⚡ TL;DR — The Verdict

LangFlow (8.2/10) vs Dify (8.3/10) — extremely close. LangFlow stands out with visual drag-and-drop flow builder and 100+ integrations. Dify wins on visual ai workflow builder with LangFlow is cheaper to self-host. Your choice depends on whether you prioritize workflow style.

LangFlow vs Dify: Complete 2026 Comparison

Updated · Based on real deployment data · 10 min read

LangFlow

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

Dify

8.3
Best for: Teams building production LLM applications who want an all-in-one platform with visual builder and built-in observability

Head-to-Head Comparison

Feature LangFlow Dify
Primary Use Case Visual framework for building multi-agent and RAG applications with a Python-based drag-and-drop UI Open-source LLM app development platform combining AI workflow builder, RAG pipeline, agent capabilities, and model management
GitHub Stars 35,000+ 45,000+
Integrations 100+ 120+
Language Python Python/TypeScript
License MIT Apache-2.0 (with commons clause for enterprise)
Min RAM 1GB 2GB
Docker Image Size ~650MB ~700MB
Self-Host Cost $10/mo $15/mo
Cloud Pricing N/A (self-host only) $59/mo
Ease of Use 8.5/10 8.5/10
AI Capabilities 8.5/10 9/10
Community Score 8/10 8.5/10
Contributors 200+ 400+

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:

LangFlow Self-Hosted

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

Dify Self-Hosted

$15/mo
  • 2GB RAM recommended
  • ~700MB Docker image
  • Apache-2.0 (with commons clause for enterprise)
  • Plugin marketplace
  • 400+ contributors

Or: Host Both on VM Nebula

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

When to Use Each (Real Scenarios)

Choose LangFlow when:

Python developers wanting a visual way to build and iterate on LangChain-based LLM applications. Key features include visual drag-and-drop flow builder, python-native components, multi-agent orchestration, making it the go-to choice for AI development workflows.

Choose Dify when:

Teams building production LLM applications who want an all-in-one platform with visual builder and built-in observability. It stands out with visual ai workflow builder, rag pipeline with advanced chunking, multi-model support (100+ models), making it ideal for LLM-powered applications.

Use both together when:

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

Deploy LangFlow + Dify in 20 seconds

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

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Frequently Asked Questions

Is LangFlow better than Dify in 2026?
LangFlow scores 8.2/10 overall while Dify scores 8.3/10. LangFlow excels at visual drag-and-drop flow builder, while Dify is stronger for visual ai workflow builder. The best choice depends on your specific use case.
How much does it cost to self-host LangFlow vs Dify?
Self-hosting LangFlow costs approximately $10/month (1GB RAM minimum). Dify costs about $15/month (2GB RAM minimum). Both can be hosted on VM Nebula starting at $9.99/month.
Can LangFlow replace Dify?
In many cases yes, as both are LLM Orchestration tools. However, LangFlow is better for python developers wanting a visual way to build and iterate on langchain-based llm applications, while Dify is optimized for teams building production llm applications who want an all-in-one platform with visual builder and built-in observability.
Which is easier to set up: LangFlow or Dify?
LangFlow is easier to set up (ease-of-use score: 8.5/10). Dify requires more configuration (score: 8.5/10). Visual drag-and-drop flow builder makes the initial setup straightforward.
What is the cheapest way to run LangFlow and Dify?
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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