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Head to head

CrewAI vs LangChain

Both are free, open-source Python frameworks for building AI agents, but they bet on opposite structures (CrewAI's role-based crew model versus LangChain/LangGraph's explicit state-machine control), and they diverge again above the free tier, where LangChain publishes a complete self-serve price ladder and CrewAI publishes no number at all between free and custom.

CrewAI and LangChain are both free, MIT-licensed Python frameworks for building AI agents, and the tiebreaker between them is not their code: it is that LangChain publishes a price for everything above its free tier and CrewAI publishes none. CrewAI organises agents into a “crew”: each one gets a role, a goal and tools, and the framework handles the hand-offs, plus an event-driven Flows layer when you need more deterministic control. LangChain provides lower-level building blocks (model, tool and retrieval abstractions) and, through LangGraph, an explicit graph of nodes and edges. You decide exactly what state each step sees and where it goes next.

Checked live on 2026-08-17: LangChain's root repository has 144,375 stars and 24,034 forks, reflecting its head start (created October 2022) and use well beyond agents. CrewAI (created October 2023) has 57,200 stars and 8,165 forks. The fairer one-to-one comparison is CrewAI against LangGraph specifically (LangChain's own agent-orchestration engine, at 39,850 stars), and on that comparison CrewAI leads by about 17,000 stars, meaning its crew abstraction has out-starred the part of LangChain built to do the same job.

Pricing is free-versus-free at the framework level, and the paid layers above them are where this decision is actually made. Read live on 2026-08-17, LangSmith publishes a complete self-serve ladder: Developer at $0/seat for one seat and 5,000 base traces a month, Plus at $39/seat/month for 10,000 base traces with unlimited seats and one free serverless deployment, and Enterprise at custom pricing, with the metered rates underneath printed on the same page, $1.50 per LangChain Compute Unit and $1.00 per LangChain Storage Unit. CrewAI's public pricing page, read the same day, shows exactly two plans: Basic, free, capped at 50 workflow executions a month, and Enterprise at custom pricing. There is no published number anywhere between them.

Third-party guides still circulate an old gated CrewAI price ladder, but none of those tiers appears on CrewAI's current public pricing page. The only terms a buyer can verify before signing in are the free Basic allowance and custom Enterprise pricing. This comparison therefore excludes the old figures instead of presenting an unverified historical ladder as a current option.

The two paid layers have also converged in shape, which narrows an axis this comparison used to turn on. LangSmith is no longer only tracing and evals: its own pricing page now meters agent deployment, sandboxes, an LLM gateway and a company-wide Fleet product in the same units as the traces. CrewAI AMP bundled a managed runtime, real-time execution tracing and a no-code Crew Studio from the start. Both vendors now sell the runtime as well as the framework; what still separates them is that one of them tells you what the runtime costs.

One difference is not a preference at all. LangChain ships an official JavaScript/TypeScript SDK (langchain-ai/langchainjs, 18,112 stars, last pushed 2026-08-14) and CrewAI ships no JavaScript or TypeScript framework: its GitHub organisation, read on 2026-08-17, carries the Python framework, a Python tools package, examples and deployment templates, and no JS/TS SDK among them. A team standardised on Node.js is not really choosing between these two.

How CrewAI and LangChain compare

Scroll across to compare every side. Feature names stay in view.

FeatureCrewAIVisit CrewAI ↗LangChain★ Our pickVisit LangChain ↗
DescriptionOpen-source multi-agent framework with a governed enterprise runtime for building and operating agent workflows.Open source agent frameworks plus LangSmith, the platform for tracing, evaluating and deploying agents.
Pricingfreefree, then $39/seat/month
TagsAPIAutonomousClaudeEnterpriseFree tierGPTMulti-agentNo-codeOpen modelsOpen sourceSelf-hostedAPIAutonomousClaudeFree tierGPTMulti-agentOpen modelsOpen sourceSelf-hosted
Pricing modelfreemiumfreemium
Model / LLMNative SDKs for OpenAI, Anthropic, Google Gemini, Azure, AWS Bedrock and Snowflake Cortex. LiteLLM for Hugging Face, Mistral, Groq, Perplexity, Cerebras, SambaNova, Ollama and others.Model-agnostic (any LLM)
Bring your own modelYes-
InterfaceLibraryLibrary
DeploymentBothSelf-host
Writes codePartlyYes
Debugs and fixesPartlyPartly (Plus, available higher)
Ships itPartlyPartly (Plus, available higher)
Done-for-you servicePartly (Enterprise, costs extra)Partly (Enterprise, available higher)
In your editorPartlyPartly (LangSmith Studio, other product line)
In your pipelinePartlyYes
Open sourcePartly (CrewAI Open Source, other product line)Yes
API accessPartly (currently degraded)Yes
Seat model-Yes
Pooled budgetPartlyYes
Audit logPartlyPartly (Enterprise, available higher)
Opt out of trainingNoYes
Data residencyPartly (Enterprise, available higher)Yes
Getting outPartlyPartly (Enterprise, available higher)
CertificationsPartly (Enterprise, higher tier)Yes
Limitations
  • Free Basic is capped at 50 workflow executions a month and the only path beyond that is a custom Enterprise sales conversation. There is no published self-serve paid tier.
  • Building custom agents requires Python, scripting, environment variables and dependency management, despite the no-code visual editor
  • Agent collaboration is limited to two coordination modes, Sequential and Hierarchical, with no built-in graph-style state control for finer orchestration
  • Agents retain memory and context within a workflow but do not learn or improve from past executions
  • The abstractions have churned across versions; a learning curve and some API instability.
  • Powerful but heavier than minimal frameworks for simple agents.

