Free · Keep quality · No signup

AI Prompt Shortener — Trim Without Losing Quality

Paste any long prompt and get a shorter version that keeps the most important elements. Fewer tokens, same quality output.

Free · Same quality · No signup

VisionPrompt — AI Prompt Shortener
VisionPrompt — Prompt Shortener Balanced · General
Your long prompt
0 chars · 0 words · Ctrl+Enter to shorten
Compression level
Brief Core essence only — subject, style, primary lighting
Balanced ★ Remove redundancy, keep all distinct visual elements
Compact Aggressive — every unique element, no repetition
Shortening your prompt…
—Original words
—Shortened words
—Reduction
Before
After ✂️
Full Shortened Prompt Balanced · General

Real Examples You Can Copy

Shortening Examples — Before & After

Before (67 words)

"A beautiful highly detailed professional photograph of a majestic golden retriever dog that is very cute and fluffy sitting down in a nicely lit bright warm sunny outdoor park setting with green grass and blue sky and clouds in the background during daytime"

After (14 words)

"Golden retriever sitting in sunny park, green grass, blue sky, professional photograph"

What was removed

Redundant adjectives (beautiful, very cute, nicely lit), filler phrases (that is, in a), repeated concepts (bright/warm/sunny → sunny). Signal preserved at 79% fewer words.

How to Use This Tool

Long prompt to concise prompt in 3 steps

1
Paste your long prompt
Any length. The tool identifies high-weight elements.
2
Select target length
Light trim, standard, or compact.
3
Copy your shortened prompt
Most impactful elements preserved.

Why it works

What makes a shorter prompt still work

Not all prompt tokens carry equal weight. Removing the right ones changes nothing.

Part of the prompt tools suite — the opposite tool is the prompt expander.

✂️
Intelligent trimming
Redundant descriptors and low-weight tokens removed first.
📊
Quality preservation
Shortening stops when quality would drop.
🎯
Model-aware
Respects which elements each model weights most heavily.

Token efficiency matters for model performance and cost. This removes low-weight tokens while preserving high-impact elements.

Use case

For prompt-based API workflows where token cost matters and a 300-token prompt and a 180-token prompt produce equivalent output. The shortener trims redundant adjectives and weak modifiers while preserving the prompt’s structural anchors.

API cost optimisation · token reduction
Try it now →

FAQ

Frequently asked questions

A prompt shortener compresses long, bloated, or redundant AI image prompts into clean, concise versions. It identifies and removes repeated concepts, conflicting instructions, filler words, and unnecessary qualifiers while preserving every distinct visual element — subject, style, lighting, color, and composition.

Longer isn't always better. Prompts that are too long can cause models to ignore some elements, create conflicting interpretations, or lose focus on the core subject. Midjourney has token limits; Stable Diffusion weights early tokens more heavily; Flux benefits from dense but non-repetitive paragraphs. A concise, well-ordered prompt often outperforms a longer one.

Three levels: Brief (core essence only — subject, dominant style, primary lighting), Balanced (removes clear redundancy while preserving all distinct visual elements — the recommended default), and Compact (aggressive compression that keeps every unique element but cuts all repetition and verbose phrasing).

Yes — completely free. No signup, no limits — keep shortening as many shortened prompts as you need.

Six target platforms are supported: Midjourney v6/v7, Stable Diffusion SDXL, Flux.1, Google Gemini Imagen, Google Image FX, and Nano Banana. The shortener picks the right token compression strategy for whichever model you select.

Balanced and Compact shortening preserve all distinct visual elements — only redundancy and repetition are removed. Brief shortening may change the output by focusing on fewer elements. The before/after comparison lets you see exactly what was removed before generating.

Priority order: main subject and action, dominant artistic style, primary lighting setup, color palette (if distinctive), composition and framing, mood and atmosphere. Generic quality words that don't carry specific visual meaning are removed first.

Yes — select Midjourney as the target model and the shortener preserves essential parameters (--v 6, --ar, --style) while compressing the text portion. Redundant or conflicting parameters are rationalized into the most appropriate set.

Related tools

Continue your workflow

🏠 Prompt Tools Hub Browse all tools. 📈 Prompt Expander Expand short prompts. ✏️ Prompt Rewriter Fix failing prompts. ✨ Prompt Enhancer Improve any prompt.

How to shorten a prompt without losing it

Past a certain length, image-generation prompts start hurting more than helping. The model has too many constraints to satisfy simultaneously and starts dropping elements — and you have less control over which elements get dropped. The shortener is the inverse of the expander: when a prompt is bloated, this tool cuts it back to what’s actually carrying weight. Below is a short editorial primer on when to shorten, what to cut, and what to keep.

The token sweet spot is model-specific

Each major image model has a length where output starts degrading:

Nano Banana: past 30 tokens, output drops noticeably.

Midjourney: past 75 tokens, the model starts ignoring later modifiers.

SDXL: past 150 tokens, weight stacking interactions collapse and modifiers fight each other.

Flux: handles 150-200 tokens cleanly; past 200 starts losing coherence.

Gemini Imagen: handles long prompts technically, but failure mode is over-specification — output flattens because the model is averaging too many constraints.

If your prompt is past these thresholds and producing inconsistent or generic output, length is the most likely cause. The tool reads your prompt and cuts to the model-specific sweet spot.

Three categories of word that earn their space

Subject anchors. The thing the prompt is about. Always keeps. Usually 1-3 tokens.

One strong style anchor. A medium (photography / illustration / painting) plus one stylistic descriptor (cinematic / impressionist / film noir). Together usually 2-4 tokens.

One strong lighting cue. Direction or quality of light (golden hour / hard side-lighting / overcast). Usually 2-3 tokens.

Most working prompts can be reduced to this skeleton plus one or two specific details. Everything else is decoration that the model averages out.

What to cut first

Evaluative adjectives. “Beautiful,” “stunning,” “magnificent,” “breathtaking,” “incredible.” The model has no consistent visual mapping for these. Cut all of them.

Quality boosters that don’t apply to your model. masterpiece, best quality, 8k, highly detailed work on SD 1.5 and SDXL but do nothing on Flux or Gemini and minimal on Midjourney v6+.

Stacked mood words. If three or more atmospheric descriptors appear (“melancholic, dreamy, atmospheric, contemplative”), pick the strongest one. Stacking them confuses the model.

Redundant style references. “Photographic, photorealistic, photo-style, 35mm photography” all say the same thing. Keep one.

Hedging language. “Possibly,” “appears to,” “might be,” “sort of.” Image generators don’t handle uncertainty markers well.

What to never cut

The subject. Even if it’s long, the subject specification is the foundation. Trim around it, never through it.

Negative-prompt items on Stable Diffusion. If you’re running SD with a negative prompt, anatomy and quality items in the negative are doing real work. Cutting the negative usually hurts output more than cutting the positive.

Aspect ratio or dimension specifications. Whether it’s a Midjourney parameter (--ar 16:9) or implicit in the prompt structure, the framing instruction is non-negotiable.

For prompts that are too short rather than too long, see the prompt expander. For structurally-wrong prompts, the prompt rewriter. To diagnose what’s actually wrong before deciding which tool to use, the prompt analyzer.