WWDC26: Integrate on-device AI models into your app using Core AI | Apple

Описание: Discover a curated collection of popular open-source models — including Qwen, Mistral, SAM3, and more — optimized for Apple silicon using the new Core AI Framework. Learn how to download, run, and benchmark models on your Mac, and integrate them into your app with just a few lines of code. Explore a new workflow for model compilation and on-device specialization to speed up first-time model load. Find out how to profile and optimize runtime performance with Core AI tools in Xcode.

Explore related documentation, sample code, and more:
Core AI PyTorch Extensions: https://apple.github.io/coreai-torch
Core AI Python: https://apple.github.io/coreai-torch/...
Core AI Optimization: https://apple.github.io/coreai-optimi...
Core AI: https://developer.apple.com/documenta...
Compiling Core AI models ahead of time: https://developer.apple.com/documenta...
Explore distributed inference and training with MLX: https://developer.apple.com/videos/pl...
Run local agentic AI on the Mac using MLX: https://developer.apple.com/videos/pl...
Explore numerical computing in Swift with MLX: https://developer.apple.com/videos/pl...
Build local AI agents on Mac with MLX: https://developer.apple.com/videos/pl...

00:00 - Introduction
01:16 - App concept: camera-based vocab learning
02:52 - Model discovery
07:40 - Getting models with the Core AI models repository
08:37 - Integration
10:55 - Writing the Swift integration code
13:05 - Diagnosing model specialization latency
14:40 - Deployment
17:00 - Ahead-of-time (AOT) compilation
18:03 - iOS demo
19:57 - Multiplatform
23:06 - Next steps

More Apple Developer resources:
Video sessions: https://apple.co/VideoSessions
Documentation: https://apple.co/DeveloperDocs
Forums: https://apple.co/DeveloperForums
App: https://apple.co/DeveloperApp