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Efficient conversion, runtime, and optimization for on-device machine learning.
Built on the battle-tested foundation of TensorFlow Lite
LiteRT isn't just new; it's the next generation of the world's most widely deployed machine learning runtime. It powers the apps you use every day, delivering low latency and high privacy on billions of devices.
Simplified hardware acceleration
Obtain a model
Use .tflite pre-trained models or convert PyTorch, JAX or TensorFlow models to .tflite
Optimize the model
Optionally Quantize the model
Run
Pick desired accelerator and run on LiteRT
Tutorials show you how to use LiteRT with complete, end-to-end examples.
Pre-trained, out-of-the-box Gen AI models.
A gallery that showcases on-device ML/GenAI use cases
Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.0 License , and code samples are licensed under the Apache 2.0 License . For details, see the Google Developers Site Policies . Java is a registered trademark of Oracle and/or its affiliates.
Last updated 2025-12-19 UTC.
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