ExecuTorch

What is ExecuTorch?

ExecuTorch is an end-to-end solution for enabling on-device inference capabilities across mobile and edge devices including wearables, embedded devices and microcontrollers. It is part of the PyTorch Edge ecosystem and enables efficient deployment of various PyTorch models (vision, speech, Generative AI, and more) to edge devices. Key value propositions of ExecuTorch are:

Portability: Compatibility with a wide variety of computing platforms, from high-end mobile phones to highly constrained embedded systems and microcontrollers.

Productivity: Enabling developers to use the same toolchains and SDK from PyTorch model authoring and conversion, to debugging and deployment to a wide variety of platforms.

Performance: Providing end users with a seamless and high-performance experience due to a lightweight runtime and utilizing full hardware capabilities such as CPUs, NPUs and DSPs.

Explore ExecuTorch

ExecuTorch is currently powering various experiences across AR, VR and Family of Apps (FOA) products and services at Meta. We are excited to see how the community leverages our all new on-device AI stack. You can learn more about key components of ExecuTorch and its architecture, how it works, and explore documentation pages and detailed tutorials.

ExecuTorch Documentation ExecuTorch on GitHub

Why ExecuTorch?

Supporting on-device AI presents unique challenges with diverse hardware, critical power requirements, low/no internet connectivity, and realtime processing needs. These constraints have historically prevented or slowed down the creation of scalable and performant on-device AI solutions. We designed ExecuTorch, backed by our industry leaders like Meta, Arm, Apple, and Qualcomm, to be highly portable and provide superior developer productivity without losing on performance.