Generate images from text on Apple Silicon.
Free trial available
Overview
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FAQs
Overview
Pricing
Ratings
Alternatives
FAQs
Overview
Pricing
Ratings
Alternatives
FAQs
Amazing AI is the ultimate tool for Apple Silicon users. Powered by Stable Diffusion, a text-to-image deep learning model, this app offers lightning-fast image generation based on text inputs. Its highly optimized for the Apple Neural Engine, providing unmatched speed and energy efficiency. With features like batch generation, shortcuts support, and automatic upscaling, Amazing AI makes creating images from text a breeze. The images are also free to use for any purpose, as long as they adhere to the Creative ML OpenRAIL
Pricing
Free trial available
Exclusively for Apple Silicon, Uses Stable Diffusion, Highly optimized for Apple Neural Engine, Faster than other tools
Only for Apple Silicon, Requires MacOS 13.1, No Intel Chip compatibility
Free
Amazing AI users appreciate its Exclusively for Apple Silicon, Uses Stable Diffusion, Highly optimized for Apple Neural Engine and Faster than other tools, though some note a Only for Apple Silicon, Requires MacOS 13.1 and No Intel Chip compatibility.
Revolutionizing visual content creation with AI.
Art-generated experimentation with diffusion models.
Create characters from language descriptions.
Stuck on something? We're here to help with all the questions and answers in one place.
Some top alternatives to Amazing AI includes Pixilio, Peacasso, Gemsouls, Charisma and Logodiffusion.
Amazing AI offers Free pricing model
The starting price is not disclosed by Amazing AI. You can visit Amazing AI website to get the latest pricing.
Amazing AI offers several advantages, including Exclusively for Apple Silicon, Uses Stable Diffusion, Highly optimized for Apple Neural Engine, Faster than other tools, More energy efficient and many more functionalities.
The cons of Amazing AI may include a Only for Apple Silicon, Requires MacOS 13.1, No Intel Chip compatibility, Doesn't support Stable Diffusion 2. and Cannot create custom models
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