Run AI on your own machine
Best local AI tools in 2026: 5 tools compared
5 tools · Updated Sep 6, 2026
Three reasons to run a model on your own computer. Privacy, because nothing has to leave the machine — a 2026 audit found no telemetry on Ollama's local inference. Cost, because there is no per-token bill: the hardware is the price, and you have already paid it. And offline, because a model sitting on your disk does not care whether the network is up. The thing to sort out before choosing is that these five tools do two different jobs. A runner downloads the model weights and does the actual inference — Ollama at the command line, LM Studio and Jan as desktop apps you can click. A front end is the chat window: Open WebUI and AnythingLLM give you conversations, accounts, documents and RAG, but neither ships a model of its own. You point them at a runner, or at a cloud model whose key you supply. People routinely install a front end, find that nothing answers, and conclude local AI is broken, when what is missing is the engine underneath. The other thing worth knowing early is that hardware, not licensing, is what stops most people: a review puts LM Studio at 16GB of RAM minimum with 32GB recommended, Jan wants 8GB or more free, and model files run from 2GB to over 100GB.
Side by side
| Tool | Best for | Free tier | From |
|---|---|---|---|
| Ollama | Technical users comfortable with a terminal who want free, private inference on hardware they already own. | The local app is free and unlimited on your own hardware. The cloud free tier is separate: one concurrent request, basic models and starter credits. | from $20/month |
| LM Studio | Beginners and non-technical users who want a graphical way to explore local models without touching a terminal. | Local inference is unlimited and LM Link covers up to five devices. Cloud models need paid credits, with no free allotment stated. | Free |
| Jan | Privacy-focused individuals who want a ChatGPT-shaped desktop app running on their own machine. | Free with no caps at all, and no paid tier to move up to — the pricing page 404s because there is nothing to price. | Free |
| Open WebUI | Teams and individuals who want a full-featured, multi-user, self-hosted ChatGPT alternative with RAG and SSO. | No functional or user cap while the original branding is intact. Removing the branding above 50 end users in any rolling 30 days is what needs an enterprise licence. | Free |
| AnythingLLM | Individuals and small organisations who want private document chat without assembling a stack themselves. | Self-hosting is functionally unlimited: no stated limits, bounded by your own hardware and the model key you bring. | from $50/month |
How we picked
Four criteria. Each is free to start: Ollama, Jan, Open WebUI and self-hosted AnythingLLM cost nothing, and LM Studio is free locally for personal and internal business use. Each runs models on hardware you control. Each publishes what it is licensed under, which here is not a formality — Ollama and AnythingLLM are MIT, Jan is Apache 2.0, LM Studio is proprietary, and Open WebUI has been BSD-3 plus a branding clause since April 2025. And each is alive: Ollama at 180,325 GitHub stars, Open WebUI at 151,151, AnythingLLM at 65,700 and Jan at 44,366, all pushed within days of 6 September 2026. Prices come from each vendor's own page, read on 6 September 2026. We have not tested them hands-on.
The tools
Ollama
from $20/monthThe default way to run models locally, driven from a terminal. Free and unlimited on your own hardware; the 2026 cloud tier is separate.
LM Studio
FreeThe graphical answer to Ollama: download and chat with local models by clicking. Free for personal and internal business use, and proprietary.
Jan
FreeA free, Apache 2.0 desktop app that works like a private ChatGPT running offline. No paid tier exists — the pricing page 404s.
Open WebUI
FreeA self-hosted, multi-user ChatGPT-style web interface for models you supply. Free to run as-is; the 2025 licence protects its branding.
AnythingLLM
from $50/monthSelf-hosted chat with your own documents, MIT-licensed and functionally unlimited on your hardware. The managed cloud starts at $50 a month.
Which one should you start with?
Start with LM Studio if you never open a terminal. It is a desktop app: browse a catalogue, download a model, chat with it in a window, free for personal and internal business use. Start with Ollama instead if a terminal is comfortable — the same job, plus an OpenAI-compatible local API that the front ends here can point at. Either way, run one model and confirm it answers before you add anything else. Then, when you want to chat with your own files rather than with the model's memory, put AnythingLLM on top. Leave Open WebUI until several people need to share one instance through a browser, and read its licence before you deploy.
Questions people actually ask
- How much RAM do I need?
- Two of these five tools state a number. A review of LM Studio puts the minimum at 16GB with 32GB recommended, and a review of Jan says it wants 8GB or more free. Ollama, Open WebUI and AnythingLLM publish no figure we could verify, so treat those two as the working floor. Budget disk as well as memory: model files run from 2GB to over 100GB.
- What is the difference between a runner and a front end?
- A runner loads the model weights and produces the answer. Ollama, LM Studio and Jan all do that. A front end is the interface around it — conversations, accounts, documents, RAG — and ships no model of its own. Open WebUI and AnythingLLM are front ends. Each needs a model, either from a runner you host or from a cloud provider whose key you supply.
- Which of these is genuinely open source?
- Ollama and AnythingLLM are MIT — permissive, with no branding or use restrictions attached. Jan is Apache 2.0, confirmed by reading its LICENSE file rather than GitHub's label, which says "Other". Open WebUI changed on 19 April 2025 from plain BSD-3 to a BSD-3 base plus a mandatory branding-protection clause, and that drew documented backlash. LM Studio is proprietary: its terms describe the source code as trade secrets.
- How much of this is free?
- Locally, all five. Ollama is free and unlimited on your own hardware, Jan has no paid tier at all, self-hosted AnythingLLM has no stated functional limits, Open WebUI is free to use as-is, and LM Studio's local tier is free for personal and internal business use. The money sits in the layers above: Ollama and LM Studio sell cloud, AnythingLLM sells hosting from $50 a month, and Open WebUI sells an enterprise licence for white-labelling.
- Does running locally really keep my data private?
- It removes the obvious leak by design, since inference happens on your machine — a 2026 privacy audit found no telemetry on Ollama's local inference. Two caveats. Anything routed to a cloud tier leaves the machine by definition: Ollama's cloud, LM Studio's credits, a model key inside AnythingLLM. And Jan's MCP connections to Gmail, Notion or Slack reach the network too.
Research-compiled, not hands-on tested. Compiled from official docs, the vendor's pricing page and community reviews as of Sep 6, 2026. We haven't tested it hands-on yet.