SWE-agent vs Devin

A detailed comparison to help you choose the right tool for your use case.

S

SWE-agent

AI Agent

Autonomous tool for software engineering tasks using language models.

D

Devin

AI Agent

Autonomous AI software engineer by Cognition Labs

Feature
SWE-agent
Devin
Focus
GitHub issue resolution, bug fixes
Full-stack development, deploy
Open Source
Yes
No
Environment
Custom computer interface
Own shell, editor, browser
Benchmark
State-of-the-art on SWE-bench
Proprietary
Pricing
Free (you pay for LLM)
$500/mo
Task Scope
Narrow — code fixes
Broad — plan, code, debug, deploy
Setup
High
Low
Best For
CI/automated fixes, research
Hands-off autonomous dev

SWE-agent

Strengths

  • State-of-the-art performance on SWE-bench
  • Highly configurable through YAML
  • Designed for research and easy to hack
  • Supports multiple language models
  • Active development and community support

Limitations

  • Current development focus on mini-SWE-agent may divert resources
  • May require technical expertise to configure and use effectively
  • Limited to specific tasks defined by the framework
  • Potentially complex for beginners in AI and software engineering

Devin

Strengths

  • Full autonomous development
  • Own sandboxed environment
  • Handles complex tasks

Limitations

  • Expensive
  • Closed source
  • Can be slow on large tasks

Verdict

SWE-agent is best for automated, benchmark-grade GitHub issue fixing with open-source control and your choice of LLM. Devin is best for full autonomous development with its own environment and broad task coverage—at a premium price. Choose SWE-agent for focused, reproducible fixes; Devin for end-to-end autonomous engineering.

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