6 Best Self-Hosted ChatGPT Alternatives

*Open WebUI uses an open-source-style license with a branding clause — fine for personal and most internal use.

The six, tested

Pair it with Ollama as the model backend and you get the closest thing to "ChatGPT, but it's yours": conversation history, model switching, web search plugins, image input with vision models, user accounts. Install is genuinely one Docker command, and updates are painless.

In our lab: an 8B model (quantized) idles happily inside 6–8GB of VRAM and responds fast enough that you stop noticing it's local. Where it falls over: you're limited by the models your hardware can run — don't expect frontier-model reasoning from an 8B.

The most faithful ChatGPT interface clone of the group, MIT-licensed, with real multi-user support. Its superpower: one interface for everything — local models via Ollama, plus OpenAI, Anthropic and other cloud APIs with your own keys. Great "one door for the whole household/team" setup.

In our lab: setup is Docker Compose with a config file — a step up in effort from Open WebUI, worth it for the account system. Where it falls over: configuration has a learning curve; overkill for a single user.

An open-source desktop app: download, install, pick a model from the built-in library, chat. No Docker, no terminal, runs fully offline. The model library shows you what will fit on your machine before you download.

Where it falls over: it's single-machine and single-user by design — this is a personal app, not a server you share.

If your real goal is "ChatGPT that knows my files," start here. Drop in PDFs, docs and websites, organize them into workspaces, and chat against them with a local model. RAG that normally takes an afternoon of Python is built in.

Where it falls over: as a plain chat interface it's less polished than Open WebUI — its value is the document pipeline.

Built for ordinary hardware: optimized to run smaller models on CPU, no GPU required. On a modern laptop, small models are perfectly usable for drafting and Q&A. Also does local document chat.

Where it falls over: CPU inference is slow with bigger models, and the model selection skews small. It's the "this old machine is what I've got" option — and it's good at that.

The most polished desktop experience here: excellent model browser, performance tuning knobs, and a local API server so other apps can use your models. Free for personal use.

The caveat: it's closed source. If the whole point of self-hosting for you is auditability and control, that matters — which is why it's ranked last despite being genuinely good software.

Hardware reality check

What you can run is decided by VRAM, roughly:

• 8GB VRAM — quantized 7–8B models. Fine for chat, drafting, light coding help.
• 12–16GB VRAM — 13–14B models, noticeably smarter, and comfortable multitasking.
• 24GB VRAM — 30B-class models; this is where local AI starts feeling properly capable.
• 70B-class models — 40GB+ VRAM. For most people this means renting, not buying.

And if you get to the end of this page and conclude self-hosting is more project than you want — that's a valid answer. A cloud subscription is the right tool for plenty of people.

FAQ

Can a self-hosted model really replace ChatGPT?

For everyday chat, drafting, coding help and document Q&A — yes, genuinely. For frontier-level reasoning, cloud models are still ahead. The common pattern: local for private and routine work, a cloud API key for the hard stuff (LibreChat lets you do both in one interface).

Is it actually private?

With a fully local setup (e.g. Open WebUI + Ollama, or Jan offline), prompts never leave your machine. That's the whole point.

What does it cost to run?

The software is free. Your costs are hardware you may already own, electricity, or cents-per-hour GPU rental for big models.