weights: tool selection (45%) · multi-tool (30%) · price (25%). Our full methodology is published on the methodology page.

Top ranked models

RankModelProviderInput $/1MOutput $/1MContext
1DeepSeek: R1 0528DeepSeek$0.50$2.15163,840
2Qwen: Qwen3.5 Plus 2026-02-15Qwen$0.26$1.561,000,000
3DeepSeek: DeepSeek V3DeepSeek$0.32$0.89163,840
4Qwen: Qwen3.5 397B A17BQwen$0.39$2.34262,144
5Tencent: Hunyuan A13B InstructTencent$0.14$0.57131,072
6MiniMax: MiniMax M2.1MiniMax$0.29$0.95196,608
7Arcee AI: Trinity Large PreviewArcee AI$0.00$0.00131,000
8OpenAI: GPT-4o (2024-11-20)OpenAI$2.50$10.00128,000
9MiniMax: MiniMax-01MiniMax$0.20$1.101,000,192
10Anthropic: Claude Sonnet 4.5Anthropic$3.00$15.001,000,000

Tips for function calling / tool use

  • Keep the tool list short and well-named. Long tool lists degrade accuracy.
  • Use JSON schemas with required fields to reduce malformed calls.
  • Log tool failures and retry with a fallback model tier if needed.

Frequently asked questions

Which LLM is best at tool use?

As of April 2026, our weighted top 3 are DeepSeek: R1 0528, Qwen: Qwen3.5 Plus 2026-02-15, DeepSeek: DeepSeek V3.

How many tools is too many?

Accuracy drops noticeably past ~30 tools in a single call. Route to a smaller toolset per conversation turn when you can.

Are tool-use benchmarks trustworthy?

Directionally yes — run the top 2 on your actual tool catalog before committing.

Related tasks

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Data refreshed daily via our snapshot cron. See our public JSON API for programmatic access.