Dify vs Langflow vs FastGPT

Side-by-side comparison of features, pricing, and ratings

Live tool data as of 2026-07-06
Reviewed by our team on
Saved

At a glance

DimensionDifyLangflow
Pricingfreemium · from Sandbox $0/mofreemium · from Open Source $0/mo
Best forTeams building RAG-based customer support chatbots with human review, Marketing teams automating content workflows and social media postingRapid prototyping of AI agent workflows, Building and deploying RAG applications visually
Standout featuresDrag-and-drop visual workflow builder · Multi-LLM support (OpenAI, Anthropic, open-source models) · Built-in RAG pipeline with data ingestion and indexingVisual drag-and-drop flow builder · Python customization under the hood · One-click deployment to enterprise cloud
Viability score95/10095/100
APIYesYes

Dify is the stronger pick for teams building rag-based customer support chatbots with human review; Langflow fits better for rapid prototyping of ai agent workflows.

Built from live tool data, last verified 2026-07-06.

Dify
Dify

Open-source visual AI workflow builder for agents and RAG pipelines.

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Langflow
Langflow

Low-code visual builder for AI agents and RAG apps

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FastGPT
FastGPT

Enterprise AI agent builder & RAG platform with visual workflows and governance.

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Pricing
Freemium
Freemium
Contact Sales
Plans
$0/mo
$59/mo (billed annually at $590/yr)
$159/mo (billed annually at $590/yr)
$0/mo
Usage-based
Popularity
3.2k views
3.4k views
4.7k views
Skill Level
Beginner-friendly
Intermediate
Intermediate
API Available
Platforms
WebAPI
WebDesktopAPI
WebAPI
Categories
⚙️ Developer Infrastructure🤖 Automation & Agents
💻 Code & Development🤖 Automation & Agents
⚙️ Developer Infrastructure🤖 Automation & Agents
Features
Drag-and-drop visual workflow builder
Multi-LLM support (OpenAI, Anthropic, open-source models)
Built-in RAG pipeline with data ingestion and indexing
Native MCP integration (HTTP-based, protocol 2025-03-26)
Human-in-the-loop review node (v1.13.0+)
Template Marketplace with community workflows (March 2026)
Creator Center with affiliate program (PartnerStack)
Backend-as-a-service deployment for websites
Team asset management for workflows (v1.14.1)
Observability and monitoring of AI agents
Plugin/tool ecosystem for extending capabilities
Support for multiple vector databases
Role-based access control for teams
Self-hosted open-source or cloud-hosted options
Native MongoDB Atlas and Voyage AI integrations (June 2026)
Visual drag-and-drop flow builder
Python customization under the hood
One-click deployment to enterprise cloud
Run single or multiple AI agents
Reusable components and pre-built flows
Supports all major LLMs and vector databases
Flow as an API
Collaborative sharing and iteration
State management for complex workflows
Assistant-driven flow building (v1.10)
Memory bases for semantic memory (v1.10)
Natural-language policy guardrails (v1.10)
Desktop app for offline development (v1.10)
Global model provider setup (v1.8)
MCP server and client support (v1.9)
Visual AI agent workflow builder (block-stacking metaphor)
Hybrid retrieval (vector + keyword) to reduce hallucinations
Auto-cleanse and keep knowledge base data live
Full LLM lifecycle governance with debugging and auditing
Integrate any large language model
SSO and RBAC for enterprise security
Embed AI assistant into existing platforms via iframe
24/7 AI customer service with second-level response
Smart ticket routing (text and image understanding)
Intelligent resume screening and scoring
Expense reimbursement auto-review with anomaly flagging
Financial market report auto-generation with charts
AI sales role-play training with scoring
Private deployment (self-hosted) option
Rich API ecosystem for integration
Integrations
OpenAI
Anthropic
Llama 3
Mistral
Google Gemini
Cohere
Pinecone
Weaviate
Qdrant
Chroma
PostgreSQL
Zapier
Slack
Notion
GitHub
Airbyte
Azure
Bing
Composio
Confluence
Couchbase
Evernote
Glean
Gmail
Google Cloud
Google Drive
Groq
HuggingFace

Who should pick which

  • Solo developer building an AI side project
    Pick: Dify

    Dify is completely free and open-source, with no usage limits, and provides built-in RAG and MCP server publishing for flexible deployment.

  • Startup team prototyping agentic RAG applications
    Pick: Langflow

    Langflow's low-code drag-and-drop, Python customization, and team collaboration features enable rapid iteration and transparent flow building.

  • Enterprise needing a self-hosted AI platform with observability
    Pick: Dify

    Dify offers full open-source control, monitoring tools, and the ability to publish MCP servers, suitable for production and compliance.

  • Non-technical team deploying AI workflows without coding
    Pick: Langflow

    Langflow's visual flows and pre-built components allow non-coders to build AI agents, with a low-code escape hatch for custom needs.

  • Team needing to integrate multiple LLMs and vector databases
    Pick: Dify

    Dify supports a wide range of LLMs and built-in RAG pipelines with vector database indexing for seamless data ingestion.

Frequently Asked Questions

Which is better, Dify or Langflow?

The best choice between Dify and Langflow depends on your specific use case — we compare them independently on features, current pricing, integrations, and real-world signals (with an on-demand sentiment scan available for each). See the side-by-side breakdown above to match them to your needs.

What are the main differences between Dify and Langflow?

The key differences include pricing model, feature set, platform support, and skill level requirements. Review the full comparison on RightAIChoice for a detailed breakdown.

Is there a free version of Dify or Langflow?

Check the pricing section in the comparison for the latest pricing details on both tools, including free tiers, trial options, and paid plans.

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