AI · head to head
LangGraph vs n8n
The short version
- Each has a real cost: LangGraph steeper learning curve compared to high-level abstractions; n8n starter tier limited to 1 project and 5 concurrent executions
- They diverge on capability: LangGraph covers Human-in-the-loop controls, n8n covers Workflow automation.
Where they differ
Only the attributes on which LangGraph and n8n actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in LangGraph
- Human-in-the-loop controls
- Customizable workflows
- Memory management
- Token-by-token streaming
- Low-level control
- Multi-agent support
Only in n8n
- Workflow automation
- Visual editor
- Conditional execution
- Looping
- Error handling
- Scheduling
- Webhooks
- REST API
What people use each for
The jobs each tool is most often brought in to do.
LangGraph
- Building production AI agents with auditable workflowsnot n8n
- Designing multi-agent systems for complex tasksnot n8n
- Implementing human oversight in autonomous systemsnot n8n
- Creating reliable agentic applications at scalenot n8n
n8n
- Building AI agents and workflow automation for technical teamsnot LangGraph
- Visual workflow design with capability to write custom JavaScript or Python codenot LangGraph
- Enterprise deployments with self-hosted or cloud optionsnot LangGraph
- Integrating 500+ pre-built applications with custom API connectionsnot LangGraph
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
LangGraph
- Steeper learning curve compared to high-level abstractions
- Requires understanding of graph-based architecture
- Debugging complex workflows can be challenging
- Not optimized for simple, one-off use cases
n8n
- Starter tier limited to 1 project and 5 concurrent executions
- Starter and Pro tiers restricted to Cloud hosting only, not self-hosted
- Business tier requires 6 months minimum commitment at €667/month
- SSO/SAML/LDAP authentication requires Business or Enterprise tier
- Dedicated support with SLA available only on Enterprise plan
Pricing, plan by plan
LangGraph
Free- Open SourceFree
- MIT-licensed framework
- Self-hosted deployment
- Full API access
- LangGraph Platform$35/month
- Managed hosting
- Enterprise deployment
- Integrated tooling
n8n
Free- CommunityFree
- Free self-hosted version on GitHub
- Open source
- Starter$20/month
- 2,500 workflow executions
- 5 concurrent executions
- 2,300 AI credits/month
- Pro$50/month
- 10,000 workflow executions
- 20 concurrent executions
- 13,700 AI credits/month
- Business$667/month
- 40,000 workflow executions
- Self-hosted option
- 6 shared projects
Which should you pick?
Choose LangGraph if
- You need human-in-the-loop controls.
- You want to start without paying.
- You work on Python, JavaScript, Web.
- You also want customizable workflows.
Choose n8n if
- You need workflow automation.
- You want to start without paying.
- You work on Web, Docker, Self-hosted.
- You also want visual editor.
Questions people ask
- Is LangGraph or n8n better?
- Neither clearly leads. LangGraph starts at Free and n8n at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, LangGraph or n8n?
- LangGraph starts at Free and n8n at Free.
- Does LangGraph or n8n run on more platforms?
- LangGraph runs on Python, JavaScript, Web. n8n runs on Web, Docker, Self-hosted.
- Can I use LangGraph for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is LangGraph best used for?
- LangGraph is most often used for building production ai agents with auditable workflows, designing multi-agent systems for complex tasks, implementing human oversight in autonomous systems, creating reliable agentic applications at scale. Of those, building production ai agents with auditable workflows and designing multi-agent systems for complex tasks are not what n8n is typically brought in for.
- What can LangGraph do that n8n cannot?
- LangGraph covers Human-in-the-loop controls, Customizable workflows, Memory management, Token-by-token streaming. n8n covers Workflow automation, Visual editor, Conditional execution, Looping.
Answered from the vendors’ own pages
LangGraph: Is LangGraph free to use?
Yes. The core LangGraph framework is MIT-licensed and completely free. You only pay if you use the optional managed LangGraph Platform for hosting.
Sourcen8n: Is there a free version of n8n?
Yes, n8n Community Edition is free and open-source, available for self-hosting on GitHub with unlimited users and workflows.
SourceLangGraph: What programming languages does LangGraph support?
LangGraph provides first-class support for Python and JavaScript, enabling cross-platform agent development.
Sourcen8n: What is the difference between n8n plans?
Plans differ by monthly workflow executions (2,500 for Starter, 10,000 for Pro, 40,000 for Business), concurrent execution limits, AI credits, and shared project counts.
SourceLangGraph: Can I deploy LangGraph in production?
Yes. LangGraph can be self-hosted on your own infrastructure or deployed through LangGraph Platform with enterprise support and SLA guarantees.
Sourcen8n: Does n8n offer annual billing discounts?
Yes, n8n offers 17% off when billing annually instead of monthly, and provides a Startup Plan at 50% off Business pricing for companies under 20 employees.
SourceRelated pages
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- n8n vs Arize AI
- n8n vs ChatGPT
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- n8n vs Dagster
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- n8n vs Mage AI
- n8n vs Temporal
- n8n vs UiPath
- n8n vs Workato
- n8n vs Jitterbit
- n8n vs mParticle
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