Benchmark: GPT-4o Agents vs Claude Opus Agents vs Gemini Agents — Which Model Powers the Best Agents?
A comprehensive benchmark comparing autonomous agent performance across GPT-4o, Claude Opus 4, and Gemini 2.5 Pro reveals significant differences in tool use accuracy, multi-step reasoning, and cost efficiency across 500 real-world tasks.
A team of independent researchers has published the most comprehensive comparison of AI model performance in agent scenarios, testing GPT-4o, Claude Opus 4, and Gemini 2.5 Pro across 500 real-world tasks spanning coding, research, data analysis, and web interaction.
Overall Results:
| Metric | Claude Opus 4 | GPT-4o | Gemini 2.5 Pro |
|---|---|---|---|
| Task Completion Rate | 84% | 79% | 76% |
| Tool Use Accuracy | 91% | 85% | 82% |
| Multi-Step Reasoning | 88% | 83% | 81% |
| Cost per Task (avg) | $0.42 | $0.38 | $0.29 |
| Avg Time to Complete | 45s | 38s | 52s |
Key Findings:
1. Claude Opus 4 led in task completion and tool use accuracy, particularly excelling at complex coding tasks and careful instruction following. Its tendency to ask clarifying questions reduced errors but increased interaction time.
2. GPT-4o offered the best speed-to-quality ratio, completing tasks fastest while maintaining competitive accuracy. It excelled at creative tasks and broad knowledge queries.
3. Gemini 2.5 Pro was the most cost-efficient and handled long-context tasks best thanks to its 1M token window. It struggled more with precise tool use but excelled at research tasks requiring synthesis of many sources.
The benchmark is open-source and reproducible, with all prompts, evaluation criteria, and raw results published on GitHub.