GPT, Claude, and DeepSeek compared on regex, refactoring, and SQL tasks

A comparison of three AI models—GPT-5 class, Claude, and DeepSeek—on three distinct tasks (regex, refactoring, and SQL queries) revealed varying strengths and weaknesses. GPT and Claude performed well on a regex task, with Claude offering a helpful caveat about performance. For code refactoring, Claude produced the cleanest output, while GPT made an unintended change to the logic. DeepSeek excelled at a complex SQL query task, providing the most elegant solution, whereas GPT initially struggled with date boundaries and Claude offered a more verbose approach. AI

IMPACT Highlights differing capabilities of leading LLMs across common coding and data tasks, informing developer tool choices.

RANK_REASON Comparison of multiple LLM models on specific tasks. [lever_c_demoted from research: ic=1 ai=1.0]

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• Claude
• DeepSeek
• generative pre-trained transformer
• GPT-5

• model release
• product

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