RAGFlow vs UltraRAG
A side-by-side look at pricing, capabilities, pros, cons, and our editorial scores.
Tagline
RAGFlow
Open-source RAG engine with deep document parsing, hybrid search, and visual agent orchestration.UltraRAG
Low-code, YAML-driven RAG pipeline orchestrator with a visual UI for building and demoing retrieval systems.Pricing
RAGFlow
FreemiumΒ· Free tier; Starter $29/mo; Pro $129/mo; Enterprise customUltraRAG
FreeΒ· Open source; self-hostedFree trial
RAGFlow
YesUltraRAG
YesAPI
RAGFlow
YesUltraRAG
YesPlatforms
RAGFlow
api
UltraRAG
api
Open source
RAGFlow
Yes Β· Apache-2.0UltraRAG
YesGitHub stars
RAGFlow
91,511
checked 2026-09-29
UltraRAG
βLast GitHub push
RAGFlow
2026-09-29UltraRAG
βFirst commit
RAGFlow
2023-12UltraRAG
βModel used
RAGFlow
Multi-modelUltraRAG
Multi-model (MiniCPM-Embedding-Light, AgentCPM-Report, BYO LLM)Best for
RAGFlow
Pick RAGFlow if you need a self-hostable, citation-grounded RAG stack that can actually digest gnarly enterprise documents and feed agents.UltraRAG
Pick UltraRAG if you want a transparent, self-hosted RAG orchestrator with a visual UI and YAML-driven loops, not a hosted black box.Not for
RAGFlow
Skip it if you just want a hosted chat-with-PDF widget or you're allergic to running your own infrastructure.UltraRAG
Skip it if you need a managed SaaS RAG service with SLAs, or you'd rather build directly on LangChain/LlamaIndex's larger ecosystem.Editorial score
RAGFlow
8.1 / 10UltraRAG
7.1 / 10Use cases
RAGFlow
document-qaenterprise-searchagent-orchestrationknowledge-basehybrid-retrieval
UltraRAG
rag-pipelinesknowledge-base-qapipeline-orchestrationrag-evaluationagentic-retrieval
Pros
RAGFlow
- Strong deep-document parsing for messy PDFs, tables, and scans
- Hybrid vector + BM25 retrieval with citation-grounded answers
- Fully open-source with active GitHub repo and self-host option
- Visual agent builder plus MCP integration for tool-calling clients
- Model-agnostic; works with most major LLM providers
UltraRAG
- Fully open source under OpenBMB - no vendor lock-in
- YAML pipelines support loops and conditionals, not just linear chains
- Visual UI for knowledge-base management and demoing
- Transparent step-by-step inspection of every retrieval and generation call
Cons
RAGFlow
- Free tier blocks API access, pushing real use to paid plans
- Self-hosting is non-trivial and resource-hungry
- Documentation and UI lag behind the engine's capabilities
UltraRAG
- Self-hosted only - you bring the infra and GPU
- Reference stack leans on OpenBMB's own MiniCPM models
- Smaller ecosystem and community than LangChain/LlamaIndex
- Docs are research-flavored; production hardening is on you
Editorial score: rule-based, 0β10, from AI-assisted profile inputs (see /methodology) β not a user rating; βββ means unscored. βNot listedβ means we have no record of it, not that it is absent. GitHub figures and prices carry the date they were checked or captured; prices are shown as published, unconverted.
Pick RAGFlow if
- β Strong deep-document parsing for messy PDFs, tables, and scans
- β Hybrid vector + BM25 retrieval with citation-grounded answers
- β Fully open-source with active GitHub repo and self-host option
- β Visual agent builder plus MCP integration for tool-calling clients
Pick UltraRAG if
- β Fully open source under OpenBMB - no vendor lock-in
- β YAML pipelines support loops and conditionals, not just linear chains
- β Visual UI for knowledge-base management and demoing
- β Transparent step-by-step inspection of every retrieval and generation call