Ollama vs LM Studio vs Jan in 2026: Which Local AI App Should You Use?

If you want an AI assistant that runs on your own laptop, with your documents never leaving the machine, you will almost certainly end up choosing between three free apps: Ollama, LM Studio and Jan. A year ago the choice was simple. Ollama was the quiet engine that developers ran in the background, LM Studio was the friendly desktop app with a model browser, and Jan was the open-source alternative that looked like ChatGPT.

In 2026 all three blurred. Ollama sells cloud plans. LM Studio's website now leads with an agent called Bionic. Jan added cloud providers, web search and tool connections. The local part still works in every one of them, but you now have to know where the cloud switch is.

What changed in 2026

Ollama went local and cloud. Its homepage now reads "Run AI models locally and in the cloud". The free tier still runs models on your own computer and includes some starter credits for cloud models; Pro costs $20 a month (with $60 of usage credits) and Max $100 a month, according to Ollama's pricing page. Cloud models are marked with :cloud at the end of their name, which is the detail to watch. On Apple Silicon Macs, version 0.40 (October) runs supported models on Apple's MLX engine by default, which is noticeably faster. In July the company announced an $88 million funding round and said it serves 8.9 million developers.

LM Studio became Bionic, mostly. In July LM Studio launched Bionic, "the AI agent for open models", which writes documents, runs code and can control your computer. The homepage now promotes Bionic first, with a $20-a-month Bionic+ plan for US-hosted cloud models that LM Studio says keep zero data. The classic LM Studio app (version 0.4.26 at the time of writing) is still free, still on the download page, and still free for use at work, a change LM Studio made in July 2025. Not everyone is happy: a popular r/LocalLLaMA thread in September was titled "Why is LM Studio making LM Studio so difficult to download?"

Jan stayed open source and added features. Jan, built by Menlo Research, is licensed under Apache 2.0 and reached version 0.8.6 on 9 October. This year it added native MLX on Mac, file uploads in Projects, MCP tool connections with an approval prompt, and built-in web search. You can also plug in ChatGPT, Claude or Gemini with your own API key, which is convenient and, again, means not everything you type stays local.

Side by side

Prices and versions as listed on each company's site on 9 October 2026. Check before you rely on them; all three ship updates every few weeks.

Choose Ollama if other apps will do the talking

Ollama's strength is that almost everything supports it. Document chat apps such as AnythingLLM, agent tools, coding assistants and home-automation projects all list Ollama as a provider. Install it once, download a model, and those apps can use it. That is why our private AI assistant on Windows guide pairs Ollama with AnythingLLM, and why our Claude Code with Ollama walkthrough starts there too.

It is less pleasant if you want to explore models by hand: settings are fewer and much of the power sits in the command line. And because cloud and local models now share one list, check the model name before you send anything private. A name ending in :cloud runs on Ollama's servers. Ollama says prompts are never stored or trained on, but that is a promise, not a property of your laptop.

Choose LM Studio if you want to see and tune what is running

Classic LM Studio remains the easiest way to search for a model, see whether it will fit in your computer's memory, download it, and adjust settings such as context length without touching a terminal. It runs a local server that speaks the same language as the OpenAI and Anthropic APIs, so tools built for those can point at your own machine instead; LM Studio published a guide to using local models in Claude Code in January.

Bionic is a different product: an agent that edits files, runs commands and offers paid cloud models. It may suit you, but if you came for a private chat app, download "LM Studio" rather than "Bionic" from the download page. If you do try Bionic, the same agent rules apply as anywhere else; our AI Agents for Everyday Use course covers permissions and approvals.

Choose Jan if you want open source and a familiar chat window

Jan looks and feels like ChatGPT, runs fully offline once a model is downloaded, and is open source under Apache 2.0, so anyone can inspect the code. Projects with uploaded files, MCP tools that ask before they run, and optional web search make it a reasonable everyday assistant. It suits people who want one app for both local models and, occasionally, a cloud model through their own API key.

The trade-off is a smaller ecosystem than Ollama and fewer tuning options than LM Studio. Jan's site also lists a "Memory" feature as coming soon. Remember that anything you route to a cloud provider through Jan follows that provider's rules, not Jan's.

Will it run on my computer?

Memory matters more than anything else. As a rough rule of thumb for the common 4-bit versions of models:

• 8 GB of RAM: small models (around 3 to 4 billion parameters). Fine for rewording, simple questions and short summaries.
• 16 GB: models of around 7 to 14 billion parameters. Good everyday quality for drafting and document questions.
• 32 GB or more (or a graphics card with 16 GB+): models around 30 billion parameters, such as the new 30B open models released this summer, which handle longer and more complex tasks.

Apple Silicon Macs use their shared memory for AI, which is why they punch above their weight here. On Windows, an NVIDIA graphics card helps a lot. All three apps show or estimate whether a model will fit; if it does not, it will either refuse to load or run very slowly. Even a well-chosen local model is usually behind the best cloud models on hard reasoning, so match the job to the machine.

How to keep "local" actually local

• Check the model name or label every time. Cloud models in Ollama end in :cloud; in LM Studio Bionic and Jan, cloud providers are listed separately from local models.
• Turn off web search for private work. A search query leaves your machine even if the model does not.
• Test it offline. Switch off Wi-Fi and ask a question. If it still answers, that model is genuinely local.
• Be careful with tool connections. MCP servers and plugins can read files and reach the internet. Our explainer on what an MCP server is covers what to check before installing one.
• Keep the local server private. All three can serve models to other devices. Leave that off unless you need it, and never expose it to the open internet.

The short version

For most people starting out: Jan if you want an open-source chat app, LM Studio (the classic app) if you want to try lots of models and see what fits, and Ollama if you plan to connect other tools or agents. Many people end up with two of them installed, and that is fine; each keeps its own copy of the models, so watch your disk space.

If you are new to all of this, our free course Private AI on Your Own Computer walks through choosing hardware, picking a first model, chatting with your own documents and the privacy checks above, one short lesson at a time.

Quick questions

Are Ollama, LM Studio and Jan free?

Yes, for running models on your own computer. Ollama and LM Studio also sell optional cloud plans; Jan lets you add paid cloud providers with your own API key.

Is a local model as good as ChatGPT or Claude?

Usually not for the hardest tasks. For drafting, summarising and questions about your own documents, a good 7–14 billion parameter model on a 16 GB machine is often enough.

Do I need the internet?

Only to install the app and download a model. After that, local models work offline.

Which is best for a Mac?

All three now use Apple's MLX engine, which makes a real difference on Apple Silicon. Choose by the interface you prefer.