# edge-ai

Run open-source LLMs on your phone, fully offline and private

Google AI Edge Gallery is an open-source mobile app that lets you download and run large language models like Gemma directly on Android and iOS devices with zero cloud dependency. Built on MediaPipe and LiteRT, it features AI chat with reasoning mode, multimodal image analysis, real-time audio transcription, and autonomous agent skills—all running entirely on-device for complete privacy. A reference implementation for developers building offline-first AI experiences.

Google's production on-device LLM inference framework

LiteRT-LM is Google's official open-source framework for running large language models on-device across Android, iOS, Web, Desktop, and Raspberry Pi. Already deployed in Chrome and Pixel hardware, it provides production-grade on-device LLM inference with 1.4K+ GitHub stars. Apache 2.0 licensed.

High-performance WebAssembly runtime for cloud and AI

WasmEdge is a CNCF sandbox WebAssembly runtime optimized for cloud-native, edge, and AI workloads. It provides a lightweight, secure, and portable execution environment that is faster than containers and safer than native processes. WasmEdge supports LLM inference via LlamaEdge, serverless functions, microservices, and plugin extensions for networking, AI, and cryptography across Linux, macOS, and Windows.

Google's lightweight ML framework for mobile and embedded

TensorFlow Lite is Google's lightweight ML framework for deploying models on mobile and embedded devices. It supports quantization, GPU/NPU delegation, and runs on Android, iOS, Linux, and microcontrollers. Provides pre-trained models, model conversion tools from TensorFlow and JAX, and hardware acceleration via GPU, Hexagon DSP, and CoreML delegates. Powers on-device ML in billions of Google app installations.

Optimize and deploy AI models on Snapdragon devices

Qualcomm AI Hub is a platform for optimizing and deploying AI models on Snapdragon-powered devices with NPU acceleration. It provides pre-optimized models, profiling tools, and the SNPE SDK for compiling models to run efficiently on Qualcomm's Hexagon DSP and AI Engine. Supports hundreds of model architectures with on-device benchmarking across real Snapdragon chipsets for mobile, IoT, and XR applications.