Last updated: May 2026
What Is Dify?
Dify is the open-source LLM application development platform that lets developers build AI agents, chatbots, RAG (retrieval-augmented generation) pipelines, and AI workflows without managing infrastructure. The product combines a visual workflow builder, RAG pipelines, prompt management, and deployment runtime in one stack. Dify serves over 200,000 developers and is one of the fastest-growing open-source AI projects.
The pitch is "LangChain plus a visual UI plus production deployment." Build an agent visually rather than coding chains. Plug in your data via built-in RAG. Deploy as an API endpoint or embed widget. The same project runs on the Dify cloud or self-hosted via Docker on your own infrastructure.
The product targets engineering teams building AI products, startups iterating on AI use cases, and enterprises wanting AI applications without vendor lock-in. Open source license means companies can self-host and modify code; cloud SaaS option offers managed hosting for teams that prefer not to manage infrastructure.
Try Dify FreeHow Dify Works
Create an app from four types: chatbot (conversational interface), agent (multi-step reasoning with tools), workflow (sequential or branching automation), text generation (prompt-based content creation). Each type has different capabilities; pick based on the use case.
Connect data sources for RAG. Upload PDFs, link to websites, sync from Notion, connect to databases. Dify chunks documents, embeds them, and retrieves relevant context during conversation. Vector database (built-in or external Pinecone/Weaviate) stores embeddings.
Configure model selection per app. Switch between OpenAI (GPT-4o, GPT-4 Turbo), Anthropic (Claude 3.5), Google (Gemini), Meta Llama (self-hosted), local models via Ollama. Multi-model approach means you can pick the best LLM for each use case based on cost, performance, or compliance.
The Studio is a visual builder for complex workflows. Drag in nodes for LLM calls, RAG retrieval, code execution (Python or JavaScript), HTTP requests, conditional branching, loops, and human-in-the-loop approval points. Test interactively with sample inputs; deploy when ready.
Deploy as REST API for application integration, embed widget for website chatbot, or web app for standalone access. Production-ready with monitoring, logging, version control, and rate limiting.
Dify Pricing in 2026
Sandbox: Free. 200 messages, 50 documents. Trial-grade.
Professional: $59/month annually. 5,000 messages, unlimited apps, priority support.
Team: $159/month annually. 10,000 messages, 5 team members, advanced features.
Enterprise: Custom pricing. SSO, on-prem, dedicated support, advanced security.
Self-hosted is free under the open-source license (no usage limits, you pay only for infrastructure and LLM costs).
See Dify PlansWhere Dify Wins
- Open source: no vendor lock-in, self-hostable.
- Visual workflow builder: faster than coding LangChain pipelines.
- Multi-model support: switch between LLM providers per app.
- RAG built in: document upload and retrieval works out of the box.
- Production-ready: handles scaling, monitoring, version control.
Where It Falls Short
- Self-hosting takes ops work: Docker setup, monitoring, scaling all on you.
- Less polished than commercial tools: rough edges in the UI compared to LangSmith.
- Documentation gaps: open source means some features lack thorough guides.
- Smaller ecosystem than LangChain: fewer pre-built integrations.
Dify vs LangChain vs Flowise vs n8n
LangChain is the code-first framework. More flexibility, much more development time.
Flowise is the closest open-source competitor with similar visual builder. Smaller community.
n8n is workflow automation first with AI capability bolted on. Pick n8n if non-AI automation matters more.
Botpress targets conversational AI specifically.
Who Should Use Dify
Developers building AI products quickly: visual builder plus self-hostable runtime.
Startups iterating on AI use cases: rapid prototyping without infrastructure overhead.
Enterprises wanting self-hosted AI: open source license, on-prem deployment, no data leaving your environment.
Internal tools teams: build AI assistants for HR, IT, sales without procurement of new SaaS.
Skip it if: you only need a chatbot widget (use ChatGPT custom GPTs), you have deep LangChain expertise and prefer code, or your AI needs are simple enough for ChatGPT API direct.
Frequently Asked Questions
Can I self-host Dify?
Yes. Docker Compose setup, full open-source code.
Which LLMs does Dify support?
OpenAI, Anthropic, Google Gemini, Meta Llama, Azure, local models via Ollama, and more.
How does RAG work?
Upload documents; Dify chunks and embeds them. Retrieves relevant chunks during conversation to ground LLM responses in your data.
Is the cloud version different from self-hosted?
Same features, different deployment. Cloud handles infrastructure; self-hosted gives full control.
Does it support vector databases?
Built-in vector store. Optional integrations with Pinecone, Weaviate, Milvus for larger deployments.
