Image Generation Terms for Neiron AI Beginners

When you start working with image generation, the first challenge is language. Not technical programming language, but a working vocabulary: what is a “prompt”, why is the result unpredictable, what is “style” in the context of generation, and how to describe what you want.

This article is a practical glossary for beginners. No academic definitions—only what helps you write your first prompt and understand why the result turned out the way it did.

Prompt

A prompt is a text description you send to the model to generate an image. Essentially, it is a technical task for an artist—except the artist is an algorithm.

A good prompt is specific. A bad prompt is too general.

Examples:

• Bad: “beautiful landscape”

• Better: “mountain landscape at sunset, fog in the valley, neutral gray-blue tones, realistic style”

The more specific the description of the object, mood, style, and details, the closer the result is to expectations. This is not a guarantee, but a more predictable direction.

Object and Background

Two basic elements of any image: the object (what is in focus) and the background (what is behind it).

If you do not specify the object explicitly, the model will choose one itself—and it may not be what you wanted. If you do not specify the background, it will also be chosen automatically.

A simple rule: always describe both elements explicitly. “A cat on a white background” and “a cat in a winter garden” are fundamentally different images, even though the object is the same.

Style

Style is the visual language of the image. Realism, illustration, oil painting, watercolor, anime, photography, 3D render, pixel art—these are all different styles.

If you do not specify a style, the model will choose a default one. It might work, or it might not—depends on the task.

A few useful style descriptions:

• “realistic photo” — result as close to reality as possible

• “digital illustration” — bright, sharp, with smooth contours

• “watercolor” — soft transitions, lightness, artistry

• “minimalist” — fewer details, more space

• “vintage poster” — stylization for a specific era

You can combine style with other elements: “realistic photo of a small coffee shop early morning, warm light, empty tables.”

Mood and Atmosphere

Mood is the emotional tone of the image. Calm, tension, joy, melancholy, mysticism—these describe feelings, not objects.

Adding mood to a prompt often changes the result drastically, even if the object description remains the same.

Examples:

• “city street” — neutral result

• “city street in rain, late evening, warm lights in the distance” — now there is atmosphere

Angle and Perspective

Angle is the point from which we look at the object. “Top view,” “close-up,” “panorama,” “portrait,” “first-person shot” — these are all angles.

If you do not specify an angle, the model will choose a neutral one. For most tasks, this works fine, but if you need a specific frame, describe it explicitly.

Examples:

• “cat, close-up, front view”

• “city, top view, panorama”

• “table with coffee, angle 45 degrees”

Color Palette

Colors in a prompt can be described in any way: “blue,” “warm tones,” “monochrome,” “bright contrasting colors,” “muted pastel tones.”

Color descriptions help control mood and style. Often, the color description decides how well the result matches the task.

Reference and Stylization

Reference is an indication of a specific visual style or direction you want to emulate. “In the style of a Japanese woodblock print,” “like a retro 60s postcard,” “in the spirit of Soviet posters.”

Important: reference is stylization, not copying. The model does not reproduce others’ works literally; it creates something new in a similar stylistic logic.

Negative Prompt (What Not to Include)

Many models allow you to specify what should not be in the image. This is called a negative prompt. For example: “without people,” “without text,” “without blur.”

Not all interfaces provide a separate field for negative prompts. Sometimes you can add clarification in the main description: “landscape without people and buildings.”

Resolution and Format

Resolution affects the size and detail of the image. Different models offer different options: square (1:1), horizontal (16:9), vertical (9:16), and other aspect ratios.

Choosing a format depends on the task:

• square is convenient for social media posts

• horizontal for covers and banners

• vertical for stories and mobile formats

If you don’t specify a format, the model will choose the default, usually a square.

Iteration: How to Improve Results

Rarely does the first prompt give exactly what you want. This is normal. The process of working with image generation is iteration: try → evaluate → adjust the prompt → try again.

What is useful to do with each iteration:

1. Note what exactly you didn’t like in the result.

2. Add specificity where it was missing.

3. Remove extraneous words that could confuse the model.

4. Change one element at a time, not everything at once.

This approach helps you understand what influences the result and find the desired variant faster.

Generation Limits

Each plan on the platform includes a certain number of image generations. One generation equals one request, regardless of how many variants the model returns.

An iterative approach helps use limits wisely: instead of running a request several times with minor changes, it is better to thoroughly think through the prompt first.

On the pricing page you can check what is included in your plan. More details about image generations on the images page.

Nano Banana and GPT Image 2

The Neiron AI platform offers several models for image generation, including Nano Banana, Nano Banana Pro, and GPT Image 2. Each has its own characteristics in style of results and generation speed.

Practical tip: try the same prompt in different models and compare the results. This is a quick way to understand which model is closer to your preferred style.

Checklist for Your First Prompt

Before you send a prompt, check:

• Is the main object specified?

• Is the background or setting described?

• Is there a style description?

• Is the angle specified (if important)?

• Is the color palette described?

• Is the mood conveyed?

If at least four out of six items are filled, the prompt is already much more specific and will give a more predictable result.

Why the Result Is Sometimes Unexpected

Image generation models interpret language in their own way. The word “big” could mean the scale of a building or a close-up. The word “old” could mean a person or a retro style.

Unexpected results are not a bug but a feature of working with language in the context of visual creation. The more specific the phrasing, the less room for interpretation, the more predictable the result.

Sometimes an unexpected result is more interesting than planned. Sometimes it is exactly what you didn’t want. In both cases, it’s important to note which prompt gave a good result and use it as a template next time.

Summary

Image generation terminology is not a complex science. It is a practical glossary of a dozen concepts that help you describe more precisely what you want. Object, background, style, mood, angle, color—these are the basic set. Once you master them, you will stop guessing why a certain result turned out that way and start managing generations consciously.