Midjourney Prompt Structure: What the Parameters Actually Do

Most Midjourney prompt guides are collections of pretty examples. This one is different: it explains the structure of a Midjourney prompt, what each parameter actually changes in the output, and why the order of your words matters. Once you understand the anatomy, you can write prompts that produce the image in your head on the first or second attempt, instead of gambling on the fifth reroll.

Midjourney prompt structure: the basic anatomy

A Midjourney prompt has two parts: the description and the parameters. The description is the plain-English sentence describing your scene, subject, style, lighting and composition. Parameters are the flags at the end that control technical behavior: --ar, --stylize, --chaos, --seed, --v and a few others.

A complete prompt looks like this:

a cinematic portrait of a neon-lit street musician in the rain, shallow depth of field, teal and orange color grade --ar 16:9 --v 6 --stylize 250 --chaos 20

Everything before the first -- is the description. Everything from the first -- onward is a parameter. The model reads the description to understand what to draw, and the parameters to understand how strictly to follow it.

What the parameters actually do

--ar: aspect ratio

--ar 16:9, --ar 1:1, --ar 9:16 or any ratio you choose. This is the only parameter that changes the shape of the image. If you are generating a hero banner for a website, use --ar 16:9; for a phone wallpaper, --ar 9:16; for a product thumbnail, --ar 1:1. Keep in mind that very extreme ratios (like --ar 1:3) work best when the subject is already vertical.

--stylize: how much Midjourney applies its own aesthetic

Range: --stylize 0 to --stylize 1000, with a default around 100. Low values (0-100) follow your text literally and produce more straightforward, photographic results. High values (400-1000) let the model add its signature artistic flair: richer color, stronger composition, more "designed" results. If your prompt describes a realistic product shot, keep stylize low. If you are doing concept art or a fashion editorial, crank it up.

--chaos: how predictable the result is

Range: --chaos 0 to --chaos 100. Chaos controls variation between the four images in a grid. At 0, the four results are close variations of the same composition. At 100, each image can be wildly different. Use low chaos when you need consistency across a batch (for example, when building a character set), and high chaos when you are exploring ideas and want surprises.

--seed: reproducibility

Every generation has a seed number that determines the starting noise. If you find an image you love and want to tweak it, re-run with the same --seed value to keep the base composition stable while you adjust other parameters. Without a fixed seed, every run is different even with the same prompt.

--v: the model version

Different model versions interpret prompts differently. If a prompt worked on version 5 but feels flat on the current version, add --v 5 (or the version you prefer) explicitly. Your prompt structure is not a universal contract; it is a conversation with a specific version of the model.

--no: what to exclude

Negative hints like --no text, watermark, extra fingers reduce the chance of unwanted elements. It is not a guarantee, so keep descriptions positive too: instead of "no cluttered background", say "clean minimal background" and reinforce it with --no cluttered.

Why prompt order matters

Midjourney weights the beginning of the description more heavily than the end. The first words carry the most influence, so the subject should come first, followed by the environment, then style and technical details. Compare:

• a leather armchair in a sunlit reading room, photorealistic, soft shadows — subject first, environment second.
• photorealistic, soft shadows, sunlit reading room, leather armchair — the model has to guess what the subject is, and the result drifts.

If a specific element keeps disappearing from your images, move it earlier in the prompt and remove competing details.

A reliable prompt structure you can reuse

After testing dozens of combinations, a dependable skeleton is:

1. Subject: what the image is about ("a ceramic teapot").
2. Action or state: what it is doing ("steaming gently").
3. Environment: where it is ("on a wooden table by a rainy window").
4. Lighting: the mood ("soft morning light, warm tones").
5. Style: the visual language ("product photography, shallow depth of field").
6. Parameters: shape and behavior ("--ar 4:3 --stylize 150 --seed 42").

This order keeps the model focused on what matters and leaves the parameters to fine-tune the output. For scenes that need a recognizable subject, lock the --seed and keep --chaos low.

Common mistakes that break prompt structure

The most expensive mistakes are silent: the image looks fine, but it is not what you asked for.

• Burying the subject at the end. The model de-weights late words, so your main subject disappears or mutates.
• Overloading with adjectives. Five style words fight each other. Pick one dominant style and one lighting cue.
• Conflicting parameters. A low --stylize with a highly stylized description pulls in two directions. Match the parameter to the description.
• Forgetting --ar. The default square crop can ruin a composition designed for a banner. Always declare the ratio.
• Changing seeds mid-iteration. You cannot compare two variations if both use different random noise. Fix the seed, then vary one variable at a time.

Putting it into practice

Now apply the structure to real work. If you need a consistent character across multiple images, start from a template that fixes the subject order and the seed, then vary the environment — the Midjourney Character Consistency Pack is built exactly for this workflow. For cinematic scenery, study how the Cinematic Landscape Master prompt orders environment, lighting and style. And if you generate marketing assets regularly, the Product Ad Backgrounds prompt shows a production-ready structure you can adapt to any brand.

Mastering Midjourney prompt structure is a small upfront investment that pays back in every batch: fewer rerolls, fewer wasted credits, and images that match the brief instead of resembling it. Write the subject first, declare your parameters deliberately, fix the seed when you iterate, and you will get the model to do what you mean — not what it guessed.