Google Tensor SDK Beta with LiteRT

MAY 19, 2026

Priya Patel Product Lead

Himangshu Roy Engineering Lead

Google Tensor ML SDK empowers you to build on-device machine learning capabilities starting from Google Pixel 10 family of devices¹, while leveraging Pixel's custom-designed Google Tensor System-on-Chip (SoC) with its dedicated Tensor Processing Unit (TPU) inference accelerator. Today, the Tensor ML SDK is graduating from its Experimental Access Program (EAP) to Beta, enabling developers to build and deploy their AI experiences seamlessly on Google Tensor’s TPU. Tensor’s TPU unlocks interactive, realtime and private on-device AI experiences such as Pixel’s Pro Zoom², Add Me, Voice Translate³ and Call Notes⁴ to name a few.

Link to Youtube Video (visible only when JS is disabled)

Watch as our Product Management team dives into the Tensor SDK and what it means for the future of Pixel development.

The Beta launch unlocks two major advantages for developers:

A Unified Developer Workflow with LiteRT
A Model Garden to run 100+ models optimally on Tensor’s TPU

A Unified Developer Workflow with LiteRT

LiteRT is Google's on-device framework for high-performance machine learning (ML) deployment on edge platforms. It abstracts away low-level, vendor-specific SDKs including compilers and runtimes and exposes them through a unified, streamlined developer-facing API. Tensor ML SDK is now integrated with LiteRT offering a seamless developer workflow to convert, compile, deploy and run ML and Generative AI models on Google Pixel via Tensor’s TPU.

Compilation: Convert and compile your PyTorch or TFLite models into optimized binaries ready to leverage the Tensor TPU using LiteRT Torch.
Deployment: Use Play Feature Delivery to distribute and install the compatible runtime and compiler libraries that connect to the on-device TPU drivers. Use AI Packs (part of Play for On-device AI) to bundle and deliver the compiled model files within your application.
Run Inference: Leverage LiteRT Runtime to run your model on the TPU with just a few lines of code. It also allows you to enable robust fallback mechanisms by specifying CPU or GPU as secondary options, and automatically uses them depending on TPU availability.

For a full, detailed guide, including colab and sample apps, visit the LiteRT NPU documentation.

Model Garden of 100+ models on Tensor

The Tensor SDK Beta enables deployment of a wide array of models—including computer vision and speech recognition—straight to Pixel devices through a large model garden. The model garden provides over 100+ Classic ML models and Generative AI Models (Gemma 3 1B), alongside a library of precompiled models available to download directly from the LiteRT Hugging Face community.

Here is a look at what developers can build with the models available:

Small Language models: Enable local actions for app interactions with Function Gemma. Add rich semantic features to your app with EmbeddingGemma.
Intelligent Content creation: Build features that generate real-time text, apply smart image filters, and execute advanced computational photography effects—like portrait blurring
Vision & Understanding: Implement object detection, depth mapping, body tracking, multimodal image to text understanding to power camera applications that recognize and react to the user’s environment
Audio & Accessibility: Run end to end speech recognition to deliver secure, low latency audio transcription, voice-controlled accessibility tools, and translation on the edge

Here are a couple of demos for inspiration:

Image Segmentation LiteRT Sample App (Left) Function Gemma with LiteRT LM on AI Edge Gallery - Mobile Actions (Right)

Get Started with Pixel Today

We invite the developer community to build a new class of intelligent and responsive AI applications starting with the Pixel 10 family. Explore the Tensor SDK, experiment with running your models on the TPU, and share your feedback with the LiteRT community on Github.

If you're joining us at I/O—either in person or virtually—be sure to check out our dedicated codelabs and sample app. You'll get hands-on experience using the Tensor SDK, compiling models, and deploying them to the family of Pixel 10 devices via TPU.

Devices Supported: Pixel 10, Pixel 10 Pro, Pixel 10 Pro XL, and Pixel 10 Pro Fold.

We can’t wait to see what you build on Pixel!

Acknowledgements

^{This project was made possible through the collaboration of several teams. We thank them for their significant contributions:}

^{Tensor Team}^{: Himangshu Roy, Chirag Gupta, Rishubh Khurana, Rachit Agrawal, Priya Patel, Prakul Sawhney, Abby Chung, Malini P V, Jui Pradhan, Naina Singla, Debapriya Maji, Aditya Srivastava, Abhishek Jatram, Vibhu Agrawal, Rachana Jayaram, Lokesh Vutla, Abhishek Singh, Annie Fu, Chen-Hao Liao, Chanchal Raj, Ty Werbicki, Sriram Kashyap M S, Shubham Saini, Thiru Ramasamy, Jayanthan K, Payal Agarwal, Pranjal Srivastava, Yathish Reddy M, Akhilesh Ravi, Harold Yang, Yi Yo, Priyanka Mittal, Ishaan Agrawal, Vivek Kumar, Minje Park, YoonKyung Kim, Eunji Heo, Mehran Nekuii, John Joseph, Nett Phasukavanich, Jess Tsopanis, Chen-Hao Liao, Jeff Setter, Ganesh Rao, Neena Maldikar.}

^{LiteRT Team:} ^{Lu Wang, Weiyi Wang, Jingjiang Li, Gerardo Carranza, Terry (Woncheol) Heo, Andrew Zhang, Chenchen Tang, Shuangfeng Li, Changming Sun, Somdatta Banerjee, Na Li, Yu-hui Chen, Tenghui Zhu, Alice Zheng, Chintan Parikh, Sachin Kotwani, Cormac Brick, Matthias Grundmann, Salil Tambe.}