apple-on-device-ai

Guide for selecting, deploying, and optimizing on-device ML models. Covers Apple Foundation Models, Core ML, MLX Swift, and llama.cpp.

Use this decision tree to pick the right framework for your use case.

When to use: Text generation, summarization, entity extraction, structured output, and short dialog on iOS 26+ / macOS 26+ devices with Apple Intelligence enabled. Zero setup -- no API keys, no network, no model downloads.

Use when integrating Foundation Models framework, implementing on-device AI with Apple Intelligence, building tool-calling AI features, working with guided generation schemas, converting models with Core ML and coremltools, or running open-source LLMs on Apple Silicon. Covers Foundation Models (LanguageModelSession, @Generable, @Guide, SystemLanguageModel, structured output, tool calling), Core ML (coremltools, model conversion, quantization, palettization, pruning, Neural Engine, MLTensor), MLX Swift (transformer inference, unified memory), and llama.cpp (GGUF, cross-platform LLM). Source: dpearson2699/swift-ios-skills.