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What is Google AI Edge Gallery?
Google AI Edge Gallery is an open-source showcase and playground for running open-weight AI models on mobile devices. It is aimed at people exploring on-device AI and developers looking for practical examples, rather than serving as a general-purpose hosted chatbot. Google introduced the project around Google I/O 2025 and later made it available in open beta through Google Play. In September 2025, Google reported 500,000 APK downloads in the app’s first two months. Google’s launch and availability announcement describes the project as a way to try models and inspect examples.
The current project documentation lists Android 12 and later, and iOS 17 and later. The app is still in beta, so availability and features may change; check the live store listing or project repository for the current release details.
What can you do in the app?
The Gallery combines model management with several ways to try local AI. Its current README lists:
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- AI Chat: converse with a selected model.
- Ask Image: provide an image and ask a model about it.
- Audio Scribe: transcribe audio locally using a supported model. Google’s September 2025 announcement introduced local Gemma 3n transcription; its reference to batch inference up to 30 seconds described the initial MediaPipe API, not a universal current app limit.
- Prompt Lab: experiment with prompts and model settings.
- Mobile Actions: see a model interpret natural-language instructions as device actions.
- Tiny Garden: use voice commands to trigger functions in a small game.
- Model management and benchmarking: download supported models, import custom models, and test performance.
Google’s February 2026 announcement says Mobile Actions and Tiny Garden use FunctionGemma, a 270-million-parameter model. The demonstrations show how small models can map instructions to functions; they are not evidence that every model can safely or reliably control every phone feature. Google’s iOS and demo announcement describes those examples.
Can Google AI Edge Gallery run offline?
Yes, for local inference: after a compatible model is installed, prompts can be processed by that model on the phone rather than sent to a cloud model service. That is the important meaning of the Gallery’s offline-AI claim. Discovering and downloading models is a separate step and requires network access to obtain the files.
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Some workflows can also involve an external service. Google’s May 2026 announcement describes experimental Android support for the Model Context Protocol (MCP) over Streamable HTTP. The model can reason and create a tool call locally, but an MCP server executes that request. The server may be on a home computer or in the cloud, so an MCP-powered action is not end-to-end offline. Google’s MCP announcement explains this boundary and also notes persistent chat history and local reminders.
Local inference is not a blanket privacy guarantee for every part of the app. Google Play’s developer-provided data-safety disclosure says no data is shared with third parties, while also listing app activity and app info and performance as categories the app may collect, and stating that data is encrypted in transit. Treat the model’s local processing and the app’s broader data practices as distinct questions; the store disclosure is the relevant place to check the current declaration. Google Play listing.
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Does AI Edge Gallery work on iPhone?
Yes. Google announced iOS availability in February 2026. The project currently lists iOS 17 or later as its software requirement. The iOS app provides access to the Gallery’s local-model experience, though model availability and performance can differ from Android. Consult the current repository and store listing for the exact build and supported features.
What phones support Google AI Edge Gallery?
The published minimums are operating-system requirements, not a promise that every supported phone has enough memory, storage, or processing capacity for every model. Android devices need Android 12 or later; iPhones need iOS 17 or later. Google Play cautions that performance depends on device hardware.
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Before choosing a model, consider these factors:
- Operating system: confirm the phone meets the applicable Android or iOS minimum.
- Storage and memory: model files occupy space, and running a model also requires working memory. Google’s LiteRT-LM overview lists Gemma 4 E2B at 2.58 GB; that is the model’s listed size, not a complete estimate of all app storage or runtime memory needs.
- Model capability: a compact model suited to function calling may not be equivalent to a larger conversational or multimodal model.
- Speed and latency: results depend on the phone, model, and runtime. A published speed on one device should not be treated as a forecast for another.
- Network dependency: local inference can work offline, but downloading models and using a remote MCP server require connectivity.
Can it run Gemma on my phone?
The Gallery supports Gemma models, and its current project README presents Gemma 4 support. Google’s LiteRT-LM overview features Gemma 4 E2B, listed at 2.58 GB, and reports GPU decode rates of 52 tokens per second on a Samsung S26 Ultra and 56 tokens per second on an iPhone 17 Pro. These are Google-published measurements from its benchmark setup for that model and those named devices—not independent tests, minimum hardware specifications, or speed guarantees for other phones. Google’s LiteRT-LM overview provides the model and benchmark details.
Google has also published a different example for FunctionGemma’s Mobile Actions use on a Pixel 7 Pro: 1,916 tokens per second for prefill and 142 tokens per second for decode. Prefill and decode are different stages, and this is a small function-calling model example, not a general chat-model result. It should not be compared directly with the Gemma 4 E2B decode figures as though both measured the same task. Google’s February 2026 post gives the FunctionGemma figures.
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How to get started
- Install the app: use the Android or iOS store route linked from the current project repository. Android users can also use APK releases listed there.
- Choose a listed model or import one: downloading a model requires an internet connection. Google’s developer guide says the app can import custom
.taskmodels as well as select from its supported model list. - Open the relevant tool: choose AI Chat, Ask Image, Audio Scribe, Prompt Lab, Mobile Actions, or Tiny Garden according to what you want to try.
- Adjust and test: in supported workflows, change parameters such as temperature and top-k, run prompts, and use the benchmarking feature to examine performance on your own device. Google’s AI Edge Gallery developer guide documents custom model and prompt workflows.
- Check whether a feature connects elsewhere: local model inference and server-executed tools are different paths. For MCP, identify the configured server and expect the tool request to leave the phone.
What the Gallery is—and is not
AI Edge Gallery is useful for exploring local model behavior, comparing how supported models perform on your own hardware, and seeing how developers can build mobile AI experiences. It does not make model downloads, every app workflow, or connected tools automatically offline. Its beta status, device-dependent performance, and separate network requirements matter more than a single benchmark or an “on-device” label.
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