Side-by-Side Comparison · 2026

Dify vs Flowise: Full Comparison (2026)

Dify is open-source llm app development platform for building ai workflows and agents. Flowise is open-source no-code llm flow builder for building ai apps visually. Use the breakdown below to find the right fit for your needs.

Dify

Dify.AI

Freemium
vs

Flowise

FlowiseAI

Freemium
This page presents factual information sourced from publicly available vendor documentation and product pages. AIHub does not endorse either product. The right tool depends on your specific use case, team, and requirements — we recommend evaluating both tools directly before making a decision.

Side-by-Side Overview

Pricing Model
Dify: FreemiumFlowise: Freemium
API Access
Dify: AvailableFlowise: Available
Platforms
Dify: Web (cloud), Self-hosted (Docker), KubernetesFlowise: Web (cloud), Docker (self-hosted), npm, Railway, Render
Integrations
Dify: 9 integrationsFlowise: 10 integrations
Vendor
Dify: Dify.AIFlowise: FlowiseAI
Category
Dify: Developer ToolsFlowise: Frameworks
Launch
Dify: Mar 2023Flowise: 2023
Models
Dify: GPT-4o, Claude 3.5 SonnetFlowise: Any via LangChain (OpenAI, Anthropic, Google, Ollama, Hugging Face, 50+ providers)

About Dify

Dify is an open-source platform for building LLM-powered applications, workflows, and agents without deep coding. It provides a visual workflow builder, RAG pipeline, agent orchestration, prompt management, and a model-agnostic backend that supports OpenAI, Anthropic, Llama, Azure, and dozens of other providers. It can be self-hosted or used as a cloud service.

Designed For

  • Building chatbots with RAG
  • LLM workflow automation
  • Agent orchestration
  • Prompt engineering & testing
Full Dify details

About Flowise

Flowise is an open-source, low-code tool for building LLM applications and AI agent workflows using a visual drag-and-drop interface. Built on LangChain under the hood, it lets developers and non-developers assemble RAG pipelines, chatbots, and agent chains without writing code. Self-hostable with Docker, it has become one of the most popular tools for visually prototyping and deploying LLM apps.

Designed For

  • RAG chatbot building
  • Visual LLM workflow prototyping
  • Agent pipeline creation
  • Document Q&A apps
Full Flowise details

Strengths & Limitations

Dify

Strengths

  • Open-source with self-hosting option
  • Visual workflow builder
  • Model-agnostic (50+ providers)
  • Built-in RAG and vector store
  • Active community & fast iteration

Limitations

  • Can be complex for simple use cases
  • Cloud plan limits on free tier
  • Docs sometimes lag releases

Flowise

Strengths

  • Drag-and-drop visual builder
  • LangChain components included
  • Self-hostable for free
  • Built-in vector store integrations
  • Embed chatbots on websites
  • Active community

Limitations

  • Less flexible than pure code
  • Can hit complexity limits for large flows
  • Cloud version needed for non-technical sharing
  • Performance overhead vs raw LangChain

Frequently Asked Questions

What is the difference between Dify and Flowise?

Dify is open-source llm app development platform for building ai workflows and agents, while Flowise is open-source no-code llm flow builder for building ai apps visually. Dify is designed for Developers building LLM apps, Enterprises with custom AI needs; Flowise is designed for Non-developers building AI apps, Agencies prototyping AI solutions. The right fit depends on your specific requirements.

How do the pricing models compare?

Dify is available under a Freemium model. Flowise is available under a Freemium model. Dify's entry tier starts at $0. Flowise's entry tier starts at $0. Always verify pricing on each vendor's official website as it may change.

What integrations does each tool support?

Dify integrates with OpenAI, Anthropic, Azure OpenAI, Hugging Face. Flowise integrates with OpenAI, Anthropic, Ollama, Pinecone. Check each vendor's documentation for the full and current list.

How do I choose between Dify and Flowise?

Consider your team's technical requirements, budget, existing tooling, and use case before deciding. We recommend signing up for free trials or demos of both tools where available, and consulting each vendor's documentation. AIHub provides this comparison for informational purposes only.