GNO vs PrivateGPT

Verdict: Both are privacy-first local RAG solutions. PrivateGPT is a Python-based server with Gradio UI and multiple LLM backend options, GNO is a TypeScript CLI with MCP integration and REST API. Choose PrivateGPT for flexible LLM backends and Python ecosystem, GNO for developer workflows and AI agent integration.

Both tools enable private document Q&A using local LLMs. Here’s how they compare.

Get Started

# GNO
bun install -g @gmickel/gno
gno init ~/notes --name notes && gno index

# PrivateGPT (Ollama setup)
git clone https://github.com/zylon-ai/private-gpt
cd private-gpt
poetry install --extras "ui llms-ollama embeddings-ollama vector-stores-qdrant"
ollama pull llama3.1 && ollama pull nomic-embed-text
PGPT_PROFILES=ollama make run

Quick Summary

Aspect GNO PrivateGPT
Best for Developers, AI agents Python devs, flexible backends
Unique strength CLI, MCP, REST API Multiple LLM providers
Stack Bun/TypeScript Python/FastAPI/Gradio
License MIT Apache-2.0

Feature Comparison

Feature GNO PrivateGPT
File Formats MD, PDF, DOCX, XLSX, PPTX, TXT MD, PDF, DOCX, PPTX, EPUB, CSV, JSON, MBOX, IPYNB, images, audio, video
Search Modes BM25, Vector, Hybrid Vector (Qdrant)
Reranking ✓ Cross-encoder
AI Answers (RAG)
Web UI gno serve ✓ Gradio
REST API ✓ FastAPI (OpenAI-compatible)
CLI ✓ Full-featured ✗ Scripts only
MCP Support ✓ 10+ targets
Local LLMs ✓ node-llama-cpp ✓ llama.cpp, Ollama
Database SQLite (embedded) Qdrant (requires service)
Setup Complexity Single command Git clone, Poetry, backend setup
Query Expansion ✓ LLM-powered
HyDE
Model Presets ✓ slim/balanced/quality
Folder Watch

LLM Backend Support

Provider GNO PrivateGPT
Local llama.cpp ✓ Built-in
Ollama
OpenAI
Azure OpenAI
Google Gemini
AWS SageMaker
vLLM

GNO Advantages

CLI-first design: Full-featured command line for scripting and automation.

gno query "authentication flow" --format json | jq '.results[0]'

MCP integration: One-command setup for Claude, Cursor, Windsurf, and more.

gno mcp install --target cursor

Hybrid search with reranking: BM25 + vector search with cross-encoder reranking for better results.

gno ask "how does caching work" --depth thorough --answer

Zero-dependency database: SQLite embedded, no external services needed.

Single command install: npm/bun global install, ready in seconds.

Skills: Native integration for Claude Code, Codex, OpenCode.

PrivateGPT Advantages

Multiple LLM backends: Switch between Ollama, llama.cpp, OpenAI, Azure, Gemini, SageMaker, and vLLM via config profiles.

Broader file format support: Handles EPUB, MBOX, Jupyter notebooks, images, audio, and video files.

OpenAI-compatible API: Drop-in replacement for OpenAI API clients.

Folder watching: Automatic ingestion when files change.

python scripts/ingest_folder.py /docs --watch

Python ecosystem: Built with FastAPI and LlamaIndex, easy to extend for Python developers.

Production deployment options: Docker images and multiple deployment configurations included.

When to Choose GNO

  • You want CLI access for scripting and automation
  • You need MCP integration for AI coding assistants (Claude, Cursor, Windsurf)
  • You prefer zero-config setup with embedded SQLite
  • You want hybrid search with BM25 + vector + reranking
  • You need fine-grained search control (depth, expansion, HyDE)
  • You work in JavaScript/TypeScript ecosystem

When to Choose PrivateGPT

  • You want to switch between multiple LLM providers (local and cloud)
  • You have EPUB, audio, video, or Jupyter notebook files
  • You want OpenAI-compatible API for existing integrations
  • You prefer Python ecosystem and LlamaIndex
  • You need folder watching for automatic ingestion
  • You want production deployment with Docker

Architecture Comparison

GNO: TypeScript/Bun, SQLite + node-llama-cpp, designed for CLI and MCP integration. Single-user, local-first, zero external dependencies.

PrivateGPT: Python/FastAPI/Gradio, Qdrant + LlamaIndex, designed for flexible LLM backends. Requires external services (Qdrant, optionally Ollama).