Unlocking iOS 26: How Developers Use Apple’s Local AI Models
▼ Summary
– Apple introduced its Foundation Models framework at WWDC 2025, enabling developers to use local AI models in their apps without inference costs.
– These local models are smaller than those from major AI companies and focus on improving quality-of-life features rather than major workflow changes.
– Apps like Lil Artist, Daylish, and MoneyCoach use the framework for features such as AI-generated stories, emoji suggestions, and spending insights.
– LookUp, Tasks, and Day One leverage the models for word learning, task management, and journaling enhancements like generating examples and prompts.
– Additional apps including Crouton and SignEasy apply the AI for recipe organization, contract summarization, and other practical, on-device functionalities.
The arrival of iOS 26 has unlocked a new era for app developers, thanks to Apple’s Foundation Models framework. This powerful toolset allows creators to integrate local AI models directly into their applications, eliminating inference costs and enabling smarter, more responsive features without relying on cloud processing. These on-device models support guided generation and tool calling, making it easier than ever to build intelligent apps that respect user privacy and perform seamlessly offline.
While Apple’s models are more compact than those from giants like OpenAI or Google, they excel at enhancing everyday usability rather than overhauling entire app experiences. Early adopters are already leveraging this technology to introduce thoughtful, quality-of-life improvements.
Lil Artist offers interactive learning experiences for children, and with the iOS 26 update, it now includes an AI story creator. Users can pick a character and theme, and the app generates a unique story using on-device text generation.
Daylish, a daily planner app, is prototyping a feature that suggests emojis for timeline events based on the title of each entry, all processed locally.
MoneyCoach, a finance tracking app, uses local AI to provide spending insights, like alerting you if you’ve gone over your typical grocery budget, and automatically suggests categories for new expenses.
LookUp, a word-learning app, has introduced two new AI-powered modes. One creates contextual examples for vocabulary words, and another challenges users to explain word usage. The app also uses on-device models to generate word origin maps.
Tasks uses local models to recommend tags, detect recurring tasks, and even break down spoken instructions into individual action items, all without an internet connection.
Day One, the popular journaling app, employs Apple’s models to highlight key moments, suggest entry titles, and generate writing prompts that encourage deeper reflection.
Crouton, a recipe app, uses local AI to recommend tags, name timers, and break down recipe instructions into clear, step-by-step directions.
SignEasy leverages on-device intelligence to summarize contracts and extract essential insights, helping users understand what they’re signing quickly and clearly.
This is just the beginning. As more developers explore the potential of Apple’s local AI models, we can expect a continued wave of innovation that makes our apps smarter, faster, and more intuitive.
(Source: TechCrunch)
