Independent AI agent reference

CrewAI vs LangGraph

A side-by-side comparison of capabilities, autonomy, integrations, and pricing to help you choose.

Short answer: choose CrewAI if you want open-source framework for orchestrating role-based, collaborating multi-agent teams (Supervised agent, freemium); choose LangGraph if you want low-level framework for stateful, durable, graph-based llm agents (Supervised agent, freemium).

CrewAILangGraph
What it isOpen-source framework for orchestrating role-based, collaborating multi-agent teamsLow-level framework for stateful, durable, graph-based LLM agents
Typeframeworkframework
AutonomySupervised agentSupervised agent
Pricingfreemium · Framework free (open source); paid tiers reported from ~$25/mofreemium · Framework free (MIT); LangGraph Platform via LangSmith (free Developer tier)
Best fordevelopers, enterprise, mid-marketdevelopers, enterprise, mid-market
Deploymentself-hosted, api, saasself-hosted, api, saas
Modalitiestext, code, apitext, code, api
Modelsmodel-agnostic, gpt, claudemodel-agnostic, gpt, claude, gemini, open-source
Protocolsfunction-calling, mcp, rest-apifunction-calling, mcp, rest-api
IntegrationsOpenAI, Anthropic, Slack, Serper, DatadogOpenAI, Anthropic, Google, AWS Bedrock, LangSmith
Capabilities4 documented4 documented

CrewAI

  • +Clean, lean abstraction (Crews + Flows) that many developers find simpler and faster than heavier frameworks
  • +Standalone (no LangChain dependency) with strong multi-agent collaboration primitives out of the box
  • +Provides a managed enterprise control plane (observability, RBAC, human-in-the-loop) for moving to production
  • -Multi-agent designs can compound error rates and cost; not always cheaper or more reliable than a single agent
  • -Newer and smaller ecosystem than LangChain, with fewer integrations and less battle-testing
Full CrewAI profile

LangGraph

  • +Explicit graph model makes complex agent control flow (loops, branching, multi-agent routing) inspectable and controllable
  • +Production-grade primitives: durable execution, checkpointing/time-travel, and first-class human-in-the-loop interrupts
  • +Open source and model-agnostic, with a hosted LangGraph Platform and LangSmith observability for deployment
  • -Lower-level and more verbose than higher-level agent libraries; a steeper learning curve
  • -Framework, not a product: autonomy and quality depend entirely on what the developer builds
Full LangGraph profile

Which should you choose?

CrewAI is open-source framework for orchestrating role-based, collaborating multi-agent teams, best for developers, enterprise, mid-market. LangGraph is low-level framework for stateful, durable, graph-based llm agents, best for developers, enterprise, mid-market. The right choice depends on the autonomy level you want, your existing integrations, and your budget, all compared above.

This comparison is generated from the sourced CrewAI and LangGraph profiles. Open either profile to review its evidence and last-reviewed date.