Enlarge / Two examples of Stable Diffusion-generated artwork provided by Apple. (credit: Apple)

On Wednesday, Apple released optimizations that allow the Stable Diffusion AI image generator to run on Apple Silicon using Core ML , Apple's proprietary framework for machine learning models. The optimizations will allow app developers to use Apple Neural Engine hardware to run Stable Diffusion about twice as fast as previous Mac-based methods.

Stable Diffusion (SD), which launched in August, is an open source AI image synthesis model that generates novel images using text input. For example, typing "astronaut on a dragon" into SD will typically create an image of exactly that.

By releasing the new SD optimizations—available as conversion scripts on GitHub —Apple wants to unlock the full potential of image synthesis on its devices, which it notes on the Apple Research announcement page. "With the growing number of applications of Stable Diffusion, ensuring that developers can leverage this technology effectively is important for creating apps that creatives everywhere will be able to use."

Enlarge / Generating AI images using "Draw Things" on the iPhone. (credit: Benj Edwards / Apple)

On Wednesday, a San Francisco-based developer named Liu Liu released Draw Things: AI Generation , a free app available in the App Store that lets iPhone owners run the popular Stable Diffusion AI image generator. Type in a description, and the app generates an image within several minutes. It's a notable step toward bringing image synthesis to a wider audience—with the added privacy of running it on your own hardware.

Introduced in August, Stable Diffusion (SD) is an AI image generator model that creates novel images from text descriptions (called "prompts"). Typically, people run SD through the commercial DreamStudio service, on a remote cloud machine with rented compute time, or locally on a PC using a custom open source implementation. When running locally, SD requires a fairly beefy GPU to generate images quickly, but some developers optimized the model to run on older GPUs with less VRAM (if you don't mind waiting longer to see results).

In the same vein, Liu Liu has managed to optimize Stable Diffusion to run on the iPhone, a somewhat difficult process that the developer described in a blog post . "The main challenge is to run the app on the 6GiB RAM iPhone devices," Liu Liu writes. "6GiB sounds a lot, but iOS will start to kill your app if you use more than 2.8GiB on a 6GiB device, and more than 2GiB on a 4GiB device."