AI image generation on mobile still feels harder than it should. Many apps rely on cloud rendering, credit systems, queues, accounts, and limited control. You write a prompt, spend a credit, wait for the result, and hope it matches what you had in mind.
PhoneDiffusion takes a different approach.
Generate AI images locally on your iPhone with PhoneDiffusion: https://apps.apple.com/us/app/phonediffusion/id6762061991
It is an iPhone app for local AI image generation, built around curated Stable Diffusion model packs converted for Apple Core ML. After downloading a compatible model pack, users can generate images directly on their device without sending prompts or images to a cloud service.
The goal is simple: make private, on-device image generation feel practical on iPhone.
PhoneDiffusion does not require an account. Prompts, negative prompts, generation history, images, and model files stay on the device unless the user chooses to export, share, or submit feedback. Instead of asking people to manage random model files manually, the app uses curated packs that are prepared for iOS.
The app currently focuses on two main areas: generation and gallery. In Generate, users choose a model, select a style, write a prompt, adjust settings if needed, and create an image. In Gallery, they can revisit previous generations, compare results, save, share, or delete them.
Under the hood, PhoneDiffusion uses Apple’s Core ML Stable Diffusion stack. The launch model set includes fast SD 1.5-class options and heavier SDXL Lightning-class models, including DreamShaper, Realistic Vision, CyberRealistic, RealVisXL, and other mobile-oriented experiments.
This is not meant to replace a full desktop Stable Diffusion workstation. Power users already have excellent tools for advanced workflows such as LoRAs, ControlNet, inpainting, outpainting, custom model imports, and complex graph-based workflows. PhoneDiffusion is aimed at a more focused use case: private, curated, phone-native image generation that is approachable enough for regular creators, while still useful for people who understand Stable Diffusion.
The basic flow is straightforward. Install the app, download a compatible model pack, let the app prepare the local pipeline, enter a prompt, generate, and save the result locally.
A major part of the work was performance testing. Local image generation on iPhone is not just a matter of packaging a model and pressing run. Model downloads can be large, iOS memory pressure matters, devices heat up, and Core ML execution behavior can vary depending on device state.
In testing, SD 1.5-class models proved to be the best path for fast and reliable first results. SDXL can deliver better image quality, but it comes with heavier cold-start, memory, and thermal tradeoffs. For many users, especially without the newest Pro-level iPhone hardware, the faster SD 1.5 models are likely to feel better in day-to-day use.
The team also benchmarked image quality manually, looking at visual quality, prompt adherence, and artifacts. Automated scores can help, but for a creative tool, human judgment still matters. If a model misses the subject, layout, or product details, the user notices immediately.
PhoneDiffusion is built for people who want private visual brainstorming on iPhone without a desktop setup or cloud workflow. Useful early workflows include avatars, tattoo ideas, thumbnails, poster concepts, product-shot drafts, interior moodboards, wallpapers, character ideas, and quick style exploration.
The broader idea behind PhoneDiffusion is that mobile AI should not simply copy desktop AI tools at a smaller size. Phones have different constraints, different workflows, and different expectations. A good local AI image generator for iPhone needs to respect those limits while still giving creators meaningful control.
You can try PhoneDiffusion here: https://apps.apple.com/us/app/phonediffusion/id6762061991
