AutoGen vs SuperAGI
Side-by-side comparison of two AI agent tools
Short answer
- SuperAGI has had no commit in 20 months; AutoGen is actively maintained.
- AutoGen is growing faster: +787 GitHub stars in the last 30 days vs +57 for SuperAGI.
- Pick AutoGen for: a programming framework for agentic AI. Pick SuperAGI for: < SuperAGI - A dev-first open source autonomous AI agent framework.
From GitHub data refreshed daily.
AutoGenfree
A programming framework for agentic AI
SuperAGIopen-source
<⚡️> SuperAGI - A dev-first open source autonomous AI agent framework. Enabling developers to build, manage & run useful autonomous agents quickly and reliably.
Metrics
| AutoGen | SuperAGI | |
|---|---|---|
| Stars | 61.3k | 17.7k |
| Star velocity /mo | 786.8253968253969 | 56.82539682539682 |
| Commits (90d) | 0 | 0 |
| Releases (6m) | 0 | 0 |
| Overall score | 0.3965748260904068 | 0.2507547304771036 |
Pros
- +支持多代理协作，可以创建复杂的 AI 交互系统
- +提供 AutoGen Studio 无代码界面，降低使用门槛
- +强大的模型集成能力，支持多种主流大语言模型和 MCP 服务器
- +完整的开源框架生态：提供从开发到部署的全链条工具，包括云服务、扩展市场和API接口
- +活跃的社区支持：拥有Discord社区、Reddit论坛和详细的文档，便于开发者学习和获得帮助
- +多样化的部署选项：既支持自主部署，也提供云端托管服务，适合不同规模的项目需求
Cons
- -需要 Python 3.10 或更高版本，对环境有一定要求
- -项目处于维护模式，新用户被建议使用 Microsoft Agent Framework
- -从 v0.2 升级需要遵循迁移指南，存在向后兼容性问题
- -框架复杂性：作为综合性框架，可能对初学者来说学习曲线较陡峭
- -开源项目依赖：框架的更新和维护依赖于社区贡献，可能存在版本兼容性问题
Use Cases
- •构建多代理对话系统，让不同角色的 AI 代理协作解决复杂问题
- •创建自动化工作流程，通过代理协作完成数据分析、内容生成等任务
- •开发具有网络浏览能力的智能助手，结合 MCP 服务器实现外部工具集成
- •企业自动化：构建智能客服代理、文档处理代理或业务流程自动化系统
- •开发者工具：创建代码审查代理、测试自动化代理或项目管理助手
- •个人助理应用：开发智能日程管理、信息聚合或任务执行代理
FAQ
- Which is more popular, AutoGen or SuperAGI?
- AutoGen has more GitHub stars (61,253 vs 17,702).
- Which is more actively developed, AutoGen or SuperAGI?
- AutoGen had more commits in the last 90 days (0 vs 0).
- Should I use AutoGen or SuperAGI?
- Compare their capabilities, limitations and "best for" notes above. Trying each on a small task is the fastest way to decide.