Compare Agency Swarm with other multi-agent AI frameworks.
Criteria | Agency Swarm | AutoGen | CrewAI |
---|---|---|---|
Origins 🏁 | ✅ Originated from a real AI agency building AI agents for clients worldwide. | ✅ Originated as a research experiment. | ❌ Originated as a funding vehicle, rather than a real production framework. |
Design & Architecture 🏗️ | ✅ Super lightweight framework with minimal abstractions. Built on top of the OpenAI Assistants API. | ✅ Event-driven architecture with support for both ChatCompletions and Assistants API. | ❌ Lacks a clear architectural design. Built on top of LangChain with numerous unnecessary abstractions. |
Reliability 🔍 | ✅ Robust type checking and validation for all tools with Pydantic. | ❌ Type hints but no validation. | ❌ Some validation is possible when using BaseTool, although the interface is not convenient to use. |
Flexibility 🔄 | ✅ No predefined prompts. Uniform communication. | ❌ Contains predefined prompts. Limited, but customizable communication flows. | ❌ Numerous predefined prompts. Only two ways of communication. |
Scalability 📈 | ✅ Easily scalable. Adding another agent only requires placing it in the agency chart. | ❌ Although it’s simple to add an agent into teams, it’s almost impossible to define custom communication between them. | ❌ Although it’s easy to add agents into crews, it’s not possible to create custom communication between them. |
Deployability 🚀 | ✅ Easily deployable with special callback functions. Offers open-source templates and tutorials. | ✅ Deployment with AutoGen studio. | ❌ Deployment via enterprise platform. No open-source deployment guides. |
Open Source Model Support 🌐 | ⚠️ Limited support with Astra Assistants API. | ✅ Moderate open-source model support. | ✅ Full open-source model support. |