AI models with tool calling: 166 that can call your functions

Tool calling
Services found: 166
#AI modelCapabilitiesAPI $/1M (in / out)Context windowPrice / moOutput $/1MOverviewVisit site
21

Gemini 3.8 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
22

Qwen3.8 Max (0902)

Qwen
Text & chatVisionVideo
$2 / $61M tokensAPI only6View
23

Qwen3.8 2.4T A95B

Qwen
Text & chatReasoningAdjustable thinking
$2 / $61.05M tokensAPI only6View
24

Gemini 3.7 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
25

Grok 4.5

xAI
Text & chatVisionReasoning
$2 / $6500K tokensAPI only6View
26

GPT-5.5

OpenAI
Text & chatVisionReasoning
$5 / $301.05M tokensAPI only30View
27

Claude Sonnet 5

Anthropic
Text & chatVisionReasoning
$2 / $101M tokensAPI only10View
28

GPT-5.6 Luna

OpenAI
Text & chatVisionReasoning
$0.2 / $1.21.05M tokensAPI only1.2View
29

DeepSeek V4 Pro 0813

DeepSeek
Text & chatReasoningAdjustable thinking
$1.0494 / $3.14821.05M tokensAPI only3.148View
30

DeepSeek V4 Flash 0731

DeepSeek
Text & chatVisionReasoning
$0.065 / $0.181.31M tokensAPI only0.18View
31

Gemini 3.6 Flash

Google
Text & chatVisionAudio
$0.75 / $3.751.05M tokensAPI only3.75View
32

Qwen3.8 27B

Qwen
Text & chatVisionVideo
$0.42 / $31M tokensAPI only3View
33

DeepSeek V4 Pro 0423

DeepSeek
Text & chatReasoningAdjustable thinking
$0.95526 / $1.910521.05M tokensAPI only1.911View
34

Claude Sonnet 4.6

Anthropic
Text & chatVisionReasoning
$3 / $151M tokensAPI only15View
35

Qwen3.7 Max

Qwen
Text & chatReasoningAdjustable thinking
$2.5 / $7.51M tokensAPI only7.5View
36

MiniMax M3

MiniMax
Text & chatVisionVideo
$0.3 / $1.21.05M tokensAPI only1.2View
37

GLM-5.1

Z.ai
Text & chatReasoningTool calling
$1.4 / $4.4200K tokensAPI only4.4View
38

MiMo-V2.5-Pro

Xiaomi
Text & chatReasoningTool calling
$0.435 / $0.871.05M tokensAPI only0.87View
39

Kimi K2.7 Code

Moonshot AI
Text & chatVisionCoding
$0.71 / $3.5262.1K tokensAPI only3.5View
40

Qwen3.7 Plus

Qwen
Text & chatVisionReasoning
$0.32 / $1.281M tokensAPI only1.28View

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Tool calling is what turns a chatbot into software. The model returns a structured call - function name plus typed arguments - and your code executes it, feeds back the result and lets the model continue. Every integration worth building rests on it.

All 166 models here support it, from Claude Fable 5.1 at $50 per million output tokens down to budget options at $0.25. What varies is reliability under pressure: how well the model picks the right tool from a long list, and how many calls it can chain before losing the thread. Frontier models are noticeably better at long chains.

Structured, not guessedThe model returns a typed call, so your code never parses prose to decide what to run.
Chains break at scaleReliability drops as the tool catalogue grows; frontier models hold longer chains together.
Pairs with JSON outputTool calling picks the action, structured output guarantees the shape of the final answer.

Models with this capability

How to choose

  • Keep tool descriptions short and unambiguous — most failures are description problems, not model problems.
  • Limit the catalogue per request; twenty tools is manageable, two hundred is not.
  • Handle partial failure explicitly: models recover better when the error message says what to do next.
  • Cache the tool definitions — they are the same on every call and caching cuts that input cost.

Common mistakes

One giant toolSplitting into several narrow tools raises accuracy far more than prompt tuning.
No timeout on chainsWithout an iteration cap an agentic loop can call tools until the budget is gone.

Who this suits

Integration teamsConnecting an assistant to internal APIs, CRMs and databases.
AutomationWorkflows where the model decides the next step rather than following a script.
Support productsLooking up orders, issuing refunds, checking availability inside the conversation.

Frequently asked questions

What is the difference from structured output?

Tool calling decides which function to run and with what arguments. Structured output constrains the shape of the final answer. Most production systems use both.

Do cheap models call tools reliably?

For a handful of well-described tools, yes. Accuracy drops as the catalogue grows and as chains get longer, which is where frontier models pull ahead.

Can the model run the tool itself?

Not by default — your code executes the call. For models that run code in a vendor sandbox, see code execution.

Can the model call several tools at once?

Most current models support parallel calls, which cuts latency on independent lookups.

What happens if the model invents a tool?

A well-formed implementation rejects unknown names and returns an error the model can act on.

Frequently searched

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