TinyML & Edge AI: On-device inference, model quantization, embedded ML, ultra-low-power AI for microcontrollers and IoT devices.

AI for Apple silicon devices.

Auditable offline edge intelligence for low-cost edge devices, with benchmark evidence and public board proof on ESP32-C3.

The Private Agent OS — search files, run AI agents, connect to 10,000+ tools via the complete protocol stack (MCP, AG-UI, A2UI, A2A). Zero cloud. Zero telemetry. On-device inference.

Flutter starter example app to get started with NobodyWho, a library designed to run LLMs locally and efficiently on any device.

React Native starter example app to get started with NobodyWho, a library designed to run LLMs locally and efficiently on any device.

Custom llama.cpp fork with character intelligence engine: control vectors, attention bias, head rescaling, attention temperature, fast weight memory

iOS + Android app that runs local LLMs on-device + routstr cloud LLMs for anonymous inference

Pythonic binding to the Apple Neural Engine

Mobile AI: iOS CoreML, Android TFLite, on-device inference, ONNX, TensorRT, and ML deployment for smartphones.

⚡️ The fastest way to run local LLMs on Apple Silicon — sub-second model loads, beats Ollama on throughput, tail latency, and full-response time. OpenAI/Ollama-compatible. No cloud, no API keys.

Curated resource for mobile teams shipping on-device LLMs — runtime benchmarks, model picks, GDPR-friendly architecture, and real production use cases.

High-performance Android SDK for on-device LLM inference (GGUF). Privacy-focused, offline-first, and powered by llama.cpp with a clean Kotlin Coroutines API.

Demos and sample code for building AI-powered apps with local on-device models on Windows — using Windows AI APIs, Foundry Local, Windows ML, and WebNN. From Microsoft Build 2026.

On-device AI inference for Swift apps. Run LLMs locally on iOS, macOS, visionOS and watchOS.

Production Android AI with ExecuTorch 1.0 - Deploy PyTorch models to mobile with NPU acceleration and 50KB footprint

On-device LLM client for Android. Fork of Google AI Edge Gallery

Unofficial Swift SDK for Google's LiteRT-LM — run Gemma 4 on-device with text, vision, audio, and tool calling. CPU + GPU (Metal). iOS 17+ / macOS 14+.