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Best AI for coding

Coding is the most measurable LLM task — there's a right answer and the code either runs or it doesn't. As of 2026, the gap between top models has narrowed but the winner depends on language, length, and whether you need reasoning vs. completion.

Our pick
Claude Opus 4.7

Opus 4.7 leads SWE-Bench and writes the cleanest, most idiomatic code across languages. Best at multi-file reasoning.

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Runner-up
GPT-5.4

GPT-5.4 closes the gap on most tasks for a fraction of the cost. Use it as your default; reach for Opus on hard architecture problems.

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Sample prompt to try

Refactor this Python function to be more efficient and add type hints. Tell me what you changed and why. [paste your function here]

What to look for in any model

  • 1Always paste the surrounding code, not just the function — context matters more than model choice
  • 2Ask for tests in the same prompt; both models are noticeably better when forced to verify
  • 3Smaller, faster models (Haiku, GPT-5.4 mini) handle 80% of refactoring at 5% of the cost
  • 4For agentic tasks (multi-step, tool-using), Claude pulls further ahead

Recipes for this task

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Community-built prompt templates already tuned for coding. Fill in the variables and run.

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