Last verified: April 2026 Different Tools

Dify vs n8n 2026 — AI Workflow Builder Comparison

Bottom line: Dify (134k+ GitHub stars) is purpose-built for LLM apps and RAG pipelines; n8n (48k+ stars) automates 400+ business app integrations. They solve different problems — and used together they're more powerful than either alone.

Quick Verdict

Choose Dify if...

  • You're building AI chatbots or assistants
  • You need a RAG knowledge base
  • You want a ready-made chat UI
  • Non-technical users need to use it

Choose n8n if...

  • You need to automate business workflows
  • You integrate 400+ different apps
  • You want event-driven automation
  • Low RAM / minimal resources

Best of both worlds: Many teams use n8n for business automation and Dify for the AI layer. n8n can call Dify's API to trigger LLM workflows when AI processing is needed.

Side-by-Side Comparison

Feature Dify n8n
Primary Use LLM app builder, RAG pipelines Workflow automation, integrations
GitHub Stars 134k+ 48k+
License Apache 2.0 (with EE features) Sustainable Use License
Self-host Docker Compose (complex) Single Docker container (simple)
Min RAM 4 GB 2 GB
Free Tier Yes (5,000 credits) Yes (community edition)
Cloud Pricing $59/mo (Pro) $20/mo (Starter)
AI / LLM Focus Native (core feature) Via HTTP / AI nodes
RAG Support Built-in knowledge base Via external tools only
Chatbot UI Built-in, embeddable Not included
Visual Editor Workflow + prompt editor Node-based workflow canvas
Integrations 20+ LLM providers 400+ apps and services

Use Case Breakdown

When to use Dify

✓ Customer support chatbot
✓ Document Q&A / RAG app
✓ AI writing assistant
✓ Internal knowledge base bot
✓ Multi-step LLM pipeline
✓ API-powered AI product

When to use n8n

✓ CRM to Slack automation
✓ GitHub → Jira sync
✓ Scheduled data pipeline
✓ Multi-app workflow
✓ Webhook processing
✓ E-commerce order processing

Self-Hosting Comparison

Dify Self-Hosting

  • 8 Docker containers via Compose
  • Min 4 GB RAM (8 GB recommended)
  • ~15 min to get running
  • 50+ GB disk for storage/DB
  • Updates via docker compose pull

n8n Self-Hosting

  • Single Docker container
  • Min 2 GB RAM
  • ~5 min to get running
  • 10+ GB disk
  • Updates via docker pull

Using n8n and Dify Together

A powerful pattern: use n8n as the automation backbone and call Dify's API when AI processing is needed.

This lets you trigger Dify AI responses from any n8n trigger — new Zendesk ticket, incoming email, Slack message, webhook, or scheduled job.

Frequently Asked Questions

Can Dify and n8n be used together?

Yes — they complement each other well. Use n8n for event-driven automation and integrations, then trigger Dify workflows via Dify's REST API whenever LLM processing is needed.

Which is easier to self-host?

n8n is considerably simpler: a single Docker container on 2 GB RAM is all you need. Dify requires docker-compose with 8 services and at least 4 GB RAM to run reliably.

Does n8n support LLMs and AI?

n8n has HTTP nodes and basic AI agent nodes for calling LLM APIs, but it lacks Dify's RAG pipeline, knowledge base management, conversation history and embeddable chat UI.

How do the cloud prices compare?

n8n Starter is $20/mo (2,500 workflow executions). Dify Professional is $59/mo (1M message credits). For general workflow automation n8n is cheaper; for dedicated AI apps Dify provides more specialized value.

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When Dify Vs N8N Genuinely Wins

Dify has clear advantages in specific scenarios:

  • Shared VPS Environments: If you need to run on a shared 1GB VPS with another service, Dify's lower resource footprint (4 GB RAM recommended) compared to n8n (2 GB minimum) makes it more viable.
  • Integration with LangChain: If your team is already using LangChain for LLM applications, Dify's compatibility allows you to avoid rewriting integrations, streamlining your workflow.
  • Rapid Development of AI Chatbots: For teams focused on quickly deploying AI chatbots, Dify's pre-built chat UI and LLM capabilities significantly reduce development time compared to n8n's general automation features.
  • RAG Knowledge Bases: If your application requires a RAG (Retrieval-Augmented Generation) knowledge base, Dify's architecture is specifically designed for this purpose, providing better performance and easier implementation.

Migration Path: Dify Vs N8N to Dify

Transitioning from n8n to Dify involves several considerations:

  • Manual Rebuild: Flows in n8n need to be manually recreated in Dify. This includes reconfiguring triggers and actions, as Dify uses a different architecture.
  • Data Migration: Any data stored in n8n's workflows must be exported and imported into Dify manually, which can be time-consuming.
  • Expected Timeline: For a simple 3-flow project, expect 1-2 days for migration. A complex 20-flow production setup could take 1-2 weeks, depending on the intricacies of the workflows.
  • Community Scripts: As of now, there are no widely recognized community-maintained migration scripts from n8n to Dify, so manual migration is the primary method.

Hosting Cost Comparison

Tool Min RAM Requirement Cheapest VPS Monthly Cost
Dify 4 GB DigitalOcean ($10/month) $10
n8n 2 GB Vultr ($5/month) $5

Notes: Managed cloud options for Dify are limited, while n8n has several managed hosting providers that offer straightforward setups. Consider your team's requirements when choosing between self-hosted and managed solutions.

Community & Ecosystem

Community engagement and support are critical for both tools:

  • GitHub Stars: Dify has 134k+ stars, while n8n has 48k+ stars, indicating a larger community for Dify.