When AI tools become part of your workflow, sooner or later the question arises: how much are we spending and on what? At first glance, the answer seems simple—just look at the subscription total. But that's just the top level. Real cost tracking starts with understanding how you and your team use AI tools in detail: how many requests go into tasks, where retries happen, and what consumes generations without real results.

This article is a practical way to build such tracking without hypothetical cases or marketing numbers. Instead of promises of savings—concrete steps to analyze your own usage.

AI Costs Aren't Just the Subscription Price

The first mistake in cost estimation is only counting the plan price. But real costs add up differently:

Request limits—each text request consumes one limit. If you rephrase the same question five times, you've used five limit units.
Image generations—a separate counter that depletes with each generation, regardless of whether you liked the result.
Video generations—the most resource-intensive type of generation. A bad prompt with attempts to recreate a scene can quickly exhaust your quota.
Unused requests—if your plan includes a bundle and you used only a third, that's still a cost—just an unnoticed one.

To see the real picture, you need to look not only at the bill but also at actual consumption patterns. On the pricing page of Neiron AI, you can check what's included in your current plan.

Step 1: Describe Your Tasks Before Counting Limits

Before diving into statistics, it's helpful to list the tasks you regularly solve with AI tools. These might include:

text drafts: articles, letters, posts
information analysis: summaries, conclusions from materials
image generation: illustrations, design options
video generation: short clips, animations
code questions: explaining snippets, suggesting fixes
search and research: Deep Research, web search via Perplexity

Once the tasks are written down, it becomes clear where usage is concentrated. Often, a significant portion of requests goes to 2–3 tasks, while the rest are rare or experimental.

Step 2: Categorize Tasks by Generation Type

Each task has its own consumption pattern:

Text tasks—consume chat model requests. This includes all dialogues, text analysis, drafting, and answering questions. Cost depends on the number of calls, but is usually lower than media generations.

Image generations—one result costs one generation, regardless of prompt complexity. If you often try multiple variants using DALL-E, GPT Image 2, or Nano Banana, it quickly adds up to a significant portion of your limit budget.

Video generations—the most resource-heavy type. One generation with Veo 3.1, Kling, or Seedance can take several minutes and cost multiple limit units. If a video doesn't come out right the first time, retries noticeably eat into your budget.

This breakdown helps you understand where limits are "leaking." For a detailed view of current options, visit the videos page or images page.

Step 3: Pay Attention to Retries

One of the hidden cost drivers is failed first attempts. When a prompt is vague, the result must be regenerated. This is where most limits are lost:

Vague image prompt: "draw a nice office" instead of "draw a modern bright office with large windows and white furniture, corner view, no people."
Imprecise chat request: "explain this further" without context forces the AI to guess what you mean.
Video without motion description: "a cat video"—and it's unclear what should happen in the frame.

A few practical rules to reduce retries:

Be specific: object, context, format, constraints.
For images: describe style, angle, lighting, and what to exclude.
For videos: describe scene, action, and duration.
For text tasks: specify audience, tone, desired length, and what to avoid.

Prompt quality directly affects limit usage. One well-crafted prompt instead of five bad ones is real savings without any tricks.

Step 4: Save Effective Prompts

If a prompt yields a good result—save it. This not only saves time but also reduces limit consumption for recurring tasks. It's useful to keep a simple document or note with templates:

prompt for generating article illustrations
prompt for analyzing data tables
prompt for writing short posts in a neutral tone

When templates are available, you don't start from scratch each time. This saves both time and limits.

Step 5: Separate Work and Experimental Tasks

Not all usage is equally valuable. It's helpful to divide tasks into two categories:

Work tasks—those whose results are used: published, shared with colleagues, part of a project. Here, quality and accuracy matter.

Experiments—trying new things, getting to know a model, testing capabilities. Here it's normal to spend more limits, but it's good to be aware of this beforehand.

If experiments make up a significant portion of consumption, it's a signal to check if there's a cheaper way to test hypotheses. For example, text requests are cheaper than media generations, and some tasks can be "checked" in the chat first.

What Not to Do When Estimating Costs

A few common mistakes that complicate the picture:

Comparing yourself to others' case studies: every usage pattern is unique. Someone else's "promised savings" says nothing about your situation.
Switching to a cheaper plan without analysis: if limits are regularly exhausted before the end of the period, downgrading will only create constraints.
Ignoring unused limits: if some limits are not used—maybe the subscription is excessive for current task volume.
Counting only direct costs: also account for time spent reformulating prompts and verifying results.

How to Use the Pricing Page for Estimation

On the pricing page, you can see what each plan includes. For cost estimation, it's useful to compare:

the request volume in your chosen plan with actual consumption
the volume of image and video generations
the availability and cost of one-off bundles if your limits run out

If you have questions about specific terms or aren't sure what's included in your current plan, reach out to the support page. You can get details without speculation.

Mini Checklist for AI Cost Estimation

List the regular tasks you solve with AI.
Categorize them by type: text requests, image generations, video generations.
Identify where retries occur and why.
Save effective prompts as templates.
Compare actual consumption with your plan's limits.
If limits run out early, check what they're being spent on.
If limits are not fully used, consider if your current plan fits.

Legal terms for use and data processing are described in the offer and privacy policy—it's worth reading before including sensitive data in your requests.

Summary

Estimating AI tool costs is not magic or a one-time audit. It's a habit: understanding what and why you request, where limits are lost, and where you can be more precise with prompts. Without this, any "optimization" remains at the level of intuition rather than concrete observations. Start by writing down your tasks—it takes ten minutes, but gives clarity that's hard to achieve otherwise.

How to Estimate AI Tool Costs Without Fictional Case Studies