SWE-bench Verified (Agentic Coding)
SWE-bench Verified is a human-filtered subset of 500 software engineering problems drawn from real GitHub issues across 12 popular Python repositories. Given a codebase and an issue description, language models are tasked with generating patches that resolve the described problems. This benchmark evaluates AI's real-world agentic coding skills by requiring models to navigate complex codebases, understand software engineering problems, and coordinate changes across multiple functions, classes, and files to fix well-defined issues with clear descriptions.
Claude Sonnet 4.5 from Anthropic currently leads the SWE-bench Verified (Agentic Coding) leaderboard with a score of 0.772 across 2 evaluated AI models.
Claude Sonnet 4.5 leads with 77.2%, followed by 
Kimi K2 Instruct at 65.8%.
Progress Over Time
Interactive timeline showing model performance evolution on SWE-bench Verified (Agentic Coding)
SWE-bench Verified (Agentic Coding) Leaderboard
| Context | Cost | License | ||||
|---|---|---|---|---|---|---|
| 1 | Anthropic | — | 200K | $3.00 / $15.00 | ||
| 2 | Moonshot AI | 1.0T | — | — |
FAQ
Common questions about SWE-bench Verified (Agentic Coding).
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