apple-on-device-ai
Build private, on-device AI features on iPhone, iPad, and Mac with Foundation Models, Core ML, MLX Swift, or llama.cpp. Use when choosing an Apple-local model runtime, building an Apple Intelligence chatbot or tool-calling feature, running an LLM on Apple Silicon, converting or compressing a Python model for Core ML, or comparing on-device inference backends. For Swift Core ML loading and prediction code, use the coreml skill.
Profile →npx skills add dpearson2699/swift-ios-skills --skill apple-on-device-ai --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# On-Device AI for Apple Platforms Guide for selecting, deploying, and optimizing on-device ML models. Covers Apple Foundation Models, Core ML, MLX Swift, and llama.cpp. ## Contents - [Framework Selection Router](#framework-selection-router) - [Apple Foundation Models Overview](#apple-foundation-models-overview) - [Core ML Overview](#core-ml-overview) - [MLX Swift Overview](#mlx-swift-overview) - [Multi-Backend Architecture](#multi-backend-architecture) - [Performance Best Practices](#performance-best-practices) - [Common Mistakes](#common-mistakes) - [Review Checklist](#review-checklist) - [References](#references) ## Framework Selection Router Use this decision tree to pick the right framework for your use case. ### Apple Foundation Models **When to use:** Text generation, summarization, entity extraction, structured output, and short dialog on iOS 26+ / macOS 26+ devices with Apple Intelligence enabled. No app-managed API key, network round trip, or model hosting; still handle system model asset readiness. **Best for:** - Generating text or structured data with `@Generable` types - Summarization, classification, content tagging - Tool-augmented generation with the `Tool` protoco
- Contents
- Framework Selection Router
- Apple Foundation Models
- Core ML
- MLX Swift
- llama.cpp
- Quick Reference
- Apple Foundation Models Overview
- Core ML Overview
- Model Formats
- Conversion Pipeline (coremltools)
- Validate, Fix, and Reconvert
- Boundary with coreml
- MLX Swift Overview
What does the apple-on-device-ai skill do?
Build private, on-device AI features on iPhone, iPad, and Mac with Foundation Models, Core ML, MLX Swift, or llama.cpp. Use when choosing an Apple-local model runtime, building an Apple Intelligence chatbot or tool-calling feature, running an LLM on Apple Silicon, converting or compressing a Python model for Core ML, or comparing on-device inference backends. For Swift Core ML loading and prediction code, use the coreml skill.
How do I install it?
Run `npx skills add dpearson2699/swift-ios-skills --skill apple-on-device-ai --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From dpearson2699/swift-ios-skills, a repository with 963 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.