New Year City Poster with Silk Ribbon Landscape and Landmarks

@dotey·Apr 19, 2026·0

This prompt generates a sophisticated city promotional poster featuring a miniature figure waving a silk ribbon that transforms into a landscape of mountains and rivers, superimposed with city landmarks. The style is elegant, with double exposure, Guochao elements, and ample white space for a fresh look.

New Year City Poster with Silk Ribbon Landscape and Landmarks — image 1

Prompt

A [2026] city promotional poster, full of [New Year festive atmosphere yet elegant style]. Double exposure, composition continues the S-shaped flow; In the lower right corner of a pure white textured background, a miniature figure dressed in traditional Chinese attire is waving a long [red] silk ribbon. This red ribbon dances in the air, not only showcasing the smooth texture of silk, but also magically transforming into a magnificent mountain range and river as it floats towards the upper left. In this "river," a hand-drawn map of [Guangzhou] city with mountains, seas, and rivers is superimposed, in a national trend (Guochao) style, with scenery fully visible, grand and majestic, breathtaking. Landmark buildings of [Guangzhou] ([Guangzhou] Tower, Zhujiang New Town architectural complex, Pearl River, ancient buildings in [Guangzhou], cruise ships, Baiyun Mountain). Surrounded by clouds and mist, ethereal and dreamlike, rich in color, complex in structure, rich in detail, but due to large areas of white space, the picture still appears fresh and refined. In the lower left corner, "SPRING [2026]" and vertical promotional text are arranged, with the overall meaning "[Millennium Commercial Capital, Charming Guangzhou]". Beautiful and generous text layout, clear and complete handwriting, size 9:16.

Try this Prompt

Poster Surreal Architecture Nature Landscape Elegant Dreamy Ancient China Event Poster Marketing Campaign Social Media Post

How to Use This Prompt

Copy the full prompt text with the copy button above.
Replace any [bracketed] placeholders with your own subject, scene, or details.
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

Poster: Single-image layout designed to be read at a glance: dominant visual, title-friendly composition, high contrast for print or thumbnail.
Surreal: Deliberately impossible imagery — dream logic, scale distortions, unexpected object combinations — where the model's "mistakes" become the style.
Architecture: Buildings and structures with believable perspective and materials — wide lenses, strong leading lines, attention to light on facades.
Nature Landscape: Wide scenic composition with believable atmospherics — layered depth, weather and time-of-day cues doing most of the mood work.
Elegant: Graceful, refined mood — soft curves, muted palettes, unhurried composition; tells the model to avoid loud colors and clutter.
Marketing Campaign: Ad-ready imagery: clear product or message hierarchy, space reserved for copy and logos, and a polished commercial finish.
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.

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 "New Year City Poster with Silk Ribbon Landscape and Landmarks"?

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.