Google to give app devs access to Gemini Nano for on-device AI
AI apps are coming
Google to give app devs access to Gemini Nano for on-device AI
New APIs for Google's ML Kit will let developers plug into the on-device AI model.
Ryan Whitwam
–
May 16, 2025 2:15 pm
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16
Credit:
Thomas Fuller/SOPA Images/LightRocket via Getty Images
Credit:
Thomas Fuller/SOPA Images/LightRocket via Getty Images
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The rapid expansion of generative AI has changed the way Google and other tech giants design products, but most of the AI features you've used are running on remote servers with a ton of processing power. Your phone has a lot less power, but Google appears poised to give developers some important new mobile AI tools. At I/O next week, Google will likely announce a new set of APIs to let developers leverage the capabilities of Gemini Nano for on-device AI.
Google has quietly published documentation on big new AI features for developers. According to Android Authority, an update to the ML Kit SDK will add API support for on-device generative AI features via Gemini Nano. It's built on AI Core, similar to the experimental Edge AI SDK, but it plugs into an existing model with a set of predefined features that should be easy for developers to implement.
Google says ML Kit’s GenAI APIs will enable apps to do summarization, proofreading, rewriting, and image description without sending data to the cloud. However, Gemini Nano doesn't have as much power as the cloud-based version, so expect some limitations. For example, Google notes that summaries can only have a maximum of three bullet points, and image descriptions will only be available in English. The quality of outputs could also vary based on the version of Gemini Nano on a phone. The standard versionis about 100MB in size, but Gemini Nano XXS as seen on the Pixel 9a is a quarter of the size. It's text-only and has a much smaller context window.
Not all versions of Gemini Nano are created equal.
Credit:
Ryan Whitwam
Not all versions of Gemini Nano are created equal.
Credit:
Ryan Whitwam
This move is good for Android in general because ML Kit works on devices outside Google's Pixel line. While Pixel devices use Gemini Nano extensively, several other phones are already designed to run this model, including the OnePlus 13, Samsung Galaxy S25, and Xiaomi 15. As more phones add support for Google's AI model, developers will be able to target those devices with generative AI features.
The documentation is available for developers to peruse now, but we expect Google to fling the API doors open at I/O. The company has already confirmed an I/O session called "Gemini Nano on Android: Building with on-device gen AI." The description promises new APIs to "summarize, proofread, and rewrite text, as well as to generate image descriptions," which sounds exactly like what the new ML Kit APIs can do.
An important piece of the AI puzzle
App developers interested in adding on-device generative AI features on Android are currently in a tough spot. Google offers the AI Edge SDK that can provide access to the NPU hardware for running models, but these tools are experimental and only work on the Pixel 9 series currently. It's also limited to text. Both Qualcomm and MediaTek offer APIs for running AI workloads, but features and functionality vary by device, which makes it risky to rely on them for a long-term project. And running your own model requires intimate knowledge of generative AI systems. The new APIs should make implementing local AI comparatively quick and easy.
Despite the limited functionality of an on-device model, this is an important part of how AI could become more helpful. Most people would probably prefer not to send all their personal data to a remote server for AI processing, but an on-device model can parse that information in a more secure way. For example, Google's Pixel Screenshots sees all your screenshots, but all the processing happens on your phone. Similarly, Motorola summarizes notifications locally on the new Razr Ultra foldable. On the other hand, its less capable base model Razr sends notifications to a server for processing.
The release of APIs that plug into Gemini Nano could provide some much-needed consistency to mobile AI. However, it does rely on Google and OEMs to collaborate on support for Gemini Nano. Some companies might decide to go their own way, and there will be plenty of phones that don't have enough power to run AI locally.
Ryan Whitwam
Senior Technology Reporter
Ryan Whitwam
Senior Technology Reporter
Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he's written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards.
16 Comments
#google #give #app #devs #access
Google to give app devs access to Gemini Nano for on-device AI
AI apps are coming
Google to give app devs access to Gemini Nano for on-device AI
New APIs for Google's ML Kit will let developers plug into the on-device AI model.
