Prompt Weighting
A technique for emphasizing or de-emphasizing specific words in an AI image generation prompt to control their influence on the output.
Prompt weighting lets users fine-tune AI image generation by assigning numerical importance to different prompt tokens. Common syntaxes include parentheses for emphasis ((word) = 1.1x, ((word)) = 1.21x) or explicit weights (word:1.5). Negative weights or negative prompts exclude unwanted elements. Effective prompt weighting addresses a common frustration: AI models don't weight all words equally, and important details can get lost. By boosting 'sharp focus:1.4' or 'golden hour lighting:1.3', users steer the generation toward specific attributes. The technique requires experimentation — too much weight creates artifacts, while too little has no visible effect. Combined with negative prompts, weighting gives precise creative control over AI outputs.
Related Terms
Prompt Engineering
The practice of crafting precise text descriptions to guide AI image generation models toward desired visual outputs.
Text-to-Image
AI technology that generates images from written text descriptions (prompts).
ControlNet
A neural network architecture that adds spatial conditioning to diffusion models, enabling precise control over generated image structure.
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