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Side-by-side comparison

AutoGen vs CrewAI

AutoGen

Build multi-agent AI workflows that can act and collaborate

AgenticnessAdaptive Collaborator
vs
CrewAI

Build and scale collaborative AI agent workflows

AgenticnessGuided Assistant

Side-by-side comparison based on our agenticness evaluation framework

At a glance

Quick Facts

FeatureAutoGenCrewAI
CategoryMulti-Agent Orchestration, Agent Frameworks & OrchestrationMulti-Agent Orchestration, Agent Frameworks & Orchestration
DeploymentSelf-hostedHybrid (cloud + self-hosted)
Autonomy LevelSemi-autonomousSemi-autonomous
Model SupportMulti-modelSingle model
Open SourceYesYes
MCP SupportYes--
Team SupportSmall teamEnterprise
Pricing ModelFree / open sourceFreemium
Interfaceapi, gui, cligui, 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

AutoGen is the better pick when you want to build custom multi-agent systems from the ground up in Python—especially when you need deep control over agent-to-agent orchestration, custom tool use via MCP, and integrations like Playwright-based browser workflows—while CrewAI AMP is the better pick when you want a visual, workflow-first platform to move from prototyping to production with managed or enterprise self-hosted deployment (Kubernetes/VPC), plus operational/security features like SSO, secret management, and PII masking.

Choose AutoGen if...

  • +Choose AutoGen if you want a developer-first, code-based multi-agent framework where you orchestrate agent-to-agent interaction using a low-level Core API plus the higher-level AgentChat patterns.
  • +Choose AutoGen if you need custom tool-using workflows that can connect to external systems via MCP (including browser automation workflows using Playwright-based MCP).
  • +Choose AutoGen if you want flexibility to integrate specific model providers (the quickstart/examples show OpenAI model usage) and prototype agent behavior in code or with AutoGen Studio’s no-code workflow prototyping.

Choose CrewAI if...

  • +Choose CrewAI AMP if your team wants a production-oriented platform for building, testing, deploying, and managing agentic workflows with a visual editor and an AI copilot to help create workflows.
  • +Choose CrewAI AMP if you need managed cloud operations (SaaS) now, but also require enterprise-grade self-hosting via Kubernetes/VPC along with controls like SSO, secret manager integration, and PII detection/masking.
  • +Choose CrewAI AMP if you prefer workflow executions and team-seat-based scaling limits (e.g., 50 executions/month on Basic) with clearer lifecycle management and enterprise support/SLAs instead of building the orchestration layer yourself.