goose vs Orca
Side-by-side comparison of two AI agent tools
Short answer
- Orca is growing faster: +19,335 GitHub stars in the last 30 days vs +3,367 for goose.
- Pick goose for: an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test. Pick Orca for: orca is the ADE for working with a fleet of parallel agents.
From GitHub data refreshed daily.
gooseopen-source
an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
O
Orcaopen-source
Orca is the ADE for working with a fleet of parallel agents. Run any coding agent with your own subscription. Available on desktop, mobile and remote runtime.
Metrics
| goose | Orca | |
|---|---|---|
| Stars | 54.9k | 83.6k |
| Star velocity /mo | 3.4k | 19.3k |
| Commits (90d) | 804 | 6.4k |
| Releases (6m) | 10 | 10 |
| Overall score | 0.8949337972867165 | 0.957769928427318 |
Pros
- +支持任何LLM模型且可多模型配置,灵活性极高
- +能够自主完成端到端开发任务,不仅仅是代码建议
- +开源架构支持自定义扩展和MCP服务器集成
Cons
- -需要本地安装和配置,对新手用户可能有一定门槛
- -作为自主代理执行任务时可能需要用户监督和验证结果
Use Cases
- •从零开始构建完整项目原型,包括代码编写和测试
- •对现有代码库进行重构和优化改进
- •管理复杂的工程流水线和自动化开发工作流
FAQ
- Which is more popular, goose or Orca?
- Orca has more GitHub stars (83,552 vs 54,872).
- Which is more actively developed, goose or Orca?
- Orca had more commits in the last 90 days (6,438 vs 804).
- Should I use goose or Orca?
- 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.