If you mention a specific AI model in an article or publication, one question is mandatory before publication: is this model actually available to users right now? Not 'planned to be added', not 'was available three months ago', but right now. The check takes a few minutes, but saves you from a situation where a reader comes to the platform and doesn't find what you wrote about.

Why This Matters for Authors and Editors

AI models appear, get updated, and sometimes become temporarily unavailable. Tariff conditions also change: a model may be in the catalog but only available at a certain subscription level. If an article is based on outdated information or a news draft without verification, the reader gets false expectations.

This is especially critical for publications with practical instructions. When an author writes 'open the section and select model X,' they are essentially making a promise. If model X is unavailable, the article misleads the user, undermining trust in the publication or author.

Step 1: Check the Current Platform Catalog

The first and main step is to open the platform interface in its current state. Do not rely on press releases, tweets, or other authors' articles. The model catalog in the interface reflects what is available here and now.

On Neiron AI, text models are available in the main chat, media tools in the /images and /videos sections. If the model you are writing about is not displayed in the interface, it is either temporarily unavailable, tariff-restricted, or the information you are using is outdated.

Step 2: Clarify Tariff Restrictions

A model being in the catalog does not mean it is available to all users. Some models require a specific subscription level. Before writing 'available in Neiron AI,' check the /pricing page: which models and features are included in each tariff.

If a model is only available on a paid tariff, this must be explicitly stated in the article. Phrases like 'available for subscribers' or 'requires tariff X' give the reader accurate information and reduce disappointment from unmet expectations.

Step 3: Distinguish Fact from Announcement

When writing about a model, it is important to clearly distinguish two types of statements:

Fact: 'Gemini is available in the Neiron AI catalog' — a statement that can be verified right now by opening the interface.

Announcement or assumption: 'A new version of Grok will appear soon,' 'plan to add X' — statements about the future that are not facts about the current state of the platform.

Mixing these two types in one sentence is dangerous. The reader does not always notice the word 'soon' or 'planned' — they perceive the statement as a current fact and form expectations.

Step 4: Check the Date of Your Source

Information about AI updates becomes outdated quickly. News published three months ago may describe a state that has changed several times since. Always check the publication date of the source and compare it with the current state of the platform.

If you cannot determine the exact date a model was added, do not specify it. It is much safer to write 'in the current Neiron AI catalog, the following are available' than to give an incorrect date that contradicts official information.

Step 5: Consult Official Support Pages

If you are unsure about the availability of a feature or model, the /support page is your next resource. There you can find up-to-date information about platform capabilities or ask a clarifying question directly.

This is especially important for media models. The availability of Veo 3.1, Seedance, Kling, Wan, or Nano Banana may vary depending on tariff and current status. Check this in the interface or through support, not by articles from third parties.

How to Properly Phrase Mentions of Models

After verification, it is important to correctly phrase the mention of the model in the article. A few practical rules:

Use the present tense with caveats. Instead of 'Gemini is available,' it is safer to write 'at the time of publication, Gemini is available in the catalog' or 'in the current version of the platform.' This signals to the reader that the information is current at the time of writing.

Add links to verifiable pages. If you write about tariffs, link to /pricing. If about images, to /images; if about video, to /videos. This allows the reader to verify currency themselves.

Do not list all models unnecessarily. A long list of models in an article looks like marketing, not useful information. Mention only those models directly related to the topic of the material.

Do not make promises on behalf of the platform. You are the article author, not a representative of Neiron AI. Any statements about plans, updates, or future features must be supported by an official source.

Red Flags When Preparing Material About Models

Before final editing, review the article for these signals:

Mention of a specific model version without citing a source
Claims about the date a model was added without a link
Phrases like 'universal model,' 'the most powerful,' 'outperforms competitors' without a comparison methodology
Promises of results ('with this model you will get...')
Information about tariffs without a link to the current pricing page

The presence of any of these elements is a signal to check or rephrase.

How to Update Articles When the Catalog Changes

Even a well-checked article can become outdated. If you regularly write about AI platforms, it's worth setting up an update process:

Set a reminder to check key articles once a quarter.
Record the date of the last check in the article: 'Information is current as of [date].'
When updating, add a note about changes rather than just editing the text without a trace.
If a model disappears from the catalog, update the article or add a clarification.

This builds trust with readers and search engines: they see that the material is kept up to date.

What to Do If There Is No Time for a Full Check

If you urgently need to publish material and there is no time for a full check, the minimum option is to add an explicit statement to the article: 'Information is current at the time of publication. We recommend checking the current model catalog on the platform.' This is an honest disclaimer that shifts responsibility for currency to the source itself.

Alternatively, you can phrase the article in more general terms without mentioning specific models — talk about types of tasks (text queries, image generation, video generation) rather than specific names. Such material ages more slowly.

Summary

Verifying model availability before publication is a professional standard for authors writing about AI tools. It takes a few minutes: open the platform interface, check the current catalog, compare with the tariff page, add links to current resources. This is not bureaucracy — it is basic respect for the reader who expects to find what you wrote about.

How to Check AI Model Availability Before Publishing an Article