Alternatives to ChatGPT Business

At a glance

Open-source alternatives to ChatGPT Business compared
Tool	Licence	Self-hosting difficulty	Who it suits	Strengths
LibreChat	MIT	Moderate: Docker stack with MongoDB, search and a vector database, plus your API keys	Teams wanting one shared AI chat that works with several model providers	Familiar chat screen, OAuth2, LDAP and email login, agents, MCP tools, file chat, spend controls
AnythingLLM	MIT	Easy to moderate: one-click desktop app for one person, Docker for a team	Teams that mostly want to ask questions of their own documents	Document workspaces with permissions, built-in vector database options, agents, local or cloud models, embeddable chat widget
Ollama	MIT	Easy to install, but the model you can run depends on your hardware	Firms that want AI running entirely on their own machines	Runs open models on Mac, Windows and Linux, local API, works with LibreChat and AnythingLLM, GPU support

LibreChat: MIT. Now owned by ClickHouse, which says it stays MIT. Licence checked 31 October 2026.
AnythingLLM: MIT. Licence checked 31 October 2026.
Ollama: MIT. Covers the software only. Each model has its own licence. Licence checked 31 October 2026.

ChatGPT Team is now called ChatGPT Business, and a Standard seat costs $20 a person a month on an annual plan, or $25 monthly, with a two-seat minimum. Ten people on annual billing pay $2,400 a year, about £1,818. If most of your people only use it for the odd email, that's a full seat for occasional use.

Let's be straight about what's on offer here. These tools don't give you a free ChatGPT. They give you the app, and you bring the AI. That can be a paid service charged by use, or an open model running on your own hardware. Either way, you own the chat history and you can choose the model.

LibreChat

LibreChat is the closest thing to a self-hosted ChatGPT. It looks familiar, so your team won't need much training.

Proper team logins. Multi-user sign-in with OAuth2, LDAP or email, plus moderation and tools for controlling token spend.
Many models, one screen. Plug in cloud providers using your own API key, or local models through Ollama and other custom endpoints.
Agents. No-code assistants that you build and share with specific people.
Chat with files, through its RAG service, and a self-hostable code interpreter.
MCP support, for connecting tools and systems.

Under the bonnet it's a bigger stack than it looks. The default Docker setup runs MongoDB, Meilisearch for search, and PostgreSQL with pgvector for file search, alongside the app itself.

Worth knowing: ClickHouse bought LibreChat in November 2025. It says the project stays open source under MIT. So far that looks to be true, but I'd keep an eye on it.

AnythingLLM

AnythingLLM is built around one job: chatting with your own documents. Staff manuals, policies, product guides and the like go into workspaces, and people ask questions in plain English.

Two versions. A one-click desktop app for one person, and a Docker version for teams.
Team features in the Docker version: user management, invitations, workspace permissions and white-labelling. The desktop app is single-user.
A wide choice of models, including Ollama and LM Studio locally, or OpenAI, Anthropic, Azure OpenAI, Google Gemini and Mistral in the cloud.
Agents that can search your documents, browse the web or query a SQL database.
An embeddable chat widget, which could put a help bot on your own website.

If you want a staff handbook bot, this gets you there faster than LibreChat. If you want a general AI assistant for everyone, LibreChat feels closer to what people are used to.

Ollama

Ollama is a different sort of thing. It isn't a chat app for your team. It's the engine that runs open AI models on your own machine, and the other two can plug into it.

Easy to run. It installs on Mac, Windows and Linux, and there's an official Docker image.
Lots of open models, including Gemma, DeepSeek, Qwen and others in its library.
Private by default when run locally. Ollama says it doesn't see your prompts or data in that mode.

The hardware is what matters. The Gemma 4 downloads run from around 5 GB to 20 GB, and that model needs to fit in memory to work well, ideally on a GPU. Ollama supports NVIDIA, AMD and Apple graphics. For a whole team using it at once, you're looking at a proper GPU server, not your spare office PC.

Two cautions. Ollama listens on the local machine only by default, and its docs don't describe a login for the local API, so don't expose it to the internet without something in front. And it now offers cloud-hosted models too, so if you want everything to stay local, you can turn those off with OLLAMA_NO_CLOUD=1.

Which one?

My pick is LibreChat, connected to a pay-as-you-go AI provider. Your team gets the top models, you pay for what's used, and you can add open models later. The main drawback is that you swap a fixed seat price for a bill based on usage, and you'll have to keep an eye on it.

A general AI assistant for the team: LibreChat.
Questions about your own documents: AnythingLLM.
Nothing leaves the building: Ollama, with one of the other two in front of it.

What it costs

The tools below are free, but the AI isn't. You either pay an AI provider per use, or buy hardware capable of running open models.

ChatGPT Business

ChatGPT Business Standard seat: £15.15 per user a month, billed annually (converted from $20 at the European Central Bank reference rate on 2 October 2026). Checked 31 October 2026 (source).
ChatGPT Business Premium seat: £75.75 per user a month, billed annually (converted from $100 at the European Central Bank reference rate on 2 October 2026). Checked 31 October 2026 (source).

Self-hosted, run for you

No per-user fees. Adding people doesn't add licence costs.
Setup: a one-off fee to set it up and move your data across.
Hosting and care: a fixed monthly fee covering every app on your server.
I'll quote once I know what you need.

Paid tool prices exclude VAT unless stated.

The UK angle

ChatGPT Business is fine for most small firms. OpenAI says Business data isn't used for training by default. If that was your main worry, it may already be answered.
Self-hosting the app doesn't keep everything here. With LibreChat and a cloud API, your chat history is on your server, but each prompt still goes to the AI provider. Only a local model keeps the lot in-house.
Staff still need rules. Whichever tool you pick, UK GDPR applies to what people paste in. A short policy on customer and staff data does more good than any tool choice.
UK data residency exists, but check it. OpenAI offers it for Enterprise, Edu and API customers. I couldn't confirm it for Business.

Honest drawbacks

Open models aren't ChatGPT. They're good and getting better, but on a typical budget they won't match the best paid models.
GPUs cost real money, whether you buy them or rent them. For a small team, pay-per-use is usually cheaper.
You miss out on OpenAI's own extras, such as its newest features, which tend to arrive first in its own app.
Moving parts. LibreChat's stack is several services, each of which needs updates and backups.
Usage bills can surprise you, so set the spend limits.
Model licences vary. Ollama is MIT, but each model has its own terms, so check them before commercial use.

If you want AI inside your own systems, such as answering from your own data or drafting from your own records, the team at Dev Partners can help build it.

Open-source alternatives to ChatGPT Business