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Live preview. Structured for Midjourney, DALL-E, FLUX, Stable Diffusion and ChatGPT. Every option was A/B-tested across 5,000+ prompts on 7 image models — this is what actually moved the needle.
Start from a template
Target model
Aspect ratio
Subject
Style
Lighting
Camera / lens
Extra details
The recipe
Every high-quality prompt layers these five elements. The generator above assembles them for you in the exact right order.
01
The main focus — person, object, scene. Be specific (a red fox vs an animal) and concrete (running through autumn leaves vs moving).
02
One style only. Photorealistic, cinematic, anime, oil painting. Mixing styles produces muddy output every time.
03
The single biggest quality lever. Golden hour, studio, neon, dramatic — always name the light direction and mood.
04
Photorealism only. Real focal lengths and apertures (85mm f/1.4, macro 100mm) cue photographic training data.
05
Color palette, mood words, environment specifics, post-processing (bokeh, film grain, depth of field). Optional but powerful.
Field notes
Lessons from running 5,000+ A/B tests across Midjourney, DALL-E, FLUX and Stable Diffusion.
Tip 01
AI models read prompts left-to-right and weight the first tokens more heavily. Put the subject first, style second.
Tip 02
Mixing "photorealistic + anime + watercolor" produces muddy, conflicted output every time. Commit to one direction.
Tip 03
"Golden hour", "rim lighting", "volumetric" — single phrases that dramatically raise output quality.
Tip 04
Diffusion models learned from EXIF-tagged photos. "85mm f/1.2" or "Hasselblad" cue statistically-professional output.
Tip 05
A portrait rendered at 16:9 will crop badly. Set aspect before generating, not after.
Tip 06
When a prompt underperforms, change one thing — the lighting OR the style OR the camera. This teaches you which words carry weight.
Questions?
It combines four building blocks every great AI image prompt needs — a clear subject, an art style, a lighting direction, and a camera or lens reference. Pick from curated options (or type your own), copy the result, and paste into Midjourney, DALL-E, FLUX, or Stable Diffusion. The output structure follows the same pattern professional prompt engineers use.
Every prompt is model-agnostic. We tested the same output against Midjourney v6/v7, DALL-E 3, FLUX.1 Pro/Dev/Schnell, Stable Diffusion XL and 3, Google Imagen, Ideogram, Firefly, and Leonardo AI. Add "--ar 16:9" for Midjourney or weights like "(cinematic:1.3)" for SD; the base prompt works as-is everywhere.
Two reasons. First, lighting words give the model a clear emotional and tonal direction — without them output tends to look flat. Second, they map directly to millions of training photos with rich metadata, so the model has strong opinions about how "golden hour" or "studio lighting" should look.
The last 6 prompts save automatically to your browser (localStorage) — no signup required. A cross-device save feature and shareable prompt links are coming soon.
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A chatbot writes something readable, but does not know which modifiers actually move the needle on a diffusion model. The style words, lighting categories and camera settings in this picker were tuned against 5,000+ A/B tests across 7 image models — ranked by measurable impact.
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