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Google AI Edge Gallery lets you download compatible open AI models and run them on your phone. It is available for Android 12 and later and iOS 17 and later, with model downloads needed before offline use. It is best understood as an experimental local-AI playground—not an offline version of Gemini or a guaranteed replacement for a cloud assistant.
What Google AI Edge Gallery is—and isn’t
Google AI Edge Gallery is an open-source mobile app for trying generative AI models directly on a phone. It uses Google AI Edge technologies, including LiteRT and LiteRT-LM, to run compatible models locally. The project is aimed at developers, AI enthusiasts and curious users who want to test on-device AI without building a separate app. The project repository currently highlights support for models including the Gemma family.
That does not mean the app runs Google’s cloud Gemini service offline. Gallery is a model playground: you choose a compatible model, download it, and use the capabilities that model supports. “On-device” means the model processes an input on the phone; “offline” generally means you can use that already-downloaded model without a network connection. It does not mean every part of setup or every optional feature works without internet.
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1Clear out junk files and repair common Windows errors2Scan for outdated or missing drivers - takes under a minute3Repair Windows errors before they cause bigger problemsThe project describes itself as experimental and in active development. Its features, model list and platform behavior can change between releases, so treat it as a useful way to explore local AI rather than a finished, uniform assistant. Check the current repository for release details.
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Availability and requirements
- Android: Android 12 or later. Google Play is the usual installation route; the project also publishes APK releases on GitHub.
- iPhone and iPad: iOS 17 or later, through the App Store listing reviewed for this guide.
Older wording in the project wiki describes iOS as “coming soon.” That conflicts with the current App Store listing and newer project information; use the current store listing for availability. Do not assume that Android and iOS have the same model choices, accelerators, features or performance. The operating-system minimum is an installation floor, not a promise that a particular model will run comfortably.
What you can try
- AI Chat: Have a multi-turn conversation with an installed local language model. Thinking Mode is listed for supported models, beginning with the Gemma 4 family; availability depends on the app release and selected model.
- Ask Image: Provide an image from the camera or photo library and ask a compatible multimodal model to describe or analyze it. This is image understanding, not necessarily image generation.
- Audio Scribe: Try transcription or translation of recordings with compatible local models. Results and language coverage depend on the model; do not assume cloud-service accuracy or universal real-time support.
- Prompt Lab: Test single-turn prompts and adjust parameters such as temperature and top-k. It is particularly useful for comparing model behavior.
- Agent Skills: Try modular workflows or tools, with examples involving services such as Wikipedia and maps. These are experimental extensions, and some may need network access.
- Mobile Actions and Tiny Garden: Explore experimental action-oriented demonstrations, including device-control workflows and a small natural-language game based on a FunctionGemma 270M fine-tune. Supported actions and permissions can vary by platform.
- Model management and benchmarking: Browse, download, switch between and remove models, and measure behavior on your own device. The app can show metrics such as time to first token, prefill speed, decode speed and latency.
Not every model supports every task. For example, an image or audio workflow needs a compatible model and modality support; installing a text model alone does not add image understanding or transcription.
Install the app and run a model
Android from Google Play
- Open Google Play and search for Google AI Edge Gallery. Confirm the developer listing is Google LLC/Research at Google.
- Install and open the app, then choose a capability such as AI Chat or Ask Image.
- Select a compatible model and tap Download.
- If prompted, sign in to Hugging Face and accept any model-specific license terms. Some models may be gated.
- When the download finishes, tap Try It and run a simple prompt.
Use the Google Play listing rather than an unofficial copy.
Android from the official GitHub APK
If Play Store access is unavailable or unsuitable, download the APK from the project’s official GitHub releases. Open it from Downloads and approve Android’s unknown-source installation prompt if shown. Avoid APKs from unrelated third-party sites.
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For a computer-based install, the official guide documents this command for the testing APK:
adb install -t ai-edge-gallery.apkThis requires USB debugging and an Android device connected to the computer. See the official getting-started guide for context.
iPhone or iPad
- Open the App Store and find Google AI Edge Gallery; check that you have the official listing.
- Install the app, choose a capability and a compatible model, then download the model while connected.
- Once the download has completed, try the model. You can then test whether that task works without a connection.
Availability can vary by region. The iOS steps and model options are not necessarily identical to Android. See the App Store listing for current availability in the United States.
Choosing and managing models
Choose by task first, then by the demands your phone can handle. A compatible model must support the modality you need, and model size, quantization and device hardware all affect the experience.
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- Smaller models generally require less storage and memory and may respond faster, but can be less capable.
- Larger models can be more capable, but may take more space and run more slowly or generate more heat.
