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You can install LM Studio’s graphical desktop app on Ubuntu and use its Discover and Chat tabs to download and run a local AI model—without using the terminal for the main workflow. LM Studio’s stated Linux minimum is Ubuntu 20.04, but its documentation cautions that “Ubuntu versions newer than 22 are not well tested.” That means Ubuntu 24.04 meets the stated minimum, while neither 24.04 nor 26.04 is specifically confirmed as well-tested in the cited requirements.
What to know before installing on Ubuntu 24.04 or 26.04
LM Studio’s system requirements specify Ubuntu 20.04 or newer and support Linux on x64 and ARM64 (aarch64). The same page qualifies that baseline: “Ubuntu versions newer than 22 are not well tested.” Ubuntu 24.04 is above the minimum and within that less-tested category. Ubuntu 26.04 is also newer than Ubuntu 22, but the documentation does not name or confirm that release specifically.
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Treat the requirements as a stated minimum, not a guarantee that every later Ubuntu release will work. Check LM Studio’s live Linux download page before downloading: package formats and versions can change. At the time reflected by that page snapshot, it listed Linux AppImage and .deb packages, both at version 0.4.25.
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Visit the official Linux download page. Choose the package matching your computer’s architecture—x64 or ARM64 (aarch64)—and select an available format, such as AppImage or .deb if both are currently offered.
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Download the package and follow the current instructions shown by Ubuntu and the package. The official onboarding information does not specify a universal, shell-free sequence of file-manager clicks for opening each package type, handling executable permissions, or creating desktop integration, so those steps may depend on the format and your Ubuntu setup.
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Launch the LM Studio desktop application. The graphical desktop app is distinct from
llmster, LM Studio’s headless daemon, andlms, its command-line interface. For this GUI route, use the desktop app rather than following the headless or CLI installation path; see LM Studio’s explanation of LM Studio, llmster, and lms.
Download a model and start your first chat
Once the desktop app is open, the documented first-use flow is to find a model in Discover, download it, and then load it in Chat. Model discovery and downloads require an internet connection.
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Open Discover in LM Studio. Choose a curated model or search for one, then download it.
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Open Chat and open the model loader. Select the model you downloaded, or a model you previously sideloaded.
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Wait for the model to load, then start chatting. Loading allocates memory for the model’s weights and other parameters, so the model must fit the resources available on your computer.
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This sequence follows LM Studio’s Get started with LM Studio guide. Model size and available system resources affect which models can load; installing the app does not mean every model will fit or run well. LM Studio documents a resource-estimation option for its CLI, but it is not required for this graphical workflow; details are in the lms load documentation.
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Downloading the app and model files requires connectivity, but once the model files are on your computer, LM Studio says inference can run offline. Its documentation also lists document chat and local-server operation as available offline. If you need to obtain the model first, plan for an internet connection before disconnecting.
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Model files are stored locally, and the space they need depends on the models you choose. An external SSD is an optional place to keep model files if internal storage is limited; LM Studio does not require an external drive. Its lms ls documentation shows an example inventory of 47 models occupying 160.78 GB, but that is example output—not a typical collection size or a recommended drive capacity.
Optional: exposing LM Studio’s server beyond your computer
Running a local chat in the desktop app does not require making its server available to other devices. If you choose to expose the server on a network, LM Studio documents 127.0.0.1 as the default bind address. Binding beyond localhost makes the service reachable beyond that machine’s loopback interface; LM Studio recommends authentication for that case. See the server start documentation before changing network settings.
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