On-Device AI for Apple Platforms

Architect and deploy private on-device machine learning and LLMs on Apple Silicon. Covers framework selection between Apple Foundation Models, Core ML, MLX Swift, and llama.cpp, plus model optimization and quantization.

Scope Boundary: Swift-side Core ML inference and model caching live in coreml. This skill owns backend selection, architecture, model conversion, and LLM runtimes.

Contents

• Framework Selection Router
• Apple Foundation Models
• Core ML & Model Conversion
• MLX Swift & Open Weights
• Model Compression & Optimization
• Common Mistakes
• Review Checklist
• References

Framework Selection Router