- Quantized models can reduce resource demands, with potential trade-offs in output quality.
There is no single model-size figure that stays reliable across versions: downloadable variants and files can change. Check the model entry and available storage before starting a download. The model-management guide explains the general flow: expand a model entry, tap Download, then use Try It after installation. Downloads can continue in the background according to the guide. Remove installed models from the model-selection screen when you need space.
Importing a custom model on Android
For developers testing a LiteRT-compatible model, the current wiki describes importing a .litertlm file. One way to transfer it to the phone is:
adb push /path/to/model.litertlm /sdcard/Download/Then open Gallery, tap the + icon, choose the file, configure the available parameters and modality or CPU/GPU options, and tap Import. Options depend on the release. Follow the current import guide; older instructions refer to a different .task extension, which should not be treated as interchangeable with .litertlm.
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Does it really work offline?
For local inference, usually yes—after the app and required model are on the device. A practical test is to install the app, download a model, run a prompt once, enable airplane mode, and try again. If it fails, confirm the model finished downloading, the selected capability has a compatible installed model, and the feature is not calling an online service.
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Connectivity may still be required to:
- Install or update the app, browse model listings, and download models.
- Sign in to Hugging Face or accept license terms for a gated model.
- Use skills or workflows that retrieve information from Wikipedia, maps, MCP or another remote service.
- Get current web information, which a local model cannot fetch on its own.
Google AI Edge describes inference as on-device and says a network connection is not required once the model is loaded. That is a statement about local model execution, not a guarantee that every app feature is network-free. The overview and FAQ cover the distinction.
Independent reader supportYour contribution helps us test, update, and keep practical guides available for everyone.Performance, storage, heat and battery
Two phones that meet the same OS minimum can deliver very different results. Available memory, free storage, CPU/GPU or neural-accelerator support, model size and quantization all matter. A model may install but still be frustratingly slow on a particular phone. CPU execution can be slower than a supported accelerator, but changing CPU/GPU settings is not guaranteed to improve performance on every device.
Use Gallery’s benchmark results as a measure of your own phone and model, not as a prediction for every Android device or iPhone. Metrics such as time to first token, prefill speed and decode speed describe different parts of a run; they are not a universal quality score. Sustained local inference can increase battery use and device temperature, as the phone is doing the computation itself. Leave storage headroom, try a smaller model, and let the device cool if performance drops during extended use.
Privacy: what local means
When a model handles a prompt, image or recording locally, the task does not need to be sent to a cloud model for inference. That can be valuable for offline use and for reducing exposure of input content to remote AI services. But local inference is not the same as “the app never connects to the internet.” Downloads, authentication, updates and network-connected skills can involve external services.
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Review camera, photo-library, microphone and other permissions before using related features. Store privacy disclosures are supplied by developers and can change. At the time represented by the reviewed Google Play listing, it reported no data shared with third parties and listed app activity and app information/performance among possible data types collected; check the current listing rather than treating that disclosure as permanent. Local models can also produce incorrect or biased answers. Keep device security and careful handling of sensitive data in place.
Troubleshooting
A model will not download
Check your connection and available storage. If the model is hosted behind a gate, complete Hugging Face sign-in and accept its license terms. The listing may also be temporarily unavailable. Consult the official FAQ if the download still fails.
The app crashes or a model fails to start
Restart the app, check for an update from the official store or repository, and try removing and downloading the model again. A smaller model may work better; closing memory-intensive apps or restarting the phone can also help. If the problem persists, report reproducible steps with your phone model, OS and app versions, model name and error message, as the official FAQ recommends.
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Responses are too slow
Try a smaller or more heavily quantized model, use text-only when image or audio support is unnecessary, shorten the prompt, or use a smaller input image. Close background apps and let the phone cool. If the app offers CPU/GPU choices, compare them on your device rather than assuming one is always faster.
It works online but not offline
Confirm the model download completed and that the chosen capability has an installed compatible model. Check whether an Agent Skill or other workflow needs a network service, whether the app is trying to authenticate or refresh model information, and whether your request depends on current web data.
Who should try it?
Gallery is a good fit if you want to explore local AI, test open models on your own hardware, or run selected tasks without a connection after setup. It is less suitable if you expect cloud-level reasoning, guaranteed high-quality transcription or image analysis, current web answers, or a polished assistant that controls every phone function. It also demands storage and patience: experimental software and phone-dependent performance are part of the bargain.
The useful promise is not that one app makes every model fast, private in every respect or equivalent to Gemini. It is that Gallery makes it easier to install compatible models, try local tasks and see how they behave on your own phone.
Quick Recap
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