What is function calling in AI?

Function calling lets AI models interact with external tools and APIs by outputting structured calls with correct parameters. For example, extracting a city name from 'What's the weather in Tokyo?' and calling a weather API with the right parameters. Top models score above 90% on schema adherence.

Which AI is best for building agents?

Models scoring highest on multi-step orchestration benchmarks, where one tool's output feeds another's input. The gap between models is largest on complex chains — most models handle single-function calls well, but only the top 3-5 reliably orchestrate multi-step workflows.

Can AI call APIs automatically?

Yes. When given a function schema (describing available tools and their parameters), top models can select the right function, extract parameters from natural language, and output valid structured calls. This is the foundation for AI agents, chatbots with tools, and automated workflows.

An AI agent is a model that can plan and execute multi-step tasks by calling tools, reading results, and deciding what to do next. Tool calling accuracy is the core capability that determines agent reliability. The leaderboard above measures exactly this capability.

Do all LLMs support function calling?

Most frontier models support function calling, but quality varies significantly. Models fine-tuned specifically for tool use outperform general-purpose models, especially on complex orchestration. Check the scores above — single-function accuracy and multi-step orchestration are different skills.

Best AI for Tool Calling in 2026

Rankings of the best AI models for tool and function calling. Compare models by tool use accuracy and API integration capabilities.

113 models41 benchmarks

LLM Stats ResearchUpdated July 23, 2026113 models reviewedMethodology

The short answer

The best AI for tool calling right now is Kimi K3 by Moonshot AI, followed by GPT-5.6 Sol — ranked by function-calling accuracy, schema adherence, and multi-tool orchestration benchmarks.

Best Overall: Kimi K3Highest combined arena + benchmark score
Best Value: Muse Spark 1.1Lowest input price among the top-ranked models
Best Open Weights: Llama 3.1 405B InstructTop model you can download and self-host
Longest Context: GPT-5.6 SolLargest context window among the top-ranked models

At a glance

Model	Best for	Top strength	Watch out	Cost · Context
Claude Opus 4.8 Anthropic	Frontier reasoning + nuanced long-form prose	Long-form coherence — voice and structure stay consistent over thousands of tokens	The highest output price of any frontier model — not the default for cost-sensitive workflows	$5.00 / $25.00 1.0M ctx
Gemini 3.5 Flash Google	Newest Google generation — strong frontier challenger	Massive native context window	Newer release; provider coverage still expanding	$1.50 / $9.00 1.0M ctx
GPT-5.5 OpenAI	OpenAI's frontier — strongest all-around model on most benchmarks	Frontier scores across reasoning, math, coding, and research	Premium pricing — match the variant (Pro / Instant) to the task	$5.00 / $30.00 1.1M ctx
Llama 3.1 405B Instruct Meta	Mature open-weight family with massive ecosystem	Best-supported open-weight family for tooling	Surpassed by Llama 3.3 and Llama 4 on quality	—

Claude Opus 4.8$5.00 / $25.00
Frontier reasoning + nuanced long-form prose
Strength
Long-form coherence — voice and structure stay consistent over thousands of tokens
Watch out
The highest output price of any frontier model — not the default for cost-sensitive workflows
Gemini 3.5 Flash$1.50 / $9.00
Newest Google generation — strong frontier challenger
Strength
Massive native context window
Watch out
Newer release; provider coverage still expanding
GPT-5.5$5.00 / $30.00
OpenAI's frontier — strongest all-around model on most benchmarks
Strength
Frontier scores across reasoning, math, coding, and research
Watch out
Premium pricing — match the variant (Pro / Instant) to the task
Llama 3.1 405B Instruct—
Mature open-weight family with massive ecosystem
Strength
Best-supported open-weight family for tooling
Watch out
Surpassed by Llama 3.3 and Llama 4 on quality

Capsule reviews of the top models

01
Anthropic
Claude Opus 4.8
Frontier reasoning + nuanced long-form prose
Strengths
- Long-form coherence — voice and structure stay consistent over thousands of tokens
- Strong instruction following on tone, length, and format
- Reliable on multi-step tasks where errors compound (agents, refactors, synthesis)
Watch-outs
- The highest output price of any frontier model — not the default for cost-sensitive workflows
- Slower than mini/flash siblings; prefer Sonnet for interactive UX
When to useWhen output quality matters more than cost or latency.
Input
$5.00/ M tokens
Output
$25.00/ M tokens
Context
1.0Mtokens
License
proprietary
See model page Compare side-by-side
02
Google
Gemini 3.5 Flash
Newest Google generation — strong frontier challenger
Strengths
- Massive native context window
- Strong multimodal — text, image, audio, and video in one call
Watch-outs
- Newer release; provider coverage still expanding
When to useCross-modal workflows; tasks where a 1M+ context actually helps.
Input
$1.50/ M tokens
Output
$9.00/ M tokens
Context
1.0Mtokens
License
proprietary
See model page Compare side-by-side
03
OpenAI
GPT-5.5
OpenAI's frontier — strongest all-around model on most benchmarks
Strengths
- Frontier scores across reasoning, math, coding, and research
- Long-context retrieval that holds up at 1M tokens
- Best-in-class tool-calling + function schema adherence
Watch-outs
- Premium pricing — match the variant (Pro / Instant) to the task
- Verbose by default; benefits from tight system prompts
When to useWhen you want the single highest-scoring model and budget isn't the constraint.
Input
$5.00/ M tokens
Output
$30.00/ M tokens
Context
1.1Mtokens
License
proprietary
See model page Compare side-by-side
04
Meta
Llama 3.1 405B Instruct
Mature open-weight family with massive ecosystem
Strengths
- Best-supported open-weight family for tooling
Watch-outs
- Surpassed by Llama 3.3 and Llama 4 on quality
When to useExisting fine-tunes; education and research.
See model page Compare side-by-side

As of July 2026, Kimi K3 leads tool calling benchmarks with a score of 39.2, followed by GPT-5.6 Sol (36.8) and GPT-5.6 Terra (34.5). Rankings test function selection accuracy, parameter extraction, and multi-step tool chain orchestration from natural language instructions.

Ranked by 41 benchmarks including Berkeley Function Calling Leaderboard (BFCL) and real-world API integration tests, evaluating schema adherence, parameter accuracy, and error recovery.

Function calling lets AI models interact with external tools and APIs by outputting structured calls with correct parameters. For example, extracting a city name from 'What's the weather in Tokyo?' and calling a weather API with the right parameters. Top models score above 90% on schema adherence.
Models scoring highest on multi-step orchestration benchmarks, where one tool's output feeds another's input. The gap between models is largest on complex chains — most models handle single-function calls well, but only the top 3-5 reliably orchestrate multi-step workflows.
Yes. When given a function schema (describing available tools and their parameters), top models can select the right function, extract parameters from natural language, and output valid structured calls. This is the foundation for AI agents, chatbots with tools, and automated workflows.
An AI agent is a model that can plan and execute multi-step tasks by calling tools, reading results, and deciding what to do next. Tool calling accuracy is the core capability that determines agent reliability. The leaderboard above measures exactly this capability.
Most frontier models support function calling, but quality varies significantly. Models fine-tuned specifically for tool use outperform general-purpose models, especially on complex orchestration. Check the scores above — single-function accuracy and multi-step orchestration are different skills.

Coding Computer Use Reasoning Developer Tools