Image Generation Settings
Search for our available models here to learn more about them.
Please use our default settings for optimal results if you're a beginner.
Image generation engines can often generate disproportionate body parts, extra limbs or fingers, strange textures etc. Use negative prompting to avoid disfiguration or for creative outputs like avoiding certain colour schemes, elements or styles.
By default, each run produces one output per Model.
An increase in output quality is comparable to a gradual progression in any drawing process that begins with a draft version and ends with a finished product.
At lower values the image will effectively be random. The standard value is between 6-8. Values that are too high can also distort the image.
Object Repositioning Settings
How big should the object look?
Where would you like to place the object in the scene?
![](data:image/png;base64,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)