Dify vs RAGFlow
Dify
dify.ai
RAGFlow
ragflow.ioSide by side
| Figure | Dify | RAGFlow |
|---|---|---|
| Price from | $49.17/mo | $29/mo |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | Yes |
| Web | Yes | Yes |
| Windows | Yes | — |
| macOS | Yes | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 11 | 5 |
| Spec score · Retrieval-Augmented Generation Tools | 9.4 (#1) | 8.8 (#3) |
| Company legal name | Dify’s terms identify the provider as LangGenius, Inc., a Delaware corporation. | Crunchbase lists the legal name as InfiniFlow Inc. |
| License | Dify uses a modified Apache 2.0 license with restrictions on unauthorized multi-tenant operation and removing frontend branding or copyright notices. | The public repository is labeled Apache-2.0 licensed. |
| Model integrations | Dify connects to proprietary and open-source LLM providers including OpenAI, Anthropic, Google Gemini, and xAI. | Documented model providers include OpenAI, Anthropic, Azure OpenAI, Bedrock, Cohere, Gemini, DeepSeek, Ollama, Xinference, LocalAI, Mistral, NVIDIA and OpenAI-compatible endpoints. |
| Purpose | Dify is an open-source platform for building AI applications with agentic workflows, RAG pipelines, model management, observability, and tools. | RAGFlow describes itself as an open-source RAG engine and integrated agent platform for building a context layer for AI agents. |
| Rating on G2 | 4.1 out of 5 from 20 reviews. | 0.0 out of 5 from 0 reviews; G2 says there are not enough reviews to provide buying insight. |
| Self-hosting | Community Edition can be deployed with Docker Compose, while Enterprise supports private or VPC deployment and Kubernetes Helm charts. | RAGFlow is deployed with Docker Compose and can be run on user-controlled infrastructure. |
| System requirements | The Docker deployment requires at least two CPU cores and 4 GiB RAM; supported setups include macOS 10.14+, Linux with Docker 19.03+, and Windows with WSL2. | The documented starting configuration is four x86 CPU cores, 16 GB RAM and 50 GB free disk. |
| What it does | Dify is an LLM application platform combining visual workflows, RAG pipelines, agents, model and tool support, publishing, and monitoring. | RAGFlow is an open-source retrieval-augmented-generation engine and agent platform designed to provide grounded answers with citations. |
Plans
Dify
- CommunityFree
- CommunityFree
- SandboxFree
- SandboxFree
- Professional$59 a month
- Team$159 a month
- Professional$590 a year
- Professional$590 a year
- Team$1,590 a year
- Team$1,590 a year
RAGFlow
- FreeFree
- FreeFree
- Starter$29 a month
- Pro$129 a month
- EnterprisePriced on request
In their own words
Dify
Dify is an open-source platform for building AI applications with agentic workflows, retrieval pipelines, model management, observability, and tools. Workflow Studio provides a visual canvas for model calls, knowledge retrieval, tools, code, branching, triggers, and human review. Workflows can start from user input, API calls, schedules, webhooks, plugin events, or uploaded payloads. Knowledge Pipeline turns files, online documents, drives, crawlers, and web content into searchable knowledge bases with metadata and citations. Retrieval supports semantic, keyword, hybrid, and reranked methods with metadata filters. Applications can be published as hosted web apps, website embeds, API endpoints, or MCP servers. Dify connects to providers including OpenAI, Anthropic, Google Gemini, and xAI, while its Marketplace lists more than 200 tools. Community Edition is self-hostable with Docker; Enterprise can run in a customer VPC, on-premises, or an air-gapped network. Sandbox and Community are free. Professional costs $590 a year per workspace; Team costs $1,590 a year per workspace.
RAGFlow
RAGFlow is an open-source retrieval-augmented generation engine and agent platform for building a context layer for AI agents. Its ingestion pipeline processes multiple data formats into semantic representations for retrieval. Search combines vector search and BM25 with custom scoring and re-ranking, while visual workflows connect retrieval, tools, and MCPs for agent orchestration. Users can connect online, local, and OpenAI-compatible model providers for knowledge bases, chats, search, and agents. Documented connectors include Notion, Google Drive, S3, Microsoft Teams, REST API, and Sitemap. RAGFlow provides HTTP and Python APIs, and a chat assistant can be embedded in another webpage using an iframe. It offers cloud and self-hosted deployment; Docker deployment has a stated minimum of 4 CPU cores, 16 GB RAM, and 50 GB disk. The free plan includes five apps, one team member, 0.1 GB of dataset storage, and 500 monthly credits, but no API key. Starter costs $29 a month and includes an API key.