Prompt Engineering Guide
Midjourney vs Flux vs GPT-Image
prompt formatting guide.
Why copying a comma-stuffed Stable Diffusion tag list into Flux or GPT-Image-2 produces stiff results—and how to translate any visual concept across architectures.
Core rule
Match your prompt grammar to the model's text encoder
Every AI image generator reads your prompt through a specific text encoder before denoising pixels. Stable Diffusion 1.5 and SDXL rely on CLIP tokenizers that weight short, comma-separated phrases. Flux.1 and GPT-Image-2 use large T5 and multimodal language encoders that parse full spatial relationships, prepositions, and quoted typography.
- Midjourney: Subject + environment + lens + lighting + aesthetic tokens + trailing --ar / --stylize flags
- Flux & GPT-Image-2: Natural declarative sentences specifying foreground, background, and exact text in quotes
- Stable Diffusion (SDXL): Weighted descriptor tags paired with an explicit Negative Prompt
Side-by-side syntax rules by model family
| Rule | Midjourney v6 / v8 | Flux.1 / GPT-Image-2 | Stable Diffusion XL |
|---|---|---|---|
| Ideal length | 35 – 75 words + flags | 60 – 140 words (prose) | 25 – 60 comma-separated tags |
| In-image text rendering | Put exact words in "quotes" + low --stylize | Describe font style, placement & "exact text" | Weak without ControlNet |
| Negative prompts | Use --no flag sparingly | Avoid; state what you want positively | Essential (blurry, bad anatomy, watermark) |