Dify vs Mastra (2026)
Updated March 10, 2026
Overview
Dify is an open-source platform for building LLM applications with both visual and code-based interfaces. It provides a workflow orchestration engine, RAG pipeline builder, agent framework, and model management—all accessible through a web UI. Dify supports 50+ LLM providers, offers enterprise features like SSO and access control, and can be self-hosted or used as a cloud service.
Mastra is a TypeScript-first agent framework for building production AI applications. It provides primitives for agents, workflows, RAG, integrations, and memory with a focus on developer experience and type safety. Mastra is designed for full-stack TypeScript developers who want to build AI features without leaving their existing tech stack.
Key features
Core capabilities each platform advertises.
- Visual workflow builder for AI apps
- Multi-model support
- RAG pipeline builder
- Plugin ecosystem
- Self-hosted and cloud options
- TypeScript agent framework
- Built-in tool calling and workflows
- Sync engine for agent state
- Integration marketplace
- Production-ready agent primitives
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Open-source with strong community
- Visual workflow builder accelerates development
- Generous free tier with 200 GPT-4 calls
- Production-ready platform
Cons
- Pricing details not fully transparent
- Specific tier costs require contact
- Taxes excluded from published prices
Pros
- Production-ready platform
- Good performance
- Active development
- Strong features
Cons
- Enterprise pricing varies
- Setup complexity
- Learning curve required
Dify or Mastra — which should you choose?
Choose Dify if you wantChoose if you want
- Building AI chatbots without deep coding
- RAG application development
- AI workflow prototyping
- Multi-model application design
- Enterprise AI tool deployment
Choose Mastra if you wantChoose if you want
- TypeScript-native agent development
- Building AI workflows with tool use
- Agent state management
- Production agent deployment
- Multi-step task automation
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