You want an AI assistant on your Linux computer. You also want your drafts, screenshots and questions to stay on that computer. Setting up a separate server for each kind of AI should not be the first task.
OGAD (Off Grid AI Desktop) now has a Linux beta that runs text, vision, image generation and voice locally. Install the app and download the models you need. Then use those local models without an account or an internet connection. Choose local models for this workflow; connected services have their own network requirements.
This guide covers v0.0.54-beta.108, a prerelease published on September 29, 2026. The documented Linux target is Ubuntu 24.04 or newer on x64. This is a core app release; the Linux package does not include Off Grid AI Pro. Release and supported platforms.
Download the Linux beta | Off Grid AI
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What can you do with local AI on Linux?
You can use one desktop app to work with text, ask about an image, create an image and use speech. Each task needs a suitable model. A downloaded chat model does not automatically supply an image generator or a voice.
| Your task | What you need | A useful first result |
|---|---|---|
| Rewrite a rough note | A local text model | A clearer paragraph you can edit |
| Understand a screenshot | A local vision model | An explanation of the visible information |
| Make an illustration | A local image model | A draft image from your description |
| Speak a question | A local transcription model | Your words in the chat input |
| Listen to an answer | A local speech model and prepared voice | Spoken playback of a short reply |
Suppose you are preparing a short project update. Paste your own rough notes into chat and ask for a summary. Add a screenshot if a visible error needs an explanation. Ask for a simple illustration for the update. These are separate tasks, but you can do them in the same app with local models.
You still check the output. A model can misread a screenshot, remove an important qualification or invent a detail. Local processing changes where the work happens; it does not remove the need to review it.
What do you need before you start?
Use the published x64 AppImage or amd64 .deb for Ubuntu 24.04 or newer. The release does not supply a Linux ARM package. Do not assume that every distribution is supported because it can run an AppImage.
The AppImage download is about 1.08 GB; the .deb is about 901 MB. Models are additional downloads. Leave room for the app, the models and their working files. Model download size is not the amount of RAM or GPU memory needed to run it.
You need internet for the initial downloads. An NVIDIA GPU is optional. Start with the app's normal setup before adding GPU components. You do not need Docker or a CUDA developer toolkit to use the installed app. Those tools appear in the source-build instructions because building the app is a different task. Installation documentation.
How do you get your first useful answer?
1. Install the Linux beta
Open the linked release and choose a Linux package. Use your system's package installer for the .deb, or give the AppImage permission to run as a program and open it. Keep the version in mind when comparing controls with older stable guides.
2. Configure local models
Open OGAD and use the setup flow. Settings → Setup & health also contains setup and component information. Review the proposed downloads and select Configure. Let the required downloads finish before disconnecting.
Use a model suited to your available memory. Starting with a smaller local model makes it easier to check the whole workflow. You can try a larger one after you have a working baseline.
3. Give it a real, bounded task
Open Chat and use a downloaded local text model. Paste a short note such as:
The desktop prototype is ready. We still need to test the export on Linux. Priya will check the labels on Thursday. Do not promise a release date yet.
Then ask:
Turn this into a three-bullet project update. Keep the open issue and the person responsible. Do not add facts or a release date.
Check that the answer preserves the Linux test, the owner and the uncertainty. Change the prompt if you want a different tone. This is a more useful first check than asking a model to tell you that it works.
4. Repeat the task offline
Once the model has loaded and answered, disconnect from the network and send another short local request. You should still receive an answer. Avoid web searches, remote models and connected tools in this check; those are separate workflows.
How do images and voice fit into the same app?
For image generation, select and download a local image model first. Start with one simple subject and a modest image size. For example: “A clean illustration of a small indoor herb garden, soft daylight, no text.” Review the result before increasing the image size or adding detail.
For voice input, prepare the transcription model and use the chat microphone. Check the transcribed words before you send them. This core chat feature does not mean the Linux release includes Pro system-wide dictation or meeting recording.
For spoken replies, use the Settings button in Chat to open Model settings. Choose Voice, select a local voice and wait for its files to be ready. Use Test voice before relying on playback. Speech has its own model resources; a working text reply alone does not prove that voice setup has finished.
The Linux release process tested local audio transcription and generated a speech WAV. It also checked the packaged image and speech runtimes. That supports the release's core scope; it is not a performance promise for every computer. Release build checks.
What if a model does not work well on your computer?
| What you see | What to check next |
|---|---|
| A request tries to download files offline | Reconnect and finish the required model or voice download |
| A large model fails to load | Try a smaller model and close other memory-heavy work |
| A selected GPU engine does not appear active | Reload the model and check the actual Now backend |
| Voice controls are present but silent | Wait for voice preparation, use Test voice, then check audio output |
| A Pro feature is absent | This Linux beta contains the core app; Pro is not bundled |
If you have an NVIDIA GPU, Settings → GPU performance offers an optional CUDA pack of about 5.88 GB. Install it, restart the app, then check the backend used by a real request. Other supported backends can still run without the pack; availability depends on the model type. Speech uses separate settings.
Start with one task you already need to finish
You do not have to download every model to make local AI useful. Rewrite one note, explain one screenshot or dictate one question. Keep the first setup small, check the result, then add another capability when you need it.
Download the Linux beta, configure a local model and give it a task from today's work.
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