Comparing Claude and GPT-4o for Autonomous Agent Tasks

A 30-day comparison of the performance of Claude and GPT-4o on various autonomous agent workloads, including content production, code generation, and API integrations.

Details

The article presents the results of a 30-day comparison between the performance of Anthropic's Claude Sonnet 4.5 and OpenAI's GPT-4o on a range of autonomous agent tasks. The tasks included content production, code generation, API integrations, and competitive research. The evaluation focused on whether the output worked as expected, with code either running or not, and articles passing or failing quality review. The key findings include: 1) Claude outperformed GPT-4o on multi-step code generation tasks, with higher pass rates on writing Python scripts with tests and docs, refactoring with backward compatibility, and API integrations from scratch. 2) GPT-4o was more accurate at extracting structured data from unstructured text, such as HTML and competitor analysis tables. 3) Claude handled long input contexts better, maintaining instruction following at over 150,000 tokens, while GPT-4o showed noticeable degradation past 100,000 tokens. 4) The cost difference between the two models is more complex than expected, with Claude's prompt caching significantly reducing its effective cost compared to GPT-4o. 5) Claude showed more reliable tool use behavior, with lower rates of argument hallucination, better parallel tool call execution, and more effective error recovery.