OmO vs SWE-agent
Side-by-side comparison of two AI agent tools
Short answer
- OmO is growing faster: +810 GitHub stars in the last 30 days vs +254 for SWE-agent.
- Pick OmO for: omO: Just type "mass ulw" keyword with your prompt. Pick SWE-agent for: sWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice.
From GitHub data refreshed daily.
O
OmOopen-source
OmO: Just type "mass ulw" keyword with your prompt. Now you are the master of graph engineering.
SWE-agentopen-source
SWE-agent takes a GitHub issue and tries to automatically fix it, using your LM of choice. It can also be employed for offensive cybersecurity or competitive coding challenges. [NeurIPS 2024]
Metrics
| OmO | SWE-agent | |
|---|---|---|
| Stars | 69.8k | 20.5k |
| Star velocity /mo | 810 | 254.3684210526316 |
| Commits (90d) | 9.7k | 6 |
| Releases (6m) | 10 | 0 |
| Downloads (30d, npm + PyPI) | 91.7K | — |
| Overall score | 0.8973547831718989 | 0.4088976488846652 |
Pros
- +在SWE-bench基准测试中达到开源项目的最先进性能水平
- +支持多种主流大语言模型（GPT-4o、Claude Sonnet 4等），配置灵活
- +专为研究设计，架构简单且文档完善，易于定制和扩展
Cons
- -开发重心已转移到mini-swe-agent项目，原项目维护可能受到影响
- -主要面向研究用途，生产环境的稳定性和可靠性可能不如商业解决方案
Use Cases
- •自动修复GitHub仓库中的代码问题和bug
- •网络安全领域的漏洞发现和渗透测试
- •竞赛编程和算法挑战的自动化解决
FAQ
- Which is more popular, OmO or SWE-agent?
- OmO has more GitHub stars (69,768 vs 20,475).
- Which is more actively developed, OmO or SWE-agent?
- OmO had more commits in the last 90 days (9,692 vs 6).
- Should I use OmO or SWE-agent?
- Compare their capabilities, limitations and "best for" notes above. Both are open source, so trying each on a small task is the fastest way to decide.