dragon ball super wallpaper, in the style of dark ...

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dragon ball super wallpaper, in the style of dark ...

dragon ball super wallpaper, in the style of dark ...

Tested & Verified Anime Commercial License
Basic Prompt

A vertical 9:16 wallpaper-style artwork of an original cosmic warrior mid-transformation, rendered in a fusion of photo-realistic detail and expressive palette knife technique. His body radiates dark golden energy crackling with raw emotion as dark yellow and burnt beige light erupts from his core, illuminating swirling cosmic dust. Face contorted in determination, eyes blazing with inner fire. Background blends abstract Hurufiyya-inspired patterns (geometric Arabic calligraphy fragments symbolizing “power” and “fate”) with Yombe art influences textured earth tones, ancestral motifs, and spiritual symbolism. Heavy impasto strokes carve light and motion; realistic light physics show energy refracting through atmospheric particles. Mood: transcendent, fierce, mythic.

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He isn’t copying a hero he’s becoming one.

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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 Anime
Aspect Ratio 9:16
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 append diffused volumetric ambient lighting.
Ethan Rowan

Ethan Rowan

Lead AI Prompt Engineer & Researcher

Specializing 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: Feb 2026 Reproducibility Score: 98%

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