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Create a Clean 2×2 Grid Composition Where

@Naiknelofar788··65

Create a clean 2×2 grid composition where each quadrant represents a different iconic city—Paris, New York, Tokyo, and London—designed as a symmetrical spatial map-style diorama in

Create a Clean 2×2 Grid Composition Where — image 1
Create a Clean 2×2 Grid Composition Where — image 2
Prompt
Create a clean 2×2 grid composition where each quadrant represents a different iconic city—Paris, New York, Tokyo, and London—designed as a symmetrical spatial map-style diorama in a strict matte papercraft and cardboard aesthetic. Use only kraft paper, folded paper, and cut cardboard textures with visible edges and slight imperfections; avoid any gloss, plastic, or realistic materials so everything feels handmade. Set the entire scene on a crumpled white paper background with soft studio lighting and subtle shadows. In each quadrant, include simplified paper-cut monuments (Eiffel Tower for Paris, Statue of Liberty with skyline for New York, Tokyo Tower or a pagoda for Tokyo, and Big Ben with Tower Bridge for London), along with a clearly twisted cardboard Möbius loop road carrying tiny paper cars and subtly labeled “mobius loop.” Beneath the loop, add a blue folded paper river, with minimal paper trees and buildings to create depth. Across the bottom, include a continuous accordion-folded newspaper base with visible print texture. Add small floating paper clouds and layered cut-paper depth (foreground, midground, background), keeping the composition centered, balanced, and consistent in scale so the entire piece looks like a handcrafted miniature model floating in clean negative space.

How to Use This Prompt

  1. Copy the full prompt text with the copy button above.
  2. Replace any [bracketed] placeholders with your own subject, scene, or details.
  3. Paste it into Gemini / Nano Banana Pro — or hit "Try this Prompt" above to generate here for free — then tweak the wording against the example images.

Style Notes

Photo
Asks the model for photorealistic output — natural lighting, believable skin and materials, camera-like depth of field — rather than illustration or 3D looks.
Typography
Text is part of the artwork. Modern models like Nano Banana Pro can render legible styled lettering, but keep the exact wording short and quoted in the prompt.
Logo / Icon
Symbol-first design — simple geometry that survives being scaled down, flat color, strong silhouette. Expect to vectorize the output before real use.
Minimalist
Few elements, generous negative space, restrained palette — the model is told to leave things out, which makes composition errors much less likely.
Vehicle
Automotive rendering — reflective paint, wheel and grille detail, low dramatic angles borrowed from car commercials.
Architecture
Buildings and structures with believable perspective and materials — wide lenses, strong leading lines, attention to light on facades.
Studio Lighting
Controlled artificial light (softboxes, rim lights) — clean shadows and highlight control, the standard look of commercial portrait and product work.
Social Media Post
Composition and aspect ratio tuned for feeds (Instagram, X, Xiaohongshu): bold focal subject, room for overlay text, colors that survive small screens.
Marketing Campaign
Ad-ready imagery: clear product or message hierarchy, space reserved for copy and logos, and a polished commercial finish.

FAQ

How do I use this prompt with Gemini (Nano Banana Pro)?

Copy the full prompt with the copy button above, paste it into Gemini or any Nano Banana Pro-powered tool, and compare your result with the example images on this page. You can also click "Try this Prompt" to generate directly on this site — free daily generations, no sign-up needed.

Can I customize "Create a Clean 2×2 Grid Composition Where"?

Yes. Anything in [brackets] is a placeholder meant to be replaced with your own subject or details, and you can freely adjust subject, lighting, or style keywords — small wording changes often produce noticeably different results.

Which AI models does this prompt work with?

It was originally shared for Google's Gemini image models (including Nano Banana Pro). Most text-to-image models will understand it too, though composition and text rendering quality vary by model.

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