Prompt weighting
Prompt weighting lets you boost or reduce the influence of specific words in your prompt, so the model pays more attention to the parts that matter most to you.
By default every word in a prompt carries roughly equal pull. Prompt weighting changes that. By marking a word or phrase with a weight, you tell the model to give it more (or less) influence over the result - handy when the model keeps under- or over-emphasizing something.
How it works
Most tools use a syntax like (word:1.4) to increase a term's weight or (word:0.6) to decrease it, where 1.0 is the baseline. Some interfaces use parentheses to nudge weight up and square brackets to nudge it down. Under the hood, the weighting scales how strongly that term's text embedding steers each denoising step.
Why it matters
Weighting is more surgical than rewriting a prompt or cranking the CFG scale (which boosts everything at once). If "red dress" keeps coming out pink, bumping (red:1.3) fixes just that. Use restraint - very high weights can distort the image or wash out other details.
Emphasize the material and de-emphasize the background so the subject dominates.
Example prompt
a (hand-forged steel knife:1.4) on a (rustic wooden table:0.7), dramatic side lighting, macro photographyTry it in the generator
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Related terms
- Negative promptA negative prompt is a list of words describing what you do NOT want in the image. The model steers away from those concepts while it generates, which removes common flaws and unwanted elements.
- CFG scaleCFG scale (classifier-free guidance scale) controls how strongly the image follows your prompt. Low values are loose and creative; high values stick closely to the prompt but can look over-processed.
- Text-to-imageText-to-image is the AI workflow where you type a written prompt and the model generates a brand-new image from it - no source image required.