Google AI Edge – on-device cross-platform AI deployment

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Deploy AI across mobile, web, and embedded applications

On device

Reduce latency. Work offline. Keep your data local & private.
Cross-platform

Run the same model across Android, iOS, web, and embedded.
Multi-framework

Compatible with JAX, Keras, PyTorch, and TensorFlow models.
Full AI edge stack

Flexible frameworks, turnkey solutions, hardware accelerators

Ready-made solutions and flexible frameworks

Low-code APIs for common AI tasks

Cross-platform APIs to tackle common generative AI, vision, text, and audio tasks.

Get started with MediaPipe tasks

Deploy custom models cross-platform

Performantly run JAX, Keras, PyTorch, and TensorFlow models on Android, iOS, web, and embedded devices, optimized for traditional ML and generative AI.

Get started with LiteRT

Feature 2

Shorten development cycles with visualization

Visualize your model’s transformation through conversion and quantization. Debug hotspots by overlaying benchmarks results.

Get started with Model Explorer

Feature 1

Build custom pipelines for complex ML features

Build your own task by performantly chaining multiple ML models along with pre and post processing logic. Run accelerated (GPU & NPU) pipelines without blocking on the CPU.

Get started with MediaPipe Framework

Feature 2

A low level framework used to build high performance accelerated ML pipelines, often including multiple ML models combined with pre and post processing.

Model Explorer

Visually explore, debug, and compare your models. Overlay performance benchmarks and numerics to pinpoint troublesome hotspots.

Gemini Nano in Android & Chrome

Build generative AI experiences using Google's most powerful, on-device model

Recent videos and blog posts

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