Magentic-One, AutoGen, LangGraph, CrewAI, or OpenAI Swarm: Which Multi-AI Agent Framework is Best?

Pros and Cons of popular Multi-Agent Orchestration framework

Mehul Gupta
Data Science in your pocket

--

The Multi AI Agent topic in Generative AI is heating up and every major tech giant has released some framework around it.

But which Multi-AI Agent framework to choose?

They are just too many !!

And with OpenAI releasing Swarm and Microsoft’s Magentic-One, this space has become very cluttered. So to clear any doubts, I will try to explain the key-features, pros and cons of each of these frameworks and let you decide what suits you well. We will be talking about

AutoGen (Microsoft)

LangGraph (LangChain)

CrewAI

OpenAI Swarm (OpenAI)

Magentic-One (Microsoft)

Let's get started !!

1. Autogen

AutoGen is the most popular and the earliest framework in the space by Microsoft, more suitable for software development tasks

Features:

  • It majorly involves two agents, the User and the Assistant.
  • User-Agent & Assistant-Agent Interaction: In Autogen’s user-assistant agent model, the User Agent can provide prompts or requirements, while the Assistant Agent generates and executes the code.
  • The Assistant Agent handles not just code generation but also the execution, giving results back to the user or other agents in the setup.
  • Specializes in multi-agent orchestration for code tasks but can handle other tasks as well.
  • Human guidance can be provided in between the interactions.
  • Strong community support from Microsoft.

Limitations:

  • Not intuitive enough, and not suitable for non-programmers.
  • A complicated setup, especially with local LLMs; requires a proxy server.
  • If not a software development task, can be pretty mediocre

2. CrewAI

CrewAI is usually the go-to choice for folks to build a quick demo for any Multi AI Agent task given it's very intuitive and easy to set up.

Features:

  • Very intuitive, and primarily relies on prompt writing.
  • Creating new agents and adding to the ecosystem is very easy. You can create 100s of agents in minutes
  • Easy to use for non-technical users.
  • Works well with most LLM providers and local LLMs, thanks to LangChain integration.

Limitations:

  • Limited flexibility and customization.
  • Suitable for basic use cases and not ideal for complex programming tasks.
  • There are some bugs during interactions between agents.
  • Community support is limited

3. Langraph

My personal favourite, LangGraph can be used for any Multi-AI Agent tasks and provides a lot of flexibility.

Features:

  • Built on top of LangChain; based on the idea of Directed Cyclic Graph.
  • It's not just a multi-AI agent framework, but a lot more.
  • Very flexible and customizable, supporting nearly any multi-agent orchestration application.
  • It is an extension of LangChain, hence got great community support.
  • Works well with open-sourced LLMs and any API

Limitations:

  • Lacks thorough documentation.
  • Not user-friendly for non-programmers or beginner programmers.
  • Requires decent programming skills, particularly in understanding graphs and logic flows.

4. OpenAI Swarm

OpenAI recently released Swarm, and I must say, it’s the easiest Multi-AI agent framework out there if you wish to get started

Features

  • Suitable for newbies in Multi-AI Agent
  • The major focus is on simplifying “Agent creation” and context switching between agents (called Handoffs).
  • Creating a short demo is super easy

Limitations

  • Doesn’t support LLMs other than OpenAI API
  • Not good for production deployments
  • Not flexible enough.
  • Community support is poor. You can't even raise issues on Git Hub!

5. Magentic-One

The latest addition to this list is Magentic-One by Microsoft (their 2nd framework) which also, is an attempt to simplify their existing AutoGen framework

Features

  • Similar to Swarm, this is suitable for non-programmers and easy to run
  • Comes with a default pack of 5 agents, one manager agent and other 4 being: WebSurfer navigates and interacts with webpages through a browser, FileSurfer manages and navigates local files, Coder focuses on writing and analyzing code, and ComputerTerminal provides console access for running programs and installing libraries.
  • Built on top of AutoGen, and is more of a generalist framework.
  • Includes AutoGenBench, a tool specific for analysing agent performance.

Limitations

  • Support for open-source LLMs is complicated
  • Not flexible enough; appears more like an application rather than a framework to me
  • Documentation and community support is nil as of now

So, what’s the best Multi-AI Agent framework?

According to my views (I have used all these packages),

  • For Software Development: AutoGen (Microsoft) — Best suited for tasks involving code generation and complex multi-agent coding workflows.
  • Best for Newbies: OpenAI Swarm & CrewAI — User-friendly, making it ideal for those new to multi-agent AI without complex setup requirements.
  • Best for Complex Tasks: LangGraph — Offers high flexibility and is built for advanced users, allowing custom logic and orchestration.
  • Open-Source LLMs: LangGraph — Integrates well with open-source LLMs and supports various APIs, unlike some other frameworks. Even CrewAI is fine.
  • Best community support: AutoGen has decent community support helping you with out-of-the-way issues
  • Ready from Word Go: CrewAI — Quick to set up and intuitive, suitable for demos or tasks that require rapid agent creation. Even Swarm and Magentic-One are pretty good but don't have enough community support
  • Cost-Effective: Magentic-One — Comes with a pre-packaged setup and a generalist approach, potentially saving on initial costs. Even Swarm and CrewAI can be considered.

I hope this blog is helpful and you choose the right Multi AI Agent Orchestration framework

--

--

Responses (14)