Prompt Weight Editor
Set per-term attention weights for a Stable Diffusion prompt and rebuild it in (term:1.25) AUTOMATIC1111 syntax. Free, runs in your browser.
Prompt Weight Editor
Type a comma-separated prompt above and each term will appear here with a weight control.
How to Use the Prompt Weight Editor
Paste your prompt
Type or paste a comma-separated Stable Diffusion prompt into the box. Each phrase between commas — "a red fox", "snowy forest", "soft morning light" — becomes its own row you can weight.
Adjust the weights
Use the − and + buttons or type a number to set each term's attention weight from 0.1 to 2.0 (default 1.0). Push a term above 1.0 to emphasise it; drop it below 1.0 to de-emphasise.
Read the rebuilt prompt
The output rebuilds live in AUTOMATIC1111 syntax: a term at 1.0 stays bare, while anything else becomes (term:1.25). Tweak weights until the balance looks right.
Copy into your UI
Hit Copy and paste the weighted prompt into AUTOMATIC1111, ComfyUI, or any compatible Stable Diffusion interface. Everything runs in your browser — nothing is uploaded.
Attention Weighting Is How You Steer Stable Diffusion
What (term:1.2) actually does to your image
When Stable Diffusion reads your prompt, it converts every word into tokens and pays a certain amount of attention to each one while it denoises the image. By default each token carries equal pull. Attention weighting — the (term:1.2) syntax popularised by the AUTOMATIC1111 web UI — lets you tilt that balance deliberately. A weight above 1.0 tells the model "lean into this"; a weight below 1.0 says "ease off". So (snowy forest:1.3) makes the snow and trees dominate the scene, while (background clutter:0.6) quietly pushes distractions away without removing them entirely.
The number is a multiplier applied to that token's contribution, not a hard switch. Small nudges go a long way: moving a term from 1.0 to 1.15 is often enough to recover a detail the model kept dropping, while jumping to 1.8 can over-bake the image — colours blow out, anatomy warps, and the composition collapses around that one over-weighted idea. That is exactly why this editor steps in increments of 0.05 and caps the range at 0.1 to 2.0: it keeps you in the zone where weighting refines the picture instead of breaking it. Older prompt dialects used stacked brackets — ((term)) to emphasise, [term] to de-emphasise, each layer multiplying by roughly 1.1 or 0.9 — but the explicit (term:1.2) form replaced them because it is precise, readable, and easy to tune one value at a time.
"A prompt lists what you want in the picture. Weights decide which of those things the model actually fights for."
Why a structured editor beats hand-typing brackets
Typing weighted prompts by hand is fiddly and error-prone: a missing colon, an unbalanced parenthesis, or a runaway ((((term)))) can quietly distort a generation or break parsing altogether. Splitting the prompt into one row per term turns weighting into a dial you can see. You scan the whole prompt at a glance, spot which ideas are competing, and rebalance them without rewriting the text — bump the subject up, trim the lighting down, leave the rest at a neutral 1.0. Because a bare term and a 1.0 weight are identical to the model, the editor keeps the output clean, only wrapping the terms you actually changed so the prompt stays readable. The syntax it emits is the de-facto standard understood by AUTOMATIC1111, ComfyUI, Forge, and most modern Stable Diffusion front-ends, so the result drops straight into your workflow. And since everything happens locally in plain JavaScript, your prompts — which often encode a creative idea you have not shipped yet — never leave the page. Fill the box, nudge the weights, copy the result, and iterate until the emphasis matches the image in your head.
10 Facts About Prompt Weighting
A weight is a multiplier on a token's attention — above 1.0 emphasises, below 1.0 de-emphasises.
The (term:1.2) syntax was popularised by the AUTOMATIC1111 web UI and is now the de-facto standard.
A term at weight 1.0 is identical to a bare term — so it is left unwrapped.
Older syntax used brackets: ((term)) to boost (~1.1×) and [term] to reduce (~0.9×).
Small nudges matter — moving a term from 1.0 to 1.15 often recovers a dropped detail.
Over-weighting (e.g. 1.8+) can blow out colours and warp anatomy around that one idea.
You can weight any phrase, not just single words: (soft morning light:1.3) works fine.
Weighting down a term keeps it in the scene but quieter — better than deleting it outright.
The same syntax is read by ComfyUI, Forge and most modern Stable Diffusion front-ends.
This editor runs entirely in your browser — your prompts are never uploaded.
Frequently Asked Questions
- It multiplies the attention the model pays to that term. A value above 1.0 emphasises the term so it shows up more strongly in the image; a value below 1.0 de-emphasises it. The form was popularised by the AUTOMATIC1111 web UI and is now the standard way to weight prompts.
- This editor allows 0.1 to 2.0 in steps of 0.05, with 1.0 as the neutral default. Most useful tweaks live between about 0.6 and 1.5 — small nudges go a long way, and very high weights tend to over-bake the image.
- A term at weight 1.0 is identical to a bare term, so the editor leaves it unwrapped to keep the prompt clean. Only the terms you actually changed get the
(term:weight)wrapper. - The
(term:1.2)form is read by AUTOMATIC1111, ComfyUI, Forge, and most modern front-ends. A handful of older or niche tools use different conventions, so check your specific UI if a prompt behaves unexpectedly. - Yes. Each comma-separated chunk is treated as one term, so "soft morning light" becomes a single row and is wrapped as
(soft morning light:1.3)if you change its weight. - Older prompts stacked brackets — each
(())layer boosting by roughly 1.1× and each[]reducing by about 0.9×. The explicit(term:1.2)form replaced them because it sets an exact value, is easier to read, and lets you tune one term at a time. - Yes. When you re-edit the prompt box, any term whose text is unchanged keeps its weight. New terms start at the neutral default of 1.0, and removed terms simply drop off.
- Not reliably. Past roughly 1.5–1.8 the image often degrades — colours blow out, anatomy warps, and the composition collapses around that one idea. If a term is being ignored, try a small bump first, or reduce competing terms instead.
- No. The whole tool runs in your browser with plain JavaScript. Nothing you type is sent to any model, server, or third party, and nothing is saved.
- Completely free, with no account or sign-up and no limit on use. It runs in your browser and collects no data.
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