AutoGen vs CrewAI
| Feature | AutoGen | CrewAI |
|---|---|---|
| Category | LLMs & AI Infra | LLMs & AI Infra |
| Sub-category | AI Agent Framework | AI Agent Framework |
| Maturity | stable | stable |
| Complexity | intermediate | intermediate |
| Performance tier | medium | medium |
| License | MIT | MIT |
| License type | permissive | permissive |
| Pricing | fully free | fully free |
| GitHub stars | 38.0K | 25.0K |
| Contributors | 400 | 200 |
| Commit frequency | daily | daily |
| Plugin ecosystem | none | none |
| Docs quality | good | good |
| Backing org | Microsoft | CrewAI Inc |
| Funding model | corporate | vc_backed |
| Min RAM | 512 MB | 512 MB |
| Min CPU cores | 1 | 1 |
| Scaling pattern | single_node | single_node |
| Self-hostable | Yes | Yes |
| K8s native | No | No |
| Offline capable | No | No |
| Vendor lock-in | none | none |
| Languages | Python | Python |
| API type | SDK | SDK |
| Protocols | HTTP | HTTP |
| Deployment | pip | pip |
| SDK languages | python | python |
| Team size fit | solo, small, medium | solo, small, medium |
| First release | 2023 | 2023 |
| Latest version | — | — |
When to use AutoGen
- ✓ Multi-agent coding assistants that debug each other
- ✓ Group chat between specialized AI agents
- ✓ Human-in-the-loop approval for agent actions
- ✓ Automated research with web browsing agents
When to use CrewAI
- ✓ Orchestrate research teams of AI agents
- ✓ Automated content creation pipelines
- ✓ Multi-step analysis with specialized agents
- ✓ Customer support escalation workflows
AutoGen anti-patterns
- ✕ Can generate very long conversations (token-heavy)
- ✕ Debugging agent interactions is complex
- ✕ Less opinionated than CrewAI — more setup needed
CrewAI anti-patterns
- ✕ High token consumption with verbose agent reasoning
- ✕ Can get stuck in thinking loops
- ✕ Overkill for single-agent tasks
- ✕ Debugging multi-agent flows is complex