This article compares the coding capabilities of OpenAI’s GPT-5 and Anthropic’s Claude Sonnet by tasking them with building a multiplayer tic-tac-toe game. It explores how their different approaches to problem-solving, rule adherence, and cost-efficiency impact their performance in real-world development scenarios, questioning what truly defines a “better” AI coding assistant.
Key Findings and Arguments
The comparison revealed distinct strengths and weaknesses for each model. GPT-5 excels at advanced reasoning and deliberate, rule-abiding problem-solving, resulting in robust and functional code. However, it is slower and consumes more tokens. In contrast, Claude Sonnet is significantly faster and produces more visually polished results, but it often struggles with schema consistency and can deliver incomplete or less reliable solutions, especially in complex tasks like authentication.
Authentication and Cost Analysis
Both models required manual intervention for complex tasks like implementing authentication, particularly with environment variables and TypeScript compatibility. In terms of cost, GPT-5 is more token-intensive but has a lower per-token price, making it valuable for projects where accuracy is paramount. Claude Sonnet uses fewer tokens, which can be cost-effective for simpler tasks, but its higher per-token rate can offset these savings.
Conclusion: Choosing the Right Tool
The article concludes that neither AI model can fully replace human oversight. The choice between them depends on project priorities. GPT-5 is the superior option for tasks requiring deep reasoning, complexity, and accuracy. Claude Sonnet is better suited for projects that prioritize speed and a polished user interface. Ultimately, developers must weigh the trade-offs between deliberate accuracy and rapid, visually appealing output.
Mentoring question
When using AI for your own projects, do you prioritize the speed and visual polish offered by a model like Claude Sonnet, or the deliberate reasoning and functional accuracy of a model like GPT-5? How does this choice impact your workflow?
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