(edge-platforms-section)=

Edge

Deploy ExecuTorch on mobile, desktop, and embedded platforms with optimized backends for each.

ExecuTorch supports deployment across a wide variety of edge computing platforms, from high-end mobile devices to constrained embedded systems and microcontrollers.

Android

Deploy ExecuTorch on Android devices with hardware acceleration support.

→ {doc}android-section — Complete Android deployment guide

Key features:

  • Hardware acceleration support (CPU, GPU, NPU)
  • Multiple backend options (XNNPACK, Vulkan, Qualcomm, MediaTek, ARM, Samsung)
  • Comprehensive examples and demos

iOS

Deploy ExecuTorch on iOS devices with Apple hardware acceleration.

→ {doc}ios-section — Complete iOS deployment guide

Key features:

  • Apple hardware optimization (CoreML, MPS, XNNPACK)
  • Swift and Objective-C integration
  • LLM and computer vision examples

Desktop & Laptop Platforms

Deploy ExecuTorch on Linux, macOS, and Windows with optimized backends.

→ {doc}desktop-section — Complete desktop deployment guide

Key features:

  • Cross-platform C++ runtime
  • Platform-specific optimization (OpenVINO, CoreML, MPS)
  • CPU and GPU acceleration options

Embedded Systems

Deploy ExecuTorch on constrained embedded systems and microcontrollers.

→ {doc}embedded-section — Complete embedded deployment guide

Key features:

  • Resource-constrained deployment
  • DSP and NPU acceleration (Cadence, ARM Ethos-U, NXP)
  • Custom backend development support
  • LLM and computer vision examples

Troubleshooting & Support

  • {doc}using-executorch-troubleshooting - Common issues and solutions across all platforms

Next Steps

After choosing your platform:

  • {doc}backends-section - Deep dive into backend selection and optimization
  • {doc}llm/working-with-llms - Working with Large Language Models on edge devices
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:maxdepth: 3
:caption: Edge Platforms

android-section
ios-section
desktop-section
embedded-section
using-executorch-troubleshooting