LM Studio has become a commonly used application for running local LLM models. It's easy to use, with a well-polished user interface. You can set up and run any AI model in just a few clicks—even if you've never used a terminal before. It's one of the best tools if you want to enjoy the benefits of a local LLM model.
But even though LM Studio is free to use, it's not open source. Some of its components, especially the command-line tools, have open licenses, but the application itself is proprietary software. For a tool that could easily sit at the heart of a local AI workflow, facing the risk of license changes whenever parent companies want is a risk many aren't comfortable with, and that's where Jan comes in .
Why is Jan a real alternative to LM Studio?
Jan, an alternative to LM Studio, is a desktop application that lets you run LLM models completely offline — very similar to LM Studio, but not only is it completely free, it's also open source, with all the source code available on GitHub. There are no licensing surprises, no proprietary software restrictions, and no minor terms you need to worry about.
The interface is very similar to ChatGPT , which can be good or bad depending on your preferences. However, if you're new to the concept of local LLM, it's familiar, clean, and easy to use. Jan was created to make local AI accessible to everyone, so the UI design mimicking ChatGPT isn't accidental. You'll have a chat window, a modeling center, and a settings page that doesn't require developer expertise to understand.
If you're switching from LM Studio, the model library will also feel familiar. You can browse and download popular open-source models like Llama , Gemma, Mistral, Qwen, DeepSeek , and many more directly from within the application. Models are also tagged to let you know whether they work well on your hardware, or whether they're too demanding to handle.
Performance, although depending on the model you're using, is quite similar to LM Studio. Token usage isn't significantly different from LM Studio either, and the inference engine is essentially the same. You also get built-in extensions in case you want to expand the application's functionality.
The privacy benefits are truly significant.
Local models, no cloud needed, no surprises.
Running AI locally has already been a privacy-focused option; however, using Jan allows you to take it a step further. Everything from your preferences, chat history, model parameters, and the model itself is on your machine. No account creation, no worries about telemetry data, and no reliance on the cloud. You can have a completely separate AI user experience from the network if you wish.
Two drawbacks to this approach are, first, you are limited by the AI models your hardware can run, and second, the open-source LLM models you can download and run aren't always as good as online models. There are tasks where you should use a local LLM model, but it can't do everything.
Jan allows you to overcome this by supporting remote APIs such as OpenAI, Anthropic, Claude, and many others if you want cloud access to their respective models. This method doesn't require you to choose between the two. The default is local (and private), but you always have the option to select a cloud-based model when the job requires it.
Jan quietly became the default alternative to LM Studio.
There aren't many reasons to switch from LM Studio to Jan. There's virtually no relearn time, and most of your models and data will migrate smoothly. The difference lies in ownership of your local AI stack. With Jan, you have complete control, and there won't be any sudden changes or license changes to confuse you.
In everyday use, Jan accomplishes everything LM Studio does, except it offers the peace of mind of having software you truly control. You still get all the necessary control and advantages, without any of the potential hassles.