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AI Image Prompt Builder

Assemble an image prompt from the parts that actually change the image.

Subject

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Result
 

Position is weighting

Most image models weight earlier terms more heavily than later ones. The first three or four terms effectively decide the image, and everything after is adjustment.

That makes term order a real control rather than a stylistic choice. Putting your subject after four style adjectives produces a different image than putting it first.

What earns its place

Medium — photograph, oil painting, 3D render. Lens and film stock for photographic looks. Lighting direction and time of day. Composition framing. These reliably change the output.

What mostly does not: "masterpiece", "best quality", "8k", "highly detailed", "trending on artstation". They correlated with good images in early diffusion training captions and are close to noise on current models, while still occupying the positions that matter most.

Frequently asked questions

How long should an image prompt be?
Long enough to specify subject, medium, lighting and composition. Beyond roughly twenty meaningful terms the model stops distinguishing between them, and additions start competing with your subject rather than supporting it.
Does this work for every image model?
The structure transfers well. Weighting syntax and negative prompt support do not — several current models accept neither, and there you describe what you want instead of what you do not.

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