Side-by-side comparison
AutoGen vs CrewAI
vs
Side-by-side comparison based on our agenticness evaluation framework
At a glance
Quick Facts
| Feature | AutoGen | CrewAI |
|---|---|---|
| Category | Multi-Agent Orchestration, Agent Frameworks & Orchestration | Multi-Agent Orchestration, Agent Frameworks & Orchestration |
| Deployment | Self-hosted | Hybrid (cloud + self-hosted) |
| Autonomy Level | Semi-autonomous | Semi-autonomous |
| Model Support | Multi-model | Single model |
| Open Source | Yes | Yes |
| MCP Support | Yes | -- |
| Team Support | Small team | Enterprise |
| Pricing Model | Free / open source | Freemium |
| Interface | api, gui, cli | gui, web, api |
36-point evaluation
Agenticness
14/36
Adaptive Collaborator
AutoGen
11/36
Guided Assistant
CrewAI
Dimension Breakdown (0-4 each)
Action Capability
AutoGen
3
CrewAI
2
Autonomy
AutoGen
2
CrewAI
1
Planning
AutoGen
2
CrewAI
2
Adaptation
AutoGen
1
CrewAI
0
State & Memory
AutoGen
1
CrewAI
0
Reliability
AutoGen
0
CrewAI
1
Interoperability
AutoGen
2
CrewAI
1
Safety
AutoGen
1
CrewAI
2
Scores from our agenticness evaluation framework. Higher is more autonomous.
Features & Use Cases
AutoGen
Features
- Builds multi-agent AI applications
- Provides a low-level Core API for message passing and event-driven agents
- Includes AgentChat for higher-level multi-agent patterns
- Supports extensions for model clients and tools
- Can connect to MCP servers for external tool use
- Works with OpenAI models in the quickstart examples
- Includes AutoGen Studio for no-code workflow prototyping
- Supports browser-based workflows through Playwright MCP
Use Cases
- Developing custom multi-agent assistants for internal workflows
- Prototyping agent workflows without writing code in AutoGen Studio
- Building tool-using assistants that can browse the web through MCP
- Orchestrating expert sub-agents for tasks like math, research, or domain-specific reasoning
- Extending existing applications with agent behavior and external integrations
CrewAI
Features
- Visual editor for building agentic workflows
- AI copilot for workflow creation
- Integrated tools and triggers
- Workflow execution limits by plan
- Cloud SaaS deployment
- Self-hosted deployment via Kubernetes and VPC for Enterprise
- SSO for Enterprise
- Secret manager integration for Enterprise
Use Cases
- Teams building production AI agent workflows with a visual interface
- Organizations that want to deploy agents in a managed cloud environment
- Enterprises that need self-hosted agent infrastructure on private cloud or on-prem systems
- Developers who want to prototype an agent workflow and later scale it for production
Pricing
AutoGen
- **Free / open source** — full functionality available at no cost.
CrewAI
- **Free (Basic):** Free tier with a visual editor, AI copilot, integrated tools and triggers, and 50 workflow executions per month.
- **Professional ($25/month):** Includes everything in Basic, plus 1 additional seat, 100 workflow executions per month, and support via the community forum.
- **Enterprise:** Custom pricing. Includes SaaS or self-hosted deployment via Kubernetes and VPC, SOC2, SSO, secret manager integration, PII detection and masking, dedicated support, uptime SLAs, Slack or Teams support channels, and forward-deployed engineers.
Analysis
Our Verdict
Pick AutoGen when you want a developer framework to orchestrate bespoke multi-agent behavior with a low-level Core runtime and higher-level AgentChat patterns, especially if you need MCP-connected tool use (including Playwright-based browser workflows) and expect to extend/implement custom orchestration in code. Pick CrewAI AMP when you want a production-oriented agent workflow platform centered on a visual editor/AI copilot, with built-in lifecycle management and enterprise controls—cloud SaaS or self-hosted via Kubernetes/VPC, plus SSO, secret manager integration, PII masking, and SLAs—so teams can scale agent workflows with guardrails and plan-based execution limits.
Choose AutoGen if...
- +Choose AutoGen if you’re a developer team that wants to *build custom multi-agent systems from the ground up* using its Core runtime (low-level message passing/event-driven agents) and then move to higher-level multi-agent patterns via the AgentChat API.
- +Choose AutoGen if you specifically need *tool-using agents connected through MCP* (including examples that integrate with MCP servers) and want browser workflows via its *Playwright-based MCP* approach.
- +Choose AutoGen if you want a coding-first workflow where you can prototype quickly but still stay fully in Python (Python 3.10+ with pip), and you prefer a framework you can extend with model-client/tool extension packages (e.g., OpenAI-model quickstart examples).
- +Choose AutoGen if you want *no-code-ish prototyping only as an add-on* (AutoGen Studio) while keeping the option to drop down into code orchestration when the workflow complexity grows; AutoGen Studio is explicitly part of the ecosystem.
Choose CrewAI if...
- +Choose CrewAI AMP if your priority is *productionization with a visual workflow builder*—its visual editor plus “AI copilot for workflow creation” is meant to take you from prototype to deployed agent workflows without hand-coding every orchestration detail.
- +Choose CrewAI AMP if you want a *managed or enterprise-grade deployment lifecycle*: it offers cloud SaaS, plus enterprise self-hosted deployment via *Kubernetes and VPC*, and includes operational features like SSO, secret manager integration, PII detection/masking, and uptime SLAs.
- +Choose CrewAI AMP if your team values *team-based governance and scaling controls* out of the box—workflow execution limits are plan-based (e.g., Basic includes 50 executions/month; Professional expands limits and adds a seat).
- +Choose CrewAI AMP if you anticipate staying within the platform’s workflow model long-term and benefit from enterprise support options (enterprise support, SLA, and dedicated support offerings) as workflows move into production.