⚡ TL;DR — The Verdict

n8n (8.0/10) vs LangFlow (8.2/10) — extremely close. n8n stands out with visual workflow builder and 400+ integrations. LangFlow wins on visual drag-and-drop flow builder with LangFlow is cheaper to self-host. Your choice depends on whether you prioritize approach.

n8n vs LangFlow: Complete 2026 Comparison

Updated · Based on real deployment data · 10 min read

n8n

8.0
Best for: complex business automation with AI capabilities and 400+ service integrations

LangFlow

8.2
Best for: a visual way to build and iterate on LangChain-based LLM applications

Head-to-Head Comparison

Feature n8n LangFlow
Primary Use Case General-purpose workflow automation platform with 400+ integrations and AI nodes for connecting business tools Visual framework for building multi-agent and RAG applications with a Python-based drag-and-drop UI
GitHub Stars 42,000+ 35,000+
Integrations 400+ 100+
Language TypeScript Python
License Sustainable Use License (Fair-code) MIT
Min RAM 2GB 1GB
Docker Image Size ~850MB ~650MB
Self-Host Cost $15/mo $10/mo
Cloud Pricing $20/mo N/A (self-host only)
Ease of Use 7.5/10 8.5/10
AI Capabilities 7/10 8.5/10
Community Score 8.5/10 8/10
Contributors 400+ 200+

Pricing Breakdown: Self-Hosted vs Cloud

Both tools are free to self-host. The real cost is infrastructure. Here's what you'll actually pay:

n8n Self-Hosted

$15/mo
  • 2GB RAM recommended
  • ~850MB Docker image
  • Sustainable Use License (Fair-code)
  • Self-hostable via Docker
  • 400+ contributors

LangFlow Self-Hosted

$10/mo
  • 1GB RAM sufficient
  • ~650MB Docker image
  • MIT
  • Flow sharing marketplace
  • 200+ contributors

Or: Host Both on VM Nebula

Skip the DevOps entirely. Deploy n8n and LangFlow with one click, persistent storage included, auto-SSL, and subdomain routing — starting at $9.99/month.

When to Use Each (Real Scenarios)

Choose n8n when:

Teams needing complex business automation with AI capabilities and 400+ service integrations. Key features include visual workflow builder, 400+ native integrations, ai/llm nodes (openai, anthropic, gemini), making it the go-to choice for AI development workflows.

Choose LangFlow when:

Python developers wanting a visual way to build and iterate on LangChain-based LLM applications. It stands out with visual drag-and-drop flow builder, python-native components, multi-agent orchestration, making it ideal for LLM-powered applications.

Use both together when:

You need the strengths of both. n8n handles visual workflow builder while LangFlow provides visual drag-and-drop flow builder. Many production teams combine them via APIs for a complete AI stack.

Deploy n8n + LangFlow in 20 seconds

Persistent storage. Auto-SSL. Subdomain routing. No DevOps required.

Start Free on VM Nebula →

Frequently Asked Questions

Is n8n better than LangFlow in 2026?
n8n scores 8/10 overall while LangFlow scores 8.2/10. n8n excels at visual workflow builder, while LangFlow is stronger for visual drag-and-drop flow builder. The best choice depends on your specific use case.
How much does it cost to self-host n8n vs LangFlow?
Self-hosting n8n costs approximately $15/month (2GB RAM minimum). LangFlow costs about $10/month (1GB RAM minimum). Both can be hosted on VM Nebula starting at $9.99/month.
Can n8n replace LangFlow?
Not directly. n8n is a Workflow Automation tool, while LangFlow is for LLM Orchestration. They serve different purposes and are often used together in production.
Which is easier to set up: n8n or LangFlow?
LangFlow is easier to set up (ease-of-use score: 8.5/10). n8n requires more configuration (score: 7.5/10). Visual drag-and-drop flow builder makes the initial setup straightforward.
What is the cheapest way to run n8n and LangFlow?
The cheapest option is self-hosting on a single VM. LangFlow only needs 1GB RAM ($10/mo). For both together, a $9.99/month VM Nebula instance with Docker Compose handles both with persistent storage, auto-SSL, and automatic restarts included.

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