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← Back to Dify Overview

Dify Pricing & Plans 2026

Complete pricing guide for Dify. Compare all plans, analyze costs, and find the perfect tier for your needs.

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Still deciding? Read our full verdict on whether Dify is worth it →

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Custom Pricing Available

Dify offers flexible pricing options. Visit their website for detailed pricing information and to request a quote.

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Pricing sourced from Dify · Last verified March 2026

Is Dify Worth It?

✅ Why Choose Dify

  • • Visual orchestration reduces boilerplate for common LLM flows
  • • Model flexibility helps teams compare providers
  • • Self-hosting and MCP support suit technical integration teams

⚠️ Consider This

  • • Production deployments still require monitoring and security engineering
  • • Complex workflows can become difficult to debug visually
  • • Hosted pricing and current usage limits could not be verified

What Users Say About Dify

👍 What Users Love

  • ✓Visual orchestration reduces boilerplate for common LLM flows
  • ✓Model flexibility helps teams compare providers
  • ✓Self-hosting and MCP support suit technical integration teams

👎 Common Concerns

  • ⚠Production deployments still require monitoring and security engineering
  • ⚠Complex workflows can become difficult to debug visually
  • ⚠Hosted pricing and current usage limits could not be verified

Pricing FAQ

Is Dify free and open source?

Yes. Dify is released under an open-source license and can be self-hosted at no cost using Docker Compose or Kubernetes. The team also offers a managed cloud service with paid tiers for users who prefer not to manage infrastructure, plus enterprise plans with SSO, advanced RBAC, and SLA support.

Which LLMs and model providers does Dify support?

Dify is model-agnostic and supports hundreds of providers including OpenAI, Anthropic Claude, Google Gemini, Azure OpenAI, AWS Bedrock, Mistral, Cohere, DeepSeek, Qwen, and Llama. It also integrates with locally hosted runtimes such as Ollama, vLLM, LocalAI, and Xinference, allowing fully on-premise deployments.

How does Dify compare to LangChain or LangGraph?

LangChain and LangGraph are code-first Python libraries for building LLM applications, while Dify is a complete platform that wraps similar capabilities behind a visual builder, hosted UI, RAG engine, and observability layer. Teams that want full programmatic control may prefer LangGraph; teams that want a deployable product with less boilerplate typically prefer Dify.

Can Dify handle Retrieval-Augmented Generation (RAG)?

Yes. Dify includes a built-in knowledge base feature that ingests PDFs, Word documents, web pages, and structured data, then handles chunking, embedding, vector storage, hybrid search, and reranking. Knowledge bases can be attached to any chatbot, agent, or workflow without external infrastructure.

Is Dify suitable for production deployments?

Yes. Dify exposes every application as a REST API, supports horizontal scaling on Kubernetes, and includes logging, prompt versioning, and analytics for production monitoring. Many companies run customer-facing chatbots and internal copilots on Dify, though teams with strict compliance needs typically choose self-hosted or enterprise tiers.

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