Chinese AI Art Prompt Weight Editor

Weighting tells the model what matters most

In AI-art models such as Stable Diffusion, ComfyUI, NovelAI and the various 文生图 tools, a prompt is a list of terms — but not every term should pull with equal force. Weighting is how you tell the model which words matter more and which should fade into the background. The explicit form (词:1.3) sets a term's weight to 1.3, a little more emphasis than the default of 1.0; (词:0.7) pulls it down. The bracket form does the same thing through nesting: (词) adds roughly ten percent of weight per pair of parentheses, while [词] removes roughly ten percent per pair of square brackets. This editor keeps that bookkeeping out of your way: you type your terms once, separated by commas, and each one gets its own slider. Drag the slider, watch the number update, and the weighted prompt rebuilds itself instantly, in whichever syntax style your target model expects.

Chinese terms weight in exactly the same way as English ones, because the model only ever sees bracketed plain text — (霓虹灯:1.3) is parsed no differently from (neon lights:1.3). What changes is how well a given model understands the underlying Chinese vocabulary, which is why prompting a Chinese-native model in Chinese, with weights, often gives the most faithful result. The editor also removes duplicate terms automatically, so you never accidentally weight the same word twice, and it accepts both the Chinese comma "，" and the ASCII comma "," as separators. Because the output is ordinary text, the same weighted prompt is portable: paste it into the positive-prompt box of almost any modern image model and it will be understood.

Restraint and balance beat a single huge weight

The mistake almost everyone makes early on is treating weight as a volume knob and turning it to the maximum. Push a single term to 1.8 or beyond and it stops being emphasis and starts being domination: the weighted element crowds out everything else, the composition collapses, and artefacts creep in. A far more reliable habit is restraint. Pick the one or two terms that genuinely carry the image, lift them gently into the 1.1–1.5 range, and leave everything else at 1.0. Weight is relative — if you raise every term at once, you have emphasised nothing, you have simply rescaled the whole prompt. The slider in this editor is deliberately capped at a sane maximum and steps in small increments precisely to encourage that fine-tuning mindset over brute force.

Weighting also works best in partnership with the other levers you already have. Term order matters: words near the front of a prompt tend to receive more attention, so a key term placed early and given a modest 1.2 often beats the same term buried at the end at 1.6. De-emphasis is the quiet half of the craft — dropping an unwanted-but-stubborn element to 0.6, or wrapping it in square brackets, is frequently cleaner than deleting it outright and hoping it stays gone. Treat your first weighted prompt as a draft: generate, see where the image drifts, then nudge one weight up or down and try again. Two or three rounds of that, with everything assembled instantly and privately in your browser, will usually land you on a balanced, reusable prompt that says exactly what you meant.