Download Amazing AI 1.1.0 (Mac) – Download Free

If you haven’t tried generating images with AI, you might want to check out some intuitive macOS apps that use the Stable Diffusion text-to-image model. They do a great job of simplifying the process while adding various other features.

amazing artificial intelligence is a very simple application that provides you with a user-friendly interface and comes with a bunch of features that make it easier to generate one or more images and use them for whatever project you need them for.

Intuitive AI Image Generation

One of the app’s greatest strengths is its streamlined and intuitive design. You just need to enter as detailed a hint as possible in the input field and the application will start generating images.

The picture is also automatically enlarged after the process is complete, which is not available in other applications or must be done manually. You can then save it anywhere on your Mac or share it directly.

Optimized and Customizable

Amazing AI only runs on Apple Silicon, and it runs on Apple’s Neural Engine. It’s also written in native code, unlike some other Stable Diffusion GUIs that rely on Electron. Essentially, it will run as efficiently as possible.

To get things just right, you can experiment with adjusting the number of steps and level of guidance, and even adding seeds to reproduce specific images. Multiple images can be generated from the same cue, and you can enter new cues to add them to the queue while the previous one is being processed.

Excellent stable diffusion GUI

Aside from the lack of support for Inpainting and Outpainting (which the developers have no plans to include), the app has everything you need to create images from scratch using Stable Diffusion. It can even be triggered via a shortcut for a more efficient workflow.

While the application itself is quite large, since it must contain the AI ​​model, it has the benefit of being able to run completely offline. You cannot currently use custom models, but this functionality is planned for a future release.