Run GenAI, AI, and ML Workloads at the Edge on Mobile Devices

Get Started running your ML and AI workloads on Arm Cortex CPUs.

ExecuTorch for On-Device AI

• Meta announced ExecuTorch to enable on-device AI for PyTorch in October, 2023. Learn what it is and how Executorch works.
• Read our guide on how to build an Android chat app with Llama, ExecuTorch, and XNNPACK.

Get Started with AI and ML on Unity with Unity Sentis and ML Agents

• A series of videos, learning paths, blogs and tutorials on how to bring AI and ML into your Unity project on Arm-based mobile devices.

Google’s AI Edge’s Mediapipe Acceleration on Arm-Based Android

• Google’s AI Edge’s Mediapipe is accelerated with Arm KleidiAI for Arm Cortex CPUs.
• Get started and run LLM inference on Android with KleidiAI, Mediapipe, and XNNPack.

Get Started with OpenCV on Android

• Learn how to create a computer vision (CV) application with OpenCV on Android devices.
• Learn how you can use OpenCV for face detection.

Accelerate your AI/ML framework, tools, and cloud services with open-source Arm libraries and optimized Arm SIMD code.

Arm Kleidi

• Arm Kleidi open-source libraries are a lighter weight performance library than ACL for accelerating AI and ML workloads and frameworks.

Arm KleidiAI

• Explore KleidiAI’s initial features and follow the step-by-step guide to running one of its critical functions for accelerating the Gemma LLM.

Arm KleidiCV

• The KleidiCV library is designed for image processing and integrates into any CV framework to enable optimum performance for CV workloads on Arm.

Arm SIMD-Extensions

• Optimize your AI/ML workloads with Arm SIMD code, either in assembly or using Arm Intrinsics in C/C++, to leverage huge performance gains.