Preparing offline AI often means downloading more than one file. You may want a chat model, an image model, and speech recognition ready before a trip. Waiting for each one to finish before choosing the next turns setup into a task you have to watch.
OGAM (Off Grid AI Mobile) lets you queue model downloads and manage their progress in one place. Add the models you need, then inspect which are downloading, queued, paused, or complete. You can leave the download screen without cancelling the work.
The downloads need internet and enough free storage. After the models are ready, their supported local tasks can work offline. A queued item is waiting for its turn; it is not necessarily transferring bytes yet.
Choose the set before filling the queue
Start with the tasks you will actually use. One suitable chat model, one image model, and one speech-input model can be more useful than several large models you have not tried.
Check the displayed file sizes and device compatibility. Download size is different from working RAM: a completed file may still be too large to load on your phone.
If you want a prepared starting set, Settings → Storage → Auto Setup offers guided plans. If you want specific models, use Models and choose them individually.
The queue and guided setup are available in OGAM 0.0.111.
Add more than one download
- Open Models, find the first model, and start its download.
- Return to the catalog and start the next model you need.
- Repeat for the remaining model or voice-input package.
- Open the download-manager button in Models to inspect the outstanding work.
- Check each item's status rather than treating the total queue count as the number actively downloading.
OGAM admits work to available download slots and starts waiting items as slots become free. You do not have to stay beside the first item's progress bar to add the next one.
Some model packages contain more than one required file. Let the app finish the whole package before assuming the feature is ready.
Leave the screen, then check the result
The app's download service owns the work independently of the model-selection or Auto Setup screen. Navigating to another screen does not cancel the queue.
Android uses a foreground download service and can show a download notification. iOS uses its native background-download mechanism. The operating system still controls background execution and network access, so leaving the app is not a promise that every queued job will finish under every condition.
Keep a stable connection and allow the app to report progress. After returning, open the download manager and check the actual status. Do this before leaving the network you planned to use for setup.
Force-closing the app, losing connectivity, or running out of storage can interrupt the process. A persistent queue helps retain the work to be done; it does not make those conditions disappear.
Pause, resume, and retry deliberately
Use Pause or Resume where the item offers that control. Use Retry for a failed item after checking its reported error, free space, and connection.
Remove a queued item when you no longer need it. That prevents an unwanted large download from starting later. Keep the distinction between removing outstanding download work and deleting a model that already completed.
If progress seems stuck, check whether the item is actually queued. Waiting for a slot is different from an active transfer that has stopped receiving data.
Resuming also depends on the model's download provider and available partial file. Use the app's offered action instead of assuming every failed download can continue from the same byte.
Finish with a task, not only a green status
After the downloads complete, load the chat model and ask a short question. Try the other capability you plan to use, such as an image or a short transcription. Then repeat a suitable task with the network off.
That final check distinguishes “the file arrived” from “the model I need is ready for my phone.”
Get OGAM, queue a small set of useful models, and check their completed state in the download manager. Prepare the offline tasks once, without waiting at each individual download screen.
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