ExecuTorch v1.1.0

Zenodo (CERN European Organization for Nuclear Research) 2026 Open access

Read full text
Authors: Mergen Nachin, Raziel Álvarez, Dave Bort, Manuel A Candales, Yanan Cao, Zhengxu Chen, Soumith Chintala, Gregory Comer, Digant Desai, Tanvir Islam, Songhao Jia, Sicheng Stephen Jia
+25 more Tarun Karuturi, Abhinay Kukkadapu, Chen Lai, Mengwei Liu, Tugsbayasgalan. Manlaibaatar, Andrew Or, Kimish Patel, Siddartha Pothapragada, Lucy Qiu, Supriya Rao, Orion Reblitz-Richardson, Max Yi Ren, Scott Roy, Anthony Shoumikhin, Jacob Szwejbka, Scott Wolchok, Guang Yang, Angela Yi, Martin Yuan, Hansong Zhang, Jack Zhang, Jerry Zhang, Shunting Zhang, C. Cagatay Bilgin, Inc. Meta Platforms
DOI: 10.5281/zenodo.18988191
Cited by: 0

Abstract

ExecuTorch is PyTorch's unified solution for deploying AI models on-device—from smartphones to microcontrollers—built for privacy, performance, and portability. It powers Meta's on-device AI across Instagram, WhatsApp, Quest 3, Ray-Ban Meta Smart Glasses, and more. Deploy LLMs, vision, speech, and multimodal models with the same PyTorch APIs you already know—accelerating research to production with seamless model export, optimization, and deployment. No manual C++ rewrites. No format conversions. No vendor lock-in.

Fields of Study & Subjects

Advanced Neural Network Applications IoT and Edge/Fog Computing Parallel Computing and Optimization Techniques

Publication details

Journal / source
Zenodo (CERN European Organization for Nuclear Research)
Publication date
12 March 2026
Language
EN