You can do it without building libtorch android, using native libraries from PyTorch android gradle dependency. For that, you will need to add the next lines to your gradle build.

To use from Android, ExecuTorch provides Java/Kotlin API bindings and Android platform integration, available as an AAR file. Note: This page covers Android app integration through …

Nov 14, 2025 · Leveraging the GPU on Android devices can significantly speed up the inference process, making real - time applications more feasible. This blog will explore the fundamental …

Apr 28, 2025 · This document outlines how to use PyTorch for Android development, focusing on the PyTorch Mobile framework that enables running PyTorch models on Android devices. The …

Question Answering demonstrates how to convert a powerful transformer QA model and use the model in an Android app to answer questions about PyTorch Mobile and more.

Nov 17, 2024 · In this blog, we’ll walk you through the process of deploying PyTorch models to iOS and Android using PyTorch Mobile.

Jun 18, 2021 · In this blog post, we provide a quick overview of 10 currently available PyTorch Mobile powered demo apps running various state-of-the-art PyTorch 1.9 machine learning …

Nov 14, 2025 · PyTorch Android is a set of libraries and tools that allow developers to run PyTorch models on Android devices. It provides a Java and Kotlin API for loading pre - trained …

After a PyTorch model is trained or a pre-trained model is made available, it is normally not ready to be used in mobile apps yet. It needs to be quantized (see the Quantization Recipe), …

Jul 10, 2024 · A new Learning Path explaining how to leverage the capabilities of large language models (LLMs) on Android using ExecuTorch and XNNPACK is now available. Here’s a …