Dify vs Flowise 2026: Which AI Agent Platform Fits Your Workflow?

Both platforms are excellent, but for very different reasons. Dify (149K GitHub stars) and Flowise (55K stars) target overlapping but distinct problems. Here's the breakdown after half a year building production agents on both.

## TL;DR **Building RAG apps (Q&A bots, knowledge bases)? Pick Dify. Building complex Agent workflows (multi-step reasoning, tool calling)? Pick Flowise.** It's that simple on the surface. But the real differences run deeper. --- ## 1. Deployment Experience ### Dify ★★★★☆ Dify's docker-compose setup is mature and well-documented: ```bash git clone https://github.com/langgenius/dify.git cd dify/docker cp .env.example .env docker compose up -d ``` It works in about 15 minutes. But it spins up 6 containers (API, Worker, Web, DB, Redis, Nginx). **A 2C4G server will struggle** — budget for 4C8G minimum. ### Flowise ★★★★★ Flowise is absurdly simple: ```bash npm install -g flowise flowise start ``` One Node.js process. Or Docker in one line: ```bash docker run -d --name flowise -p 3000:3000 flowiseai/flowise ``` **Runs comfortably on 1C2G.** For personal dev and testing, Flowise's lightness is a killer advantage. **Verdict:** Solo devs / small teams → Flowise wins. Enterprise deployment → Dify's complete stack is more appropriate. --- ## 2. RAG Capabilities ### Dify ★★★★★ RAG is Dify's home turf. - **Knowledge base management:** 10+ data sources (PDF, HTML, Notion, websites), adjustable chunking strategies - **Retrieval strategies:** Vector search + full-text search + hybrid + HyDE mode - **Recall testing:** Built-in recall evaluation — tweak chunking params, see recall metrics instantly - **Embedding models:** Built-in OpenAI, Cohere, Jina, plus custom providers ### Flowise ★★★☆☆ Flowise *can* do RAG, but it's not pleasant. - You manually chain Vector Store + Embedding + LLM nodes - **No built-in knowledge base UI** — document upload, chunk preview are DIY - Retrieval is limited to simple Top K vector search **Verdict:** Building a knowledge Q&A system → Dify, no contest. Flowise's RAG works but feels like an afterthought. --- ## 3. AI Agent Capabilities ### Dify ★★★★☆ Dify's Agent features improved dramatically in v2.0: - ReAct and Function Calling modes - Built-in tools: Google Search, Bing, Wolfram Alpha, etc. - Custom tools via OpenAPI/Swagger import or custom code - Multi-agent orchestration with transitions **Limitation:** You can't fine-tune the Agent's internal reasoning prompt. Want to customize the ReAct template? Not exposed. ### Flowise ★★★★★ Agent workflows are Flowise's real strength: - **Fully open prompt control** — modify the system prompt, ReAct template, even per-step instructions - **ChatFlow visual canvas** — not rigid chains, you can draw branches, loops, conditionals - **Unrestricted tooling** — write custom JS/Python as tools, or use any API - **Native multi-agent** — Supervisor → Specialist pattern built in **Real scenario:** I needed an Agent to query a database, decide which API to call based on results, and compile a report. In Flowise, ChatFlow + conditional branches + loop nodes: 30 minutes. In Dify, achieving the same logic required writing custom code. **Verdict:** Deep Agent customization → Flowise wins hands down. --- ## 4. Community & Ecosystem | Dimension | Dify | Flowise | |:----------|:-----|:--------| | GitHub Stars | 149K | 55K | | Contributors | 600+ | 200+ | | Integrations | 40+ built-in | 100+ community | | Docs Quality | Excellent (zh + en) | Decent (English only) | | Chinese Community | Active (WeChat/Feishu) | Quiet | Dify has strong ties to ByteDance and excellent Chinese-language support. Flowise is fully international. **Verdict:** Chinese-speaking developers → Dify's ecosystem is more accessible. English-preferring devs who value customization → Flowise offers more freedom. --- ## 5. Extensibility ### Dify Python backend (Flask + Celery) + TypeScript frontend. - **Plugin system:** Official plugin marketplace launched in 2026 - **API:** Well-documented RESTful API for embedding in other systems ### Flowise Node.js + React + Express. - **Node packages:** Publish npm packages as custom nodes (primary extension method) - **Full source access:** Fork and modify freely (GPL-3.0) - **Embedded mode:** Can embed into your existing Express/Next.js app **Core difference:** Dify is a *platform* you use. Flowise is a *framework* you modify. --- ## Summary: Decision Matrix | Your Need | Recommended | |:----------|:------------| | Knowledge base Q&A bot | **Dify** | | Enterprise deployment | **Dify** | | Deep Agent prompt customization | **Flowise** | | Low-resource server | **Flowise** | | Chinese docs/community | **Dify** | | Embed into Node.js app | **Flowise** | | External API integration | Both work | **My advice:** Install both. Dify via Docker, Flowise via npm global install — they don't conflict. Use Dify for knowledge base scenarios, Flowise for Agent-heavy tasks. That's my setup, and it's been working well. > 💡 **Bookmark this.** Platform choice is a long-term decision — switching costs are high. Every dimension in this comparison comes from real usage, not docs-reading. > > 📤 **Share with a friend building AI Agents.** They're probably agonizing over the same choice. This will save them a full day of research. Previous: Advanced n8n Workflows for AI Agents Next: Building AI Agent APIs with FastAPI — From Zero to Production