Who each one is for

CrewAI

Developers who want to stand up a role-based, collaborating multi-agent system quickly in Python, with a stable MIT-licensed core and a hosted build and runtime for production.

From Free (month (50 workflow executions))

LangChain

Engineering teams building a bespoke, production-grade agent who want the largest integration ecosystem plus real stateful control.

From Free

Verdict: CrewAI or LangChain?

LangChain, for most teams that intend to run the thing in production. It is the only side of this pair whose cost you can read off a page before you commit ($0, then $39 per seat per month, then metered LCU/LSU), the only one with an official TypeScript SDK, and the one whose explicit state control is what a bespoke agent eventually needs. Pick CrewAI in three specific cases, and none of them is small: your problem genuinely is a crew of role-playing specialists, where CrewAI gets you a working multi-agent system in well under 50 lines and LangGraph makes you draw the graph first; you are staying self-hosted permanently, where CrewAI's unpriced commercial layer costs you nothing; or you want the managed runtime, execution tracing and a no-code Crew Studio as one product rather than assembled from LangSmith's parts. One case is a hard stop rather than a preference: if your stack is JavaScript or TypeScript, CrewAI is Python-only and the choice is already made. The two mistakes, stated plainly: choosing CrewAI while planning to scale past 50 workflow executions a month on a budget you have to forecast, and choosing LangChain for a five-agent workflow you could have had running this afternoon.

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Frequently asked questions

Is CrewAI built on top of LangChain?
No. Despite that being a common assumption from CrewAI's early days, CrewAI's own README FAQ states plainly: “CrewAI is a standalone Python framework with its own primitives for agents, tasks, crews, flows, tools, and orchestration.” It does not depend on LangChain; both are separately model-agnostic (CrewAI routes through LiteLLM, which reaches local and self-hosted models via Ollama as well as the hosted providers; LangChain uses its own provider integrations).
Which has more traction on GitHub?
LangChain's root repository leads by a wide margin: 144,375 stars and 24,034 forks as of 2026-08-17, reflecting its head start (created October 2022) and use beyond agents. CrewAI (created October 2023) has 57,200 stars and 8,165 forks. The fairer comparison is CrewAI against LangGraph, LangChain's own agent-orchestration engine, which has 39,850 stars: on that head-to-head CrewAI is roughly 17,000 stars ahead of the part of LangChain built to do its job.
Are CrewAI and LangChain actually free?
Both cores are MIT-licensed and free to self-host, and the paid layers are where they stop resembling each other. LangSmith publishes self-serve pricing: Developer $0/seat (1 seat, 5,000 base traces a month), Plus $39/seat/month (10,000 base traces, unlimited seats, one free serverless deployment), Enterprise custom, plus per-unit metering at $1.50 per LangChain Compute Unit and $1.00 per LangChain Storage Unit. CrewAI's public pricing page lists only Basic (free, 50 workflow executions a month) and Enterprise (custom), with nothing priced in between, all read live on 2026-08-17.
What does CrewAI cost once you outgrow the free tier?
CrewAI does not publish that number. Its pricing page moves from Basic, free for 50 workflow executions a month, to custom Enterprise pricing. Older third-party ladders are not present on the current vendor page, so they are not treated as current prices here.
Does either support JavaScript or TypeScript?
LangChain does, CrewAI does not. LangChain maintains an official JS/TS SDK at langchain-ai/langchainjs (18,112 stars, last pushed 2026-08-14). CrewAI's GitHub organisation, read on 2026-08-17, publishes the Python framework, a Python tools package, examples and templates, and no JavaScript or TypeScript framework among them. For a team standardised on Node.js this is a hard constraint, not a preference.
Which is the better starting point for a beginner?
CrewAI's role-based crew abstraction is the faster on-ramp: a working multi-agent system in well under 50 lines of code. LangChain/LangGraph has a steeper learning curve (its core abstractions changed across major versions, so older tutorials can mislead), but rewards that curve with finer-grained state control, the larger integration ecosystem, and a commercial layer you can price yourself once the prototype has to become a product.

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At a glance

Both are free, open-source Python frameworks for building AI agents, but they bet on opposite structures (CrewAI's role-based crew model versus LangChain/LangGraph's explicit state-machine control), and they diverge again above the free tier, where LangChain publishes a complete self-serve price ladder and CrewAI publishes no number at all between free and custom.