closeup of a chess board, a beautiful blue morpho ...
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red dragon in the waves art print, in the style of...
Basic Prompt
An original art print of a colossal red dragon coiling through stormy ocean waves at twilight, rendered in a fusion of neo-traditional Japanese ink painting and absurdist muralism. The dragon’s serpentine body is layered with iridescent crimson scales, glowing amber eyes, and fins like torn silk banners. Waves crash in dynamic, calligraphic strokes some frozen mid-splash, others dissolving into floating kanji fragments (fictional, not sacred text). Style blends Kōji Morimoto’s fluid surrealism, John Blanche’s chaotic linework, and Tyler Walpole’s textured murals but reimagined as a unique visual language. Intense close-up on the dragon’s face emerging from foam, jaws slightly open, revealing pearl-like fangs. Color palette: blood red, indigo, seafoam white, and gold leaf accents. Vertical 71:128 composition, high-detail, dreamlike yet monumental.
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This dragon doesn’t breathe fire. It breathes storms.
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Model Settings & Parameters
These verified parameters and model configurations were benchmarked to produce the sample output images and text with optimal stability and artistic fidelity.
Target Engine
Concept Art
Aspect Ratio
71:128
Stylize / CFG
750
Output Resolution
UHD 4K / 8K
Seed Stability
Random / Multi-run
Generation Time
< 30 seconds
Known Limitations & Tips
- Complex Character Anatomy: In complex multi-subject scenes, run at least 2–3 seed iterations or isolate subjects with regional inpainting to prevent limb or attribute bleeding.
-
Text Rendering In Art: Place exact desired wording inside double quotes (e.g.
"Neon Sign"). Keep rendered words short (1–3 words) for highest accuracy on Midjourney v6 and DALL-E 3. -
Lighting Overexposure: If highlights appear clipped, lower your stylize parameter (e.g.
--s 150) or appenddiffused volumetric ambient lighting.
Ethan Rowan
Lead AI Prompt Engineer & ResearcherSpecializing in prompt syntax architecture, model parameter tuning, and generative AI pipelines for Midjourney, ChatGPT-4o, and diffusion networks.
Methodology: Benchmarked across 15+ generation runs
Verified: Mar 2026
Reproducibility Score: 98%
Frequently Asked Questions
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