LangGraphvsCrewAI

2 agents, 2 evaluations — 0 community and 2 editorial — compared across overall score, task fit, reliability, cost, ease of setup, and drift over time.

Current verdict: LangGraph currently leads CrewAI by 0.6 points on Ruling's 10-point scale; confirm the top-review context before shortlisting.

ruling.so/compare/langgraph-vs-crewai

Scorecard

Winners are highlighted only when comparable review-derived scores exist.

2 evaluations considered

Overall

Weighted aggregate verdict across the review.

9.0/10

4.5/5 source average.

8.4/10

4.2/5 source average.

review avg
Task fit

How well the agent matches the job users hired it for.

9.4/10

4.7/5 source average.

8.6/10

4.3/5 source average.

review avg
Reliability

Consistency, uptime, and repeatability under real workflows.

8.6/10

4.3/5 source average.

7.8/10

3.9/5 source average.

review avg
Ease of setup

How quickly teams can get from signup to useful output.

7.2/10

3.6/5 source average.

8.0/10

4.0/5 source average.

review avg
Cost efficiency

Whether the results justify the seat, usage, or platform cost.

8.0/10

4.0/5 source average.

8.6/10

4.3/5 source average.

review avg
Drift score

How well quality holds up over longer sessions and releases.

9.0/10

4.5/5 source average.

8.0/10

4.0/5 source average.

review avg

At a glance

A truthful, data-backed summary of where each agent stands today.

LangGraph

LangChain · Frameworks & Indie

Top score

LangGraph is LangChain's stateful agent and multi-agent framework that models agent workflows as directed graphs — enabling complex cycles, human-in-the-loop checkpoints, and persistent state across agent sessions. It has become the go-to framework for enterprise agent applications requiring production-grade reliability, observability, and complex workflow management. LangGraph Cloud offers managed hosting with built-in deployment, scaling, and monitoring.

Best signalThe strongest framework choice for stateful production agents

CrewAI

CrewAI · Frameworks & Indie

CrewAI is the fastest-growing multi-agent orchestration framework, enabling developers to build teams of specialized AI agents that collaborate to complete complex tasks through role-based coordination. Its intuitive Python API has made it the most popular framework for enterprise multi-agent applications, with over 25 million agent runs per month across its cloud platform. CrewAI's "Crews" model maps naturally to business workflows where different agents handle research, writing, coding, and review.

Best signalApproachable multi-agent orchestration for business workflows

Pricing and specs

Static facts from the Ruling catalog, not prototype estimates.

Pricing
Free
Freemium
Price details
Open-source framework (free); LangGraph Cloud has usage-based pricing
Open-source framework (free); CrewAI+ cloud platform with free and paid tiers
Model backbone
Any LangChain-compatible model (GPT-4o, Claude, Gemini, etc.)
GPT-4o, Claude, Gemini, Ollama (user-configurable)
Setup complexity
Complex
Moderate
Catalog facts
Verified Aug 21, 2026
Verified Aug 21, 2026
Evaluations
1
1

Pricing and model availability change quickly. Ruling shows the latest catalog value we have verified from official sources; confirm on the vendor site before purchasing.

Top review for each

Most helpful published review per agent, pulled from current Ruling data.

Browse all reviews
Top review↓ most helpful
RE
Ruling Editorial — Frameworks
Ruling editorial benchmark · 6-12 months

The strongest framework choice for stateful production agents

Ruling editorial benchmark: LangGraph is a serious option for builders who need state, retries, human-in-the-loop checkpoints, and more deterministic control than a simple agent loop. It has a steeper learning curve than lighter frameworks, but the graph model pays off when workflows become long-running or business-critical.

27 found helpfulRead →
RE
Ruling Editorial — Frameworks
Ruling editorial benchmark · 1-6 months

Approachable multi-agent orchestration for business workflows

Ruling editorial benchmark: CrewAI has one of the most approachable APIs for modeling role-based agent workflows. It works well for demos and internal process prototypes where the team can define roles, tasks, and expected outputs clearly. Production use still requires observability, evaluation, and careful tool boundaries.

18 found helpfulRead →

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