OpenHands vs AutoGen vs CrewAI: Which Open-Source Agent Framework Fits Your Workflow?
A practical comparison of OpenHands (code-first autonomous agent), AutoGen (multi-agent conversations), and CrewAI (role-based team orchestration).
OpenHands, AutoGen, and CrewAI are three of the most popular open-source agent frameworks, but they solve different problems.
OpenHands (71K+ stars) is a code-first autonomous agent that works inside repositories. AutoGen (58K+ stars) from Microsoft Research is a multi-agent conversation framework. CrewAI (52K+ stars) organizes agents as role-based teams.
Quick recommendation
- Choose OpenHands when your primary goal is autonomous software development: fixing GitHub issues, writing code, running tests, and managing repositories.
- Choose AutoGen when you need multi-agent conversations, group chats, and flexible agent topologies for complex problem-solving workflows.
- Choose CrewAI when a role-and-task model with clear delegation maps naturally to your workflow, especially for content generation, research, and structured output pipelines.
Comparison table
| Framework | Best for | GitHub stars | Setup burden | Main risk | Open source |
|---|---|---|---|---|---|
| OpenHands | Code-first autonomous development | 71,464 | Medium | Can make uncontrolled repo changes | MIT |
| AutoGen | Multi-agent conversation orchestration | 58,400 | Medium to high | Complex agent topology management | CC-BY-4.0 |
| CrewAI | Role-based agent teams | 52,300 | Low to medium | Roles can become vague without strict task definitions | MIT |
When to pick each framework
OpenHands: best for autonomous software development
OpenHands is built for one core scenario: an AI agent that can work inside a code repository. It installs dependencies, reads files, writes code, runs tests, and opens pull requests. If your mental model is "give an agent a GitHub issue and let it figure out the fix," OpenHands is the most mature option.
Start with a small, well-scoped issue in a repo you control. Set clear boundaries on which files the agent can modify. Review every diff before merging.
AutoGen: best for multi-agent conversations
AutoGen from Microsoft Research is a framework where multiple agents talk to each other through structured conversations. It supports group chats, hierarchical agent topologies, handoffs, and tool integration. Use it when different agents should play different roles—a writer agent, a reviewer agent, a fact-checker agent—and coordinate through conversation.
AutoGen is not primarily a coding agent. It is an orchestration framework for any kind of multi-agent workflow where conversation is the coordination primitive.
CrewAI: best for role-based agent teams
CrewAI organizes agents as a "crew" with defined roles, tasks, and a sequential or hierarchical process. It is the most intuitive framework if you think in terms of team structure: a researcher agent, a writer agent, and an editor agent working together on a document.
CrewAI is especially popular for content generation, market research reports, and structured data extraction pipelines. It is less suited for open-ended software development or free-form multi-agent conversations.
How to choose
- If your task is software engineering (fix bugs, write code, manage PRs), start with OpenHands.
- If your task requires multiple agents with different roles talking to each other, start with AutoGen.
- If your task is a structured pipeline of roles and deliverables, start with CrewAI.
Pick the simplest framework that covers your primary use case. All three can be extended later.
First test to run
For OpenHands: give it a small GitHub issue with a clear expected outcome. For AutoGen: build a two-agent system where one agent asks questions and another provides answers. For CrewAI: define two roles and one task, then run the crew end to end.
OpenAgent next step
Browse the Agents directory for more open-source agent frameworks, or read our agent evaluation stack guide for testing strategies.