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KnowledgeMay 11, 2026·2 min de lectura

SWE-bench — Benchmark for Coding Agents

Evaluate coding agents on real GitHub issues with SWE-bench, including a harness to run and score patch predictions. Compare models and tool stacks.

Listo para agents

Instalación lista para agent

Este activo puede instalarse después de elegir el runtime, revisar el plan y ejecutar el comando correspondiente.

Native · 96/100Política: permitir
Superficie agent
Cualquier agent MCP/CLI
Tipo
Knowledge
Instalación
Single
Confianza
Confianza: Established
Entrada
Asset
Comando de instalación directa
npx -y tokrepo@latest install 7fd5858d-76a8-4679-80d1-ee1191ad2977 --target codex

Ejecutar después de confirmar el plan con dry-run.

Introducción

Evaluate coding agents on real GitHub issues with SWE-bench, including a harness to run and score patch predictions. Compare models and tool stacks.

  • Best for: Teams benchmarking AI coding agents with reproducible datasets and harness-driven scoring
  • Works with: Python, Docker-based evaluation runs, dataset inputs + predictions JSON, optional Modal execution
  • Setup time: 30 minutes

Quantitative Notes

  • Setup time ~30 minutes (install + Docker + first harness run)
  • GitHub stars + forks (verified): see Source & Thanks
  • Resource note from README: ~120GB free disk, 8 CPU cores recommended for full runs

Practical Notes

Use SWE-bench as your north-star eval: define a baseline agent (model + tools), run SWE-bench Lite for fast iteration, and only run larger suites when you’re confident. Record versions (model, agent code, tool prompts) so improvements are auditable and repeatable.

Safety note: Harden your evaluation environment: isolate Docker, pin dependencies, and avoid running untrusted code outside sandboxes.

FAQ

Q: Is it only a dataset? A: No. SWE-bench includes a dataset plus a harness to run and score predictions reproducibly.

Q: Can I use it for regression tests? A: Yes. Freeze a subset of tasks and run the harness periodically or on key changes.

Q: Why does it need so much disk? A: Evaluations often build/run many repos in Docker; logs and images add up quickly.


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Fuente y agradecimientos

GitHub: https://github.com/SWE-bench/SWE-bench Owner avatar: https://avatars.githubusercontent.com/u/139597579?v=4 License (SPDX): MIT GitHub stars (verified via api.github.com/repos/SWE-bench/SWE-bench): 4,900 GitHub forks (verified via api.github.com/repos/SWE-bench/SWE-bench): 856

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