SWE-agent vs Devin
Detailed side-by-side comparison to help you choose the right tool
SWE-agent
🔴DeveloperAI Development Assistants
Open-source autonomous coding agent from Princeton and Stanford researchers that resolves GitHub issues, detects cybersecurity vulnerabilities, and implements code changes using GPT-4o, Claude, or local LLMs — achieving state-of-the-art performance on SWE-bench benchmarks.
Was this helpful?
Starting Price
FreeDevin
🟡Low CodeAI Development Assistants
AI software engineer that codes, fixes bugs, and ships features autonomously. Builds full applications end-to-end with minimal supervision.
Was this helpful?
Starting Price
$500/moFeature Comparison
Scroll horizontally to compare details.
SWE-agent - Pros & Cons
Pros
- ✓Completely free and open-source with no usage restrictions
- ✓State-of-the-art performance on SWE-bench benchmarks
- ✓LLM-agnostic — works with OpenAI, Anthropic, or local models
- ✓Fully autonomous operation without human-in-the-loop requirements
- ✓Backed by peer-reviewed research from Princeton and Stanford
- ✓Simple YAML configuration for easy customization
- ✓Active development with regular feature updates
- ✓Mini-swe-agent offers ultra-lightweight deployment option
- ✓Multimodal support for processing visual bug reports
- ✓MCP integration extends capabilities with external tools
Cons
- ✗Requires developer expertise for installation and configuration
- ✗LLM API costs can accumulate on complex repositories
- ✗No hosted/managed service — must self-deploy and maintain
- ✗Performance varies significantly based on chosen LLM backend
- ✗Limited IDE integration compared to commercial tools like Cursor or Copilot
- ✗Docker dependency adds infrastructure complexity
Devin - Pros & Cons
Pros
- ✓Truly autonomous coding agent (plans and executes independently)
- ✓Full development environment with browser and shell access
- ✓Can handle complex multi-file changes and architectural decisions
- ✓Integrates seamlessly with GitHub and Slack workflows
- ✓Learns from codebase context and maintains coding standards
- ✓Fair ACU-based pricing model (no idle time charges)
- ✓Parallel execution enables team-wide automation
Cons
- ✗Expensive at $500/user/month minimum for serious usage
- ✗ACU-based pricing can escalate quickly on complex debugging tasks
- ✗Still requires human review for critical production code
- ✗No native MCP support limits ecosystem integration
- ✗Output quality varies significantly on novel architectural challenges
- ✗Learning curve for optimal task decomposition and ACU management
Not sure which to pick?
🎯 Take our quiz →🔒 Security & Compliance Comparison
Scroll horizontally to compare details.
Price Drop Alerts
Get notified when AI tools lower their prices
Get weekly AI agent tool insights
Comparisons, new tool launches, and expert recommendations delivered to your inbox.