Function guide

Best AI models for function calling

This page is built for teams that need models to call tools reliably, return machine-friendly payloads, and keep enough context for multi-step orchestration.

Live signalTool support for function and action calls
Live signalStructured output support for predictable payloads
Live signalEnough context for orchestration prompts and state
Live signalLive pricing for automation-heavy production use
Fast answer

Start with the live shortlist, then validate the route

Function calling is a core building block for agents, but this page is more narrowly focused on tool orchestration and reliable machine-to-machine output.

Data source and freshness

Catalog-backed, not a static price sheet

TVP refreshes this page from the live OpenRouter model catalog. This render used 685 public model records and was synchronized Oct 26, 2026, 7:31 AM UTC. Pricing, availability, and context values can change.

Verify the exact route before sending production traffic, then use the linked model and provider pages as the source for current values. Read the TVP data methodology.

Shortlist

Top live candidates right now

x-ai

SpaceXAI: Grok 4.20

Grok 4.20 is a reasoning model from SpaceXAI with industry-leading speed and agentic tool calling capabilities. It combines the lowest hallucination rate on the market with strict prompt adherance, delivering...

Context2,000,000
Input$1.25
Output$2.50

2,000,000 token context, tool support, and structured output make it suitable for orchestration-heavy workflows.

  • text
  • image
  • file
  • tools
  • structured
meta-llama

Meta: Llama 4 Scout

Llama 4 Scout 17B Instruct (16E) is a mixture-of-experts (MoE) language model developed by Meta, activating 17 billion parameters out of a total of 109B. It supports native multimodal input...

Context1,310,720
Input$0.1
Output$0.3

1,310,720 token context, tool support, and structured output make it suitable for orchestration-heavy workflows.

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  • image
  • tools
  • structured
openai

OpenAI: GPT-6 Luna (batch)

GPT-6 Luna is the fast, cost-efficient model in OpenAI's GPT-6 series, positioned below GPT-6 Sol. It is suited for high-volume and latency-sensitive workloads such as chat, classification, and lightweight agentic...

Context1,050,000
Input$0.05
Output$0.25

1,050,000 token context, tool support, and structured output make it suitable for orchestration-heavy workflows.

  • file
  • image
  • text
  • tools
  • structured
openai

OpenAI: GPT-6 Luna Pro (batch)

GPT-6 Luna Pro is the same underlying model as [GPT-6 Luna](TVP catalog), served with `reasoning.mode` set to `pro` for higher-quality responses on complex tasks. **Cost note:** pro mode spends far more...

Context1,050,000
Input$0.05
Output$0.25

1,050,000 token context, tool support, and structured output make it suitable for orchestration-heavy workflows.

  • file
  • image
  • text
  • tools
  • structured
xiaomi

Xiaomi: MiMo-V2.5

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

Context1,050,000
Input$0.119
Output$0.238

1,050,000 token context, tool support, and structured output make it suitable for orchestration-heavy workflows.

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  • audio
  • image
  • video
  • tools
  • structured
FAQ

What buyers usually ask

Is function calling the same as agents?

Function calling is a core building block for agents, but this page is more narrowly focused on tool orchestration and reliable machine-to-machine output.

Why compare structured output here?

Because orchestration breaks down when outputs are inconsistent. Models that support structured formats are easier to plug into production systems.

Next step

Use the guide, then validate the route in live TVP data.

TVP keeps the shortlist connected to the current catalog, provider coverage, and token pricing so buyers can move from research to routing without starting over.