Building AI agents? These 227 models support function calling and are ranked by their agentic capability coverage - tool use, reasoning, JSON output, streaming, vision, and web search.
| # | Model | Score |
|---|---|---|
| 1 | MiMo-V2-ProXiaomi | 85 |
| 2 | Nemotron 3 Super (free)NVIDIA | 84 |
| 3 | MiniMax M2.5 (free)MiniMax | 83 |
| 4 | MiniMax M2.7MiniMax | 83 |
| 5 | Qwen Plus 0728 (thinking)Alibaba | 83 |
| 6 | MiMo-V2-FlashXiaomi | 83 |
| 7 | Trinity Miniarcee-ai | 82 |
| 8 | Nemotron Nano 12B 2 VL (free)NVIDIA | 82 |
| 9 | Tongyi DeepResearch 30B A3BAlibaba | 82 |
| 10 | Qwen3 Max ThinkingAlibaba | 82 |
| 11 | gpt-oss-safeguard-20bOpenAI | 82 |
| 12 | Mercury 2Inception | 81 |
| 13 | Qwen3 VL 32B InstructAlibaba | 81 |
| 14 | Qwen3 VL 8B InstructAlibaba | 81 |
| 15 | Qwen3 VL 30B A3B InstructAlibaba | 81 |
| 16 | Qwen3 30B A3B Thinking 2507Alibaba | 81 |
| 17 | R1 0528DeepSeek | 78 |
| 18 | DeepSeek V3.2 ExpDeepSeek | 77 |
| 19 | Llama 4 MaverickMeta | 77 |
| 20 | MiniMax M2.5MiniMax | 76 |
The foundation of agentic AI. Models must be able to decide when and how to call external tools - APIs, databases, file systems, web browsers. Without this, agents can only produce text, not take action.
Agents need to produce structured, parseable output reliably. JSON mode ensures the model always returns valid JSON, preventing the parsing errors that break automated workflows.
Chain-of-thought reasoning helps agents plan multi-step sequences, recover from errors, and make better decisions about which tools to use. Critical for complex autonomous workflows.
Streaming lets you observe agent actions in real-time - see which tools it's calling, watch it reason through problems, and intervene early if it goes off track. Essential for interactive agent interfaces.
Vision-capable agents can process screenshots, analyze charts, read documents, and interact with visual interfaces. Required for browser automation, document processing, and GUI agents.
Built-in web search lets agents find current information without custom search tool integrations. Ideal for research agents, fact-checkers, and competitive analysis workflows.
Agent-capable models need strong function calling (tool use), reasoning ability, long context windows, and reliable instruction following. They must decide when to use tools, handle multi-step plans, and recover from errors.
GPT-4o, Claude 3.5 Sonnet, and Gemini 2.0 are the top choices for AI agents. They offer reliable function calling, strong reasoning, and the ability to maintain context across long multi-step workflows.
Chatbots respond to individual messages. AI agents autonomously execute multi-step tasks - browsing the web, writing code, calling APIs, and making decisions. Agents use tool calling and planning capabilities that go beyond simple conversation.