Agent Frameworks

CrewAI vs LangChain.

Both sit in Agent Frameworks, scored on the same six pillars from the same published methodology. Here is where they actually differ.

The short answer

LangChain scores higher — 85.4 against 79.1, a margin of 6.3 points. That is the overall answer, not the whole one: the pillar breakdown below is where the decision usually actually gets made.

LangChain leads on integrations & ecosystem, maturity & reliability and capability.

CrewAI

CrewAI, Inc.

79.1

Strong

Role-based multi-agent orchestration, from open source to enterprise.

From
Free / Enterprise platform custom pricing
Pricing
Open Source
Maturity
Emerging
Founded
2023
LangChain

LangChain, Inc.

85.4

Excellent

The most adopted framework for building LLM applications and agents.

From
Free / LangSmith from $39 per month
Pricing
Open Source
Maturity
Established
Founded
2022

Pillar by pillar

The same six pillars and fixed weights used for every tool on the site. A lead of fewer than 5 points is not called for either side — these are evidence-backed judgements, not measurements. Read the methodology.

Capability

LangChain by 6

CrewAI80
LangChain86

Value for Money

Level

CrewAI85
LangChain88

Security & Compliance

Level

CrewAI74
LangChain78

Integrations & Ecosystem

LangChain by 15

CrewAI80
LangChain95

Maturity & Reliability

LangChain by 10

CrewAI68
LangChain78

Momentum

Level

CrewAI83
LangChain84

Which one, and when

Pick CrewAI if

  • Multi-agent automation POCs
  • Business-process agent teams
  • Python-first teams

The catch

  • Less battle-tested at scale than LangGraph
  • Fast API evolution between versions
Full CrewAI profile →

Pick LangChain if

  • it has to fit the stack you already run — it leads Integrations & Ecosystem by 15 points.
  • it has to hold up in production from day one — it leads Maturity & Reliability by 10 points.
  • the hardest end of the work is what you are buying for — it leads Capability by 6 points.
  • Production agent systems
  • RAG pipelines
  • Teams needing provider flexibility

The catch

  • Abstraction layers can obscure what's happening under the hood
  • Historical API churn; major-version migrations required effort
Full LangChain profile →

What each is good at

CrewAI

  • Intuitive role/goal/task mental model for multi-agent design
  • Standalone and lightweight, no heavy framework dependency
  • Strong education funnel: large certified developer community

LangChain

  • Largest integration catalog in the ecosystem
  • LangGraph provides durable, controllable agent orchestration
  • LangSmith closes the loop with tracing, evals and monitoring

Other comparisons in Agent Frameworks

Comparing something else? Build your own side-by-side across any tools in the catalog.