OpenHands vs SWE-Agent
Agent-Assisted
An open-source AI agent that autonomously handles software development tasks including code generation, debugging, and testing through natural language commands.
Spec-Driven
An AI agent that autonomously solves software engineering tasks by interacting with code repositories and development tools.
Summary
- OpenHands scores 3.9/5 and SWE-Agent scores 4.0/5 on the Dark Factory Score, a difference of 0.1.
- The widest gap is Self-Correction: OpenHands 3.5, SWE-Agent 4.0.
- OpenHands scores higher on code quality.
- SWE-Agent scores higher on autonomy, self-correction and project complexity.
- They score the same on integration.
- Both are listed as open source.
- Both are listed under Full-Stack Agents, Code Generation and Debugging.
Dimension by dimension
| Dimension | Weight | OpenHands | SWE-Agent |
|---|---|---|---|
| Autonomy | 28% | 4.2 | 4.5 |
| Code Quality | 20% | 3.8 | 3.5 |
| Integration | 17% | 4.0 | 4.0 |
| Self-Correction | 15% | 3.5 | 4.0 |
| Project Complexity | 20% | 3.6 | 3.8 |
| Dark Factory Score | 3.9 | 4.0 |
Why OpenHands scores 3.9
OpenHands demonstrates strong autonomy capabilities as a full-stack agent that can handle multi-step software development tasks through natural language commands. Its ability to perform code generation, debugging, and testing autonomously across the development lifecycle shows sophisticated task execution capabilities. The tool appears well-integrated with development workflows, likely supporting Git operations and CI/CD processes given its full-stack positioning. However, the GitHub repository page doesn't provide detailed implementation examples or specific technical capabilities.
Scored by Claude AI — last evaluated February 27, 2026
Why SWE-Agent scores 4.0
SWE-Agent demonstrates exceptional autonomy by being designed specifically to interact with code repositories and development tools independently, executing multi-step software engineering tasks without constant human intervention. Its ability to navigate codebases, understand context, and make informed decisions about code changes positions it highly for autonomous operation. The tool shows strong integration capabilities with its focus on working directly with repositories and development environments, though the specific CI/CD and deployment features would need verification. Self-correction appears robust given its agent-based architecture that can analyze results and iterate on solutions.
Scored by Claude AI — last evaluated February 27, 2026
More comparisons
Generated from Dark Factory Score data. How the score works. Comparing three or more tools at once is part of Pro.