Midjourney & DALL-E Prompting: A Visual Guide

Midjourney vs DALL·E vs the rest: the Reddit verdict on what each is actually good at

After four years of image-gen iteration, the "which tool should I use?" question has clearer answers than it did in 2023. The r/midjourney, r/StableDiffusion, and r/OpenAI communities have largely stopped arguing and started specialising. Here's the settled shape of that specialisation.

What each tool is genuinely best at:

• →Midjourney remains the king of aesthetic output. The v7 models have a distinctive visual sensibility that's hard to escape and often what users want. For moodboards, concept art, editorial imagery, and anything where "looks beautiful" matters more than "matches the prompt literally," Midjourney wins. The Midjourney prompt guide has caught up with community best practices at last.
• →DALL·E 3 (via ChatGPT or the API) is the best at prompt adherence and text-in-image. Ask for "a cat holding a sign that says 'hello world' in red sans-serif," and DALL·E is by far the most likely to deliver it accurately. For illustration tasks with specific content requirements, this matters enormously.
• →Stable Diffusion / Flux / local models win on customisation and volume. LoRAs, ControlNet, specific style training, NSFW use cases (for those users), batch generation — nothing beats local inference on a decent GPU. The tooling (ComfyUI, Forge, A1111) is intimidating but the ceiling is higher.
• →Google Imagen / Gemini's image gen is catching up fast and integrates well with Google's ecosystem, but doesn't yet displace any of the above in its own specialty.

What the community warns about:

• →Style consistency across generations is still the unsolved problem. Even with character reference tools, getting the same character in 10 different poses without drift remains hard. Workflows involving image-to-image and consistent LoRAs are the current best practice.
• →Prompt templates posted in tutorials are often outdated within months. Each model version changes what works. Treat prompt advice older than 6 months as a starting hypothesis, not a formula.

The practical selection pattern: pick Midjourney for beauty, DALL·E for accuracy, Stable Diffusion for control. Don't buy into any "one model wins" narrative — the tools are differentiating, not converging.

How Image Prompts Differ from Text Prompts

When prompting for text, you're having a conversation. When prompting for images, you're describing a scene for an AI to visualize.

Text Prompt (ChatGPT)

Explain how photosynthesis works

Image Prompt (Midjourney/DALL-E)

A peaceful forest clearing at golden hour, sunlight streaming 
through leaves, photorealistic, 8K detail, National Geographic style

Image prompts are descriptive, not conversational.

The Anatomy of an Image Prompt

Effective image prompts typically include:

1. Subject

What's the main focus?

"A lone astronaut on a red desert planet"

2. Style

What aesthetic are you going for?

"oil painting style, impressionist, Monet-inspired"

3. Details

Specifics that enrich the image:

"wearing a weathered spacesuit, dust on visor"

4. Mood/Atmosphere

The feeling you want:

"melancholic, vast emptiness, isolation"

5. Technical Specifications

Quality and format cues:

"8K resolution, cinematic lighting, shallow depth of field"

A Prompt Formula

Here's a simple formula to start:

[Subject] + [Style] + [Details] + [Mood] + [Technical]

Example

A wise old owl perched on an ancient book, 
fantasy illustration style, intricate feather details, 
mystical atmosphere with glowing runes, 
4K digital art, dramatic lighting

Midjourney vs. DALL-E

While both generate images from text, they have different strengths:

Knowing your tool helps you craft better prompts for it.

Keywords That Transform Images

Certain words dramatically impact output:

Quality Enhancers

• →"8K", "ultra-detailed", "high resolution"
• →"professional photography", "award-winning"
• →"masterpiece", "trending on ArtStation"

Style Keywords

• →"cyberpunk", "steampunk", "art deco"
• →"minimalist", "maximalist", "baroque"
• →"watercolor", "oil painting", "digital art"

Lighting

• →"golden hour", "blue hour", "neon lighting"
• →"dramatic shadows", "soft diffused light"
• →"rim lighting", "volumetric lighting"

Camera/Perspective

• →"aerial view", "macro shot", "wide angle"
• →"shallow depth of field", "bokeh"
• →"fisheye lens", "35mm photograph"

Common Mistakes to Avoid

1. Being Too Vague

❌ "A nice picture of a cat" ✅ "A fluffy Persian cat sleeping on a velvet cushion, golden sunlight, cozy atmosphere"

2. Conflicting Instructions

❌ "Dark and bright, simple and complex" ✅ Pick a consistent direction

3. Too Many Subjects

❌ "A dragon fighting a robot while a wizard watches and there's a spaceship and also a beach" ✅ Focus on one main subject

4. Ignoring Negative Prompts

Many tools let you specify what NOT to include. Use this to avoid common artifacts.

The Iterative Process

Great images rarely come from the first prompt. The process is:

1. →Generate with your initial prompt
2. →Analyze what worked and what didn't
3. →Refine the prompt based on observations
4. →Repeat until you get what you want

Think of it as a conversation with the AI through images.

Key Takeaways

1. →Image prompts are descriptive, not conversational
2. →Include subject, style, details, mood, and technical specs
3. →Specific keywords dramatically impact output quality
4. →Different tools have different strengths
5. →Great results require iteration and refinement

Ready to Master Visual AI?

This article covered the what and why of image prompting. But creating consistent, branded visual content requires deeper techniques.

In our Module 7, Multimodal & Creative Prompting, you'll learn:

• →Advanced techniques for consistent character design
• →Creating brand-aligned visual content
• →Working with style references and image-to-image
• →Combining text and image AI in workflows
• →Prompt engineering for video generation

→ Explore Module 7: Multimodal & Creative Prompting