Generating Images and Videos in Neiron AI: What to Prepare Before Requesting

Generating images and videos requires more preparation than a simple text request. If a user writes “make a pretty picture” or “make a video for an ad,” the result will depend on the model's random interpretations. A more reliable approach is to describe in advance the goal, audience, scene, format, constraints, and evaluation criteria. In Neiron AI, there are dedicated public endpoints for such scenarios: /images and /videos, as well as tariffs and generation packages that need to be considered before starting a series of experiments.

For images, the fact-check database lists Nano Banana, Nano Banana Pro, and GPT Image 2. Nano Banana is described as a model for quick images from descriptions and variations based on photos. Nano Banana Pro is associated with quality modes 1K, 2K, or 4K. GPT Image 2 creates and edits images, including scenarios with a single source photo. These are permissible facts. It is not permissible to promise that any model will create a commercially ready banner, boost conversion, or replace a designer. It is safer to explain how to prepare a request and evaluate the result.

A good image request includes: subject, action, environment, style, angle, color, format, and prohibitions. For example: “create an image for a cover article about an AI platform: a desk, laptop, abstract model cards, calm blue and violet shades, no third-party brand logos, horizontal format.” If an image based on a photo is needed, specify what can be changed and what must remain. If the model supports quality selection, choose it deliberately after the first attempt, not after ten random tries.

For videos, the database lists Veo 3.1, Seedance 2.0, Grok Imagine, Wan 2.6, and Kling Motion. Veo 3.1 is used for short videos with sound and speech. Seedance 2.0 supports quick videos and scenarios with references. Grok Imagine is used for quick creative videos. Wan 2.6 is suitable for videos in different frame formats and durations. Kling Motion is used for motion templates and photo dance scenarios. These descriptions help in selecting a direction but are not a promise of a specific visual result.

A video request should describe a sequence. Specify the first frame, action, camera movement, object movement, duration, mood, background, sound or speech if the scenario supports it. For a social media clip, it is useful to decide in advance if a vertical format, a single character, text overlays, or product demonstration is needed. If the goal is marketing material, do not claim in the article “high-converting.” Instead, write: prepare several variants, show them to an editor, check meaning, legal restrictions, brand fit, and technical quality.

Before generating media, check limits. Subscriptions Neuron Lite, Neuron Max, and Neuron Mega Max differ in the number of images per day and videos per month. There are one-time packages for image and video generation. For intensive work with Nano Banana, there are separate plans: Nano Banana and Nano Banana x2. This is important because media generations typically consume more quickly than text requests. First, formulate the idea in text, then make a trial version, correct the request, and only then run a series.

A separate issue is source materials. If you upload a photo, text, file, or other content, ensure you have the right to use it in AI tools. The privacy database covers user content, attached files, generation results, and AI model providers. Therefore, do not send personal documents, client commercial materials, or images of people without understanding rights and consents. For a public article, it is sufficient to honestly warn: check rights for sources and results before publication.

After generation, evaluate the result using a checklist. For an image: does the subject match, are there unnecessary details, is the format suitable, is the composition readable, have foreign logos appeared, is the text within the image correct. For a video: is the first frame clear, is the movement smooth, are there unwanted artifacts, does the duration match, does the clip contradict the task. If the result goes into advertising or a public channel, add a manual editorial review.

In the article, it is useful to link media scenarios to internal pages. /images leads to image generation, /videos to video generation, /pricing to limits and packages, /support to questions about billing, account, and generations, /news/articles to future guides. This makes the material practical and prevents it from being a repetition of a raw draft.

Mini-template for editors and authors

Before launching an image generation, fill in five lines: image purpose, subject, environment, format, constraints. For example, for an article cover, the purpose might be “explain the AI platform topic,” subject — “laptop and model cards,” environment — “workspace without recognizable brands,” format — “horizontal cover,” constraints — “no real people’s faces and no third-party logos.” Such a template helps avoid wasting generations on model guessing.

For a video, use a similar scheme but add movement: first frame, action, scene change, final frame, sound or speech. If the scenario involves a product, do not ask the model to show an interface that is not in the approved public layout. Instead, use an abstract demonstration of the idea, and prepare exact screenshots separately through product design and legal review.

After obtaining the result, save not only the file but also the request. This allows repeating a successful generation, explaining to an editor why the result looks that way, and fixing the next version faster. For public publication, add a check: no distorted text, random logos, erroneous interfaces, unverified medical, financial, or legal hints. If in doubt, do not publish the result and consult the editor or content owner.

FAQ

Can I use external images from an export file? In this editorial review, they are not used: rights and relevance were not verified through platform media checks.

Which model is suitable for images? Neiron AI lists Nano Banana, Nano Banana Pro, and GPT Image 2. The choice depends on the scenario and availability in the interface.

How to avoid wasting generations? First, prepare a text description, then make a trial version, correct the request, and only then run a series.

How to save successful requests

After a good generation, save not only the final file but also the request itself: scene description, style, format, constraints, and edits after the first attempt. This helps repeat the approach later and understand what exactly influenced the result. For images, it is useful to separately store composition and subject details; for videos, movement, duration, background, and final frame. Such an archive does not guarantee the same result but makes working with generations calmer and more predictable.