Kotaemon vs Quivr

Kotaemon

RAG

Quivr

RAG

Tagline

Kotaemon

Open-source RAG UI for chatting with your own documents, locally or self-hosted.

Quivr

Open-source RAG framework for building custom AI assistants over your own documents in a few lines of Python.

Pricing

Kotaemon

Free· Free, open-source (MIT-style); self-hosted infrastructure costs only

Quivr

Free· Open source (pip install quivr-core); pay only for LLM/vector-store usage

Free trial

Kotaemon

Yes

Quivr

Yes

API

Kotaemon

Yes

Quivr

Yes

Platforms

Kotaemon

webmacoslinuxapi

Quivr

api

Open source

Kotaemon

Yes · Apache-2.0

Quivr

Yes · Apache-2.0

GitHub stars

Kotaemon

25,789

checked 2026-09-29

Quivr

7,414

checked 2026-09-29

Last GitHub push

Kotaemon

2026-07-14

Quivr

2025-02-21

First commit

Kotaemon

2024-03

Quivr

2024-05

Model used

Kotaemon

Multi-model (OpenAI, LlamaCPP, any OpenAI-compatible endpoint)

Quivr

Multi-model (OpenAI, Anthropic, Mistral, Gemma)

Best for

Kotaemon

Pick Kotaemon if you want a hackable, self-hosted RAG UI over your own documents with citation support and full control of the LLM and vector store.

Quivr

Pick Quivr if you are a Python developer who wants a lightweight, model-agnostic RAG library you can extend rather than a hosted chat-your-docs SaaS.

Not for

Kotaemon

Skip it if you need a polished SaaS product, enterprise SSO out of the box, or a managed RAG service you don't have to deploy yourself.

Quivr

Skip it if you want a turnkey no-code product with a polished UI, hosted vector store, and a sales team to call.

Editorial score

Kotaemon

7.0 / 10

Quivr

8.4 / 10

Use cases

Kotaemon

document-qaprivate-ragcitation-grounded-chatlocal-llm-frontendknowledge-base-search

Quivr

document-qacustom-knowledge-baserag-pipelineinternal-assistantschat-with-pdf

Pros

Kotaemon

• Genuinely model- and vector-store-agnostic; swap backends without touching code
• Citations with source highlights, not just naked LLM answers
• One-click HuggingFace Spaces deploy or local installer scripts
• Active GitHub project with clear extension hooks for developers

Quivr

• Genuinely open source and pip-installable, no vendor lock-in
• Model-agnostic: OpenAI, Anthropic, Mistral, and Gemma supported
• Minimal boilerplate to get a working RAG assistant running
• Pairs with Megaparse for tougher PDF and document ingestion
• Customizable pipeline with tools and web search when you need more

Cons

Kotaemon

• Gradio UI feels prototype-grade compared to commercial RAG products
• Default admin/admin credentials and thin auth aren't production-ready
• Self-hosted only — no managed SaaS option if you don't want to run it

Quivr

• Python library, not a hosted product or UI
• You manage infra, vector store, and evals yourself
• Documentation site is sparse compared to larger RAG frameworks
• LLM and embedding costs are on you

Website

Kotaemon

cinnamon.github.io

Quivr

core.quivr.com

Editorial score: rule-based, 0–10, from AI-assisted profile inputs (see /methodology) — not a user rating; “—” means unscored. “Not listed” 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.