Side-by-side comparison
AutoGen vs CrewAI
AutoGen
Build multi-agent AI workflows that can act and collaborate
AgenticnessAdaptive Collaborator 🤝
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 |
32-point evaluation
Agenticness
12/32
Adaptive Collaborator 🤝
AutoGen
8/32
Guided Assistant đź’¬
CrewAI
Dimension Breakdown (0-4 each)
Action Capability
AutoGen
3
CrewAI
2
Autonomy
AutoGen
2
CrewAI
1
Planning
AutoGen
2
CrewAI
1
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 framework; pricing details for hosted services or paid tiers are not publicly available in the provided content.
- **Pro:** Not publicly available.
- **Enterprise:** Not publicly available.
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 need developer-grade control to orchestrate multi-agent behavior in Python—especially agent-to-agent workflows, MCP-connected tool use, and Playwright-based browser workflows—and you’re comfortable self-hosting and coding your integration patterns. Pick CrewAI AMP when you want a production workflow platform with a visual editor and copilot, clear lifecycle management from prototype to deployment, and enterprise-friendly hybrid options like Kubernetes/VPC self-hosting, SSO, secret management, and PII detection/masking, with pricing tied to workflow executions.
Choose AutoGen if...
- +Choose AutoGen if you’re a developer team that wants to *build custom multi-agent systems in code*, with control over agent-to-agent interaction via a low-level Core API and higher-level AgentChat patterns for faster prototyping.
- +Choose AutoGen if your workflows need *agent tool use and external integrations*—for example connecting to *MCP servers* and using *Playwright-based browser workflows* for web/browsing tasks.
- +Choose AutoGen if you want flexibility to integrate with specific model/tool stacks (e.g., the quickstart examples include *OpenAI*), and you’re comfortable running a *self-hosted* Python 3.10+ setup rather than relying on a managed platform.
- +Choose AutoGen if you need *agentic orchestration that stays close to your application*, like extending existing apps with agent behavior and external tool connectivity.
Choose CrewAI if...
- +Choose CrewAI AMP if you want a *visual editor* and an AI copilot to build and iterate on agentic workflows quickly—especially when you’ll hand off workflows from builders to teams for operation.
- +Choose CrewAI AMP if you’re moving from prototype to production and want a *managed lifecycle platform* with *workflow execution limits by plan*, cloud hosting (SaaS), and a clear upgrade path from a free Basic tier (50 executions/month).
- +Choose CrewAI AMP if you’re an enterprise that needs *hybrid deployment and governance*: self-hosted via *Kubernetes and VPC*, plus *SSO*, *secret manager integration*, and *PII detection and masking* with enterprise support and uptime SLAs.
- +Choose CrewAI AMP if your team benefits from platform services like *integrated tools and triggers* and ongoing operational support rather than building the orchestration framework yourself.