Google Tensor brings private on-device AI to Pixel 10 phones

Google revealed the capabilities of its Tensor custom chip and built-in Tensor Processing Unit (TPU) at a special India I/O showcase, demonstrating how the Pixel 10 family will deliver powerful artificial intelligence that never requires an internet connection. The company emphasized that all processing happens directly on the device, ensuring complete data privacy.

New AI Models Optimized for Edge Processing#

The centerpiece of the announcement was Gemma 4 E2B, a compact yet capable model designed to run natively on Pixel devices' TPU. Unlike cloud-based alternatives, this model keeps all user information local, making it suitable for sensitive applications where privacy is paramount.

Alongside Gemma 4, Google introduced Functional Gemma, which enables the TPU to execute specific tasks and mobile actions directly on the phone. This allows the device itself to reason about user requests without relying on external servers.

Practical Offline AI Capabilities#

Google demonstrated a range of real-world applications that operate without internet connectivity:

• AI Chat: Engage in detailed conversations offline, even while flying at 30,000 feet
• Ask Image: Photograph objects, plants, or problematic items to get instant identification
• Ask Audio: Transcribe lectures and audio recordings with zero internet dependency

Industry Applications Taking Shape#

The technology already shows promise across multiple sectors. Retailers can convert meal ideas into offline shopping routes customized for their local stores. In automotive repair, mechanics can photograph damaged components and receive instant visual analysis on the spot—all without connectivity.

Developer Access and Resources#

Google is opening access through its Tensor SDK beta, providing developers with the tools needed to build TPU-powered applications. The company has released source code samples, over 100 classical machine learning models, and pre-trained models through its Hugging Face community. Additional resources include Colab notebooks and an Android gallery app for exploring edge AI capabilities.