LiteRT (short for Lite Runtime) is the new name for TensorFlow Lite (TFLite). While the name is new, it's still the same trusted, high-performance runtime for on-device AI, now with an expanded vision.

LiteRT Torch Converter: A tool to convert PyTorch models into the .tflite format. LiteRT Torch Generative API: A library to reauthor LLMs for efficient conversion and inference.

class Optimize: Enum defining the optimizations to apply when generating a tflite model. class RepresentativeDataset: Representative dataset used to optimize the model.

A Github issue should be the primary method of getting in touch with the TensorFlow Lite Micro (TFLM) team. The following resources may also be useful: SIG Micro email group and monthly meetings. …

Dec 29, 2025 · TensorFlow Lite Model File (.tflite): A lightweight platform-independent model format based on FlatBuffers, optimized for low latency, high performance and minimal memory usage.

Oct 28, 2025 · TensorFlow Lite Flutter plugin provides an easy, flexible, and fast Dart API to integrate TFLite models in flutter apps across mobile and desktop platforms.

May 28, 2026 · This interface simplifies the deployment of .tflite models across a wide range of edge platforms by providing a unified developer experiences and advanced features designed for …

Oct 2, 2025 · TensorFlow Lite (TFLite) is Google’s solution for running ML models on edge devices with low latency and a small footprint. To use it, you need to convert your standard TensorFlow models …

Feb 2, 2023 · With TensorFlow Lite (TFLite), you can now run sophisticated models that perform pose estimation and object segmentation, but these models still require a relatively powerful processor …

Sep 18, 2024 · In this codelab, you’ll build an Android app that can detect objects in images. You’ll start with training a custom object detection model with TFLite Model Maker and then deploy it with TFLite...