The Open Source Alternative to ChatGPT Enterprise & Custom GPTs

🩺 Vitals

📦 Version: v1.10.0 (Released 2026-01-22)
🚀 Velocity: Active (Last commit 2026-01-30)
🌟 Community: 54.0k Stars · 5.8k Forks
🐞 Backlog: 272 Open Issues

🏗️ Profile

Official: anythingllm.com
Source: github.com/Mintplex-Labs/anything-llm
License: MIT
Deployment: Desktop App / Docker
Data Model: Integrated Vector DB (LanceDB) + SQLite
Jurisdiction: USA 🇺🇸
Compliance: Not specified (Self-hosted / Enterprise available)
Complexity: Low (1/5) - One-click Desktop Install
Maintenance: Low (2/5) - Auto-updating
Enterprise Ready: High (4/5) - Multi-userDocker, RBAC

1. The Executive Summary

What is it? AnythingLLM is a full-stack application that turns any device into a private, secure AI powerhouse. It allows individuals and teams to chat with their documents (RAG), build custom AI agents, and automate workflows without writing code. It supports virtually any LLM (Ollama, OpenAI, Anthropic) and Vector Database.

The Strategic Verdict:

🔴 For Pure Model Running: Caution. If you just want to run Llama 3, tools like Ollama or LM Studio are lighter. AnythingLLM is for using the models with data.
🟢 For Private RAG: Strong Buy. Easiest way to set up a "Chat with PDF" system for a team, completely on-premise.

2. The "Hidden" Costs (TCO Analysis)

Cost Component	Proprietary (Custom GPTs)	AnythingLLM (Self-Hosted)
Data Privacy	Training Risk	100% Local
Subscription	~$20/user/mo	$0 (MIT)
Hardware	Low (Cloud)	Moderate (Depends on Model)

3. The "Day 2" Reality Check

🚀 Deployment & Operations

Installation: The Desktop version is a simple installer. TheDocker version converts it into a multi-user server with accounts and permissions.
Flexibility: Highly modular. You can swap out the LLM provider (e.g., move from OpenAI to local Ollama) or Vector DB at any time.

🛡️ Security & Governance

Compliance: Not specified (Self-hosted / Enterprise available)
Access Control: TheDocker version supports password-protected workspaces and multi-user management.

AnythingLLM