RAGFlow vs 
LiteLLM
RAGFlow vs LiteLLM compared for 2026 — features, license, ease of use, performance and which one to choose. Deep-document-understanding RAG vs One API for 100+ LLM providers.
Updated regularly · curated by OpenSourceAI.tech
RAGFlow vs LiteLLM at a glance
| Spec | RAGFlow | LiteLLM |
|---|---|---|
| Category | LLM / RAG framework | LLM / RAG framework |
| Type | RAG engine | LLM gateway / SDK |
| License | Apache-2.0 | MIT |
| Runs locally | Self-hosted | Cloud-optional |
| Primary language | Python | Python |
| Ease of use | Intermediate | Beginner |
| Best for | RAG over messy, complex documents | teams standardizing on one LLM interface |
| GitHub stars | 85.2k | 53.8k |
How RAGFlow and LiteLLM score
| Criterion | RAGFlow | LiteLLM |
|---|---|---|
| Popularity | 4.5 | 4.5 |
| Maintenance | 5.0 | 5.0 |
| Ease of use | 3.5 | 5.0 |
| Privacy | 4.5 | 3.5 |
| License freedom | 5.0 | 5.0 |
Scores are computed automatically from public signals — GitHub stars (popularity), recent commit activity (maintenance), license type (freedom), local-first design (privacy) and onboarding complexity (ease of use). Indicative, not a verdict.
What each one is
RAGFlow
RAGFlow is an open-source RAG engine built on deep document understanding, extracting clean structure from complex files to give LLMs grounded, cited answers.
- Strong document layout understanding
- Grounded answers with citations
- Self-hostable web UI
LiteLLM
LiteLLM is a gateway and SDK that exposes 100+ LLM providers behind the OpenAI format, adding routing, fallbacks, budgets and observability.
- OpenAI-format access to 100+ providers
- Routing, fallbacks, budgets and rate limits
- Proxy server for org-wide governance
Key differences
RAGFlow is rAG engine, while LiteLLM is lLM gateway / SDK. Their licenses differ (Apache-2.0 vs MIT), which matters if you ship a commercial product. RAGFlow leans more intermediate-friendly, whereas LiteLLM is more suited to beginner users. They also differ in how they run (Self-hosted vs Cloud-optional). In short, RAGFlow fits RAG over messy, complex documents, and LiteLLM fits teams standardizing on one LLM interface.
Which should you choose?
Choose RAGFlow for RAG over messy, complex documents. Choose LiteLLM for teams standardizing on one LLM interface.
There is rarely one winner — many setups use both. The right pick depends on your hardware, your team's skills, and whether you value simplicity or control.
Frequently asked questions
Is RAGFlow or LiteLLM easier to use?
LiteLLM is generally the easier of the two to get started with, while RAGFlow rewards more setup with more control.
Are RAGFlow and LiteLLM free?
RAGFlow is free and open source (Apache-2.0), and LiteLLM is free and open source (MIT). Neither charges for the core software.
Can I run RAGFlow and LiteLLM locally?
RAGFlow: self-hosted · LiteLLM: cloud-optional. Both can be used without sending your data to a third-party cloud where their setup allows.
RAGFlow vs LiteLLM — which should I pick in 2026?
Choose RAGFlow for RAG over messy, complex documents. Choose LiteLLM for teams standardizing on one LLM interface.
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