Ryan Whitwam
–
May 16, 2025 2:15 pm
|
16
Credit:
Thomas Fuller/SOPA Images/LightRocket via Getty Images
Credit:
Thomas Fuller/SOPA Images/LightRocket via Getty Images
Story text
Size
Small
Standard
Large
Width
*
Standard
Wide
Links
Standard
Orange
* Subscribers only
Learn more
The rapid expansion of generative AI has changed the way Google and other tech giants design products, but most of the AI features you've used are running on remote servers with a ton of processing power. Your phone has a lot less power, but Google appears poised to give developers some important new mobile AI tools. At I/O next week, Google will likely announce a new set of APIs to let developers leverage the capabilities of Gemini Nano for on-device AI.
Google has quietly published documentation on big new AI features for developers. According to Android Authority, an update to the ML Kit SDK will add API support for on-device generative AI features via Gemini Nano. It's built on AI Core, similar to the experimental Edge AI SDK, but it plugs into an existing model with a set of predefined features that should be easy for developers to implement.
Google says ML Kit’s GenAI APIs will enable apps to do summarization, proofreading, rewriting, and image description without sending data to the cloud. However, Gemini Nano doesn't have as much power as the cloud-based version, so expect some limitations. For example, Google notes that summaries can only have a maximum of three bullet points, and image descriptions will only be available in English. The quality of outputs could also vary based on the version of Gemini Nano on a phone. The standard versionis about 100MB in size, but Gemini Nano XXS as seen on the Pixel 9a is a quarter of the size. It's text-only and has a much smaller context window.
Not all versions of Gemini Nano are created equal.
Credit:
Ryan Whitwam
Not all versions of Gemini Nano are created equal.
Credit:
Ryan Whitwam
This move is good for Android in general because ML Kit works on devices outside Google's Pixel line. While Pixel devices use Gemini Nano extensively, several other phones are already designed to run this model, including the OnePlus 13, Samsung Galaxy S25, and Xiaomi 15. As more phones add support for Google's AI model, developers will be able to target those devices with generative AI features.
The documentation is available for developers to peruse now, but we expect Google to fling the API doors open at I/O. The company has already confirmed an I/O session called "Gemini Nano on Android: Building with on-device gen AI." The description promises new APIs to "summarize, proofread, and rewrite text, as well as to generate image descriptions," which sounds exactly like what the new ML Kit APIs can do.
An important piece of the AI puzzle
App developers interested in adding on-device generative AI features on Android are currently in a tough spot. Google offers the AI Edge SDK that can provide access to the NPU hardware for running models, but these tools are experimental and only work on the Pixel 9 series currently. It's also limited to text. Both Qualcomm and MediaTek offer APIs for running AI workloads, but features and functionality vary by device, which makes it risky to rely on them for a long-term project. And running your own model requires intimate knowledge of generative AI systems. The new APIs should make implementing local AI comparatively quick and easy.
Despite the limited functionality of an on-device model, this is an important part of how AI could become more helpful. Most people would probably prefer not to send all their personal data to a remote server for AI processing, but an on-device model can parse that information in a more secure way. For example, Google's Pixel Screenshots sees all your screenshots, but all the processing happens on your phone. Similarly, Motorola summarizes notifications locally on the new Razr Ultra foldable. On the other hand, its less capable base model Razr sends notifications to a server for processing.
The release of APIs that plug into Gemini Nano could provide some much-needed consistency to mobile AI. However, it does rely on Google and OEMs to collaborate on support for Gemini Nano. Some companies might decide to go their own way, and there will be plenty of phones that don't have enough power to run AI locally.
Ryan Whitwam
Senior Technology Reporter
Ryan Whitwam
Senior Technology Reporter
Ryan Whitwam is a senior technology reporter at Ars Technica, covering the ways Google, AI, and mobile technology continue to change the world. Over his 20-year career, he's written for Android Police, ExtremeTech, Wirecutter, NY Times, and more. He has reviewed more phones than most people will ever own. You can follow him on Bluesky, where you will see photos of his dozens of mechanical keyboards.
16 Comments
#google #give #app #devs #access
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