The definitive ranking of AI models for building autonomous agents, tool use, and multi-step task completion based on Terminal-Bench and Ī²-Bench. Rankings are based on Terminal-Bench Hard, Ī²-Bench Telecom, and IFBench benchmarks from independent evaluations.
Agentic AI represents the next frontier: models that can autonomously complete multi-step tasks, use tools, browse the web, execute code, and orchestrate complex workflows. As AI moves from chat interfaces to autonomous systems, selecting the right model for your agents is critical.
Reliable function calling, API integration, and external tool orchestration
Planning, executing, and adapting through complex workflows
Following instructions accurately to achieve specified goals
Quality Index
73
OpenAI
Quality Index
73
Quality Index
71
| Rank | Model | Quality | Terminal-Bench | Ī²-Bench | IFBench | License |
|---|---|---|---|---|---|---|
| 1 | GPT-5.2 (xhigh) OpenAI | 73 | 44% | 85% | 75% | Proprietary |
| 2 | Gemini 3 Pro Preview (high) | 73 | 39% | 87% | 70% | Proprietary |
| 3 | Gemini 3 Flash | 71 | 36% | 80% | 78% | Proprietary |
| 4 | GPT-5.1 (high) OpenAI | 70 | 43% | 82% | 73% | Proprietary |
| 5 | Claude Opus 4.5 (high) Anthropic | 70 | 44% | 90% | 58% | Proprietary |
| 6 | GLM-4.7 (Thinking) Z AI | 68 | 30% | 96% | 68% | Open |
| 7 | Kimi K2 Thinking Kimi | 67 | 29% | 93% | 68% | Open |
| 8 | GPT-5.1 Codex (high) OpenAI | 67 | 33% | 83% | 70% | Proprietary |
| 9 | MiMo-V2-Flash Xiaomi | 66 | 26% | 95% | 64% | Open |
| 10 | DeepSeek V3.2 DeepSeek | 66 | 33% | 91% | 61% | Open |
Complex workflows, multi-system integration, business process automation
Best: Claude Opus 4.5, GPT-5.2
Code generation, testing, deployment pipelines, DevOps automation
Best: GPT-5 Codex, GLM-4.7 Thinking
Browser automation, web scraping, form filling, research tasks
Best: Gemini 3 Pro, Claude Opus 4.5
SQL queries, data pipelines, report generation, analytics
Best: GPT-5.2, DeepSeek V3.2
Support tickets, CRM integration, automated responses
Best: Gemini 2.5 Flash, GPT-5 mini
Literature review, hypothesis testing, experiment design
Best: Claude Opus 4.5, o3
Our agentic model rankings are based on three key benchmarks that evaluate real-world agent capabilities:
Tests complex terminal operations, system administration, and multi-step command execution in realistic environments.
Evaluates tool use in enterprise scenarios with real API integrations, database queries, and multi-system orchestration.
Measures instruction following accuracy, function calling reliability, and parameter extraction precision.
Use our interactive comparison tool to explore pricing, latency, and benchmark scores for all 10 agentic models.
As of January 2026, GPT-5.2 (xhigh) leads our agentic benchmarks. For open source alternatives, GLM-4.7 Thinking achieves 90%+ on Terminal-Bench Hard, making it the best self-hostable option for autonomous agents.
GPT-5.2 (xhigh) and Gemini 3 Pro currently lead in function calling reliability, with 95%+ success rates on the IFBench benchmark. Claude Opus 4.5 excels at complex multi-tool orchestration and reasoning chains.
Absolutely. Open source models like GLM-4.7 Thinking and DeepSeek V3.2 now rival proprietary options for agentic tasks. GLM-4.7 scores 90.6% on tool use benchmarks and supports hybrid reasoning modes ideal for autonomous agents. The main advantage is cost savings and the ability to self-host for data privacy.
The key benchmarks for agentic AI are Terminal-Bench Hard (system-level task execution), Ī²-Bench (enterprise tool use), and IFBench (instruction following). These evaluate real-world agent capabilities better than traditional benchmarks like MMLU.