Know your AI generation cost before you run the code

When you build with image or video generation APIs, the bill usually surprises you after the fact. Input tokens, output tokens, image resolution, seconds of video - you only see the total at the end of the month.

There is a simpler pattern: know the price before you send the request.

The problem with post-hoc pricing

Most visual AI providers calculate cost after generation:

• You pick a model and some settings
• The job runs
• You get charged by tokens, pixels, or seconds
• Your invoice arrives later

That works, but it makes budgeting awkward when you run a lot of jobs, or when you let users generate content in your own product.

What pre-flight pricing looks like

With Pixapi, you choose a supported model and settings, and the API returns the required credits before you commit. You know instantly whether a generation is inside your budget.

Some example prices (check current pricing for the live numbers):

• Nano Banana from 2 credits (roughly $0.02)
• Supported routes typically 20-49% below official list prices

One key, one balance

You do not need separate keys or balances per model family. A single Bearer key and credit balance covers:

• Image generation
• Image editing
• Async video generation (Veo, Kling, Wan, and more)

Practical tips

1. Always read the estimated credits from the pre-flight response and cache it for your UI
2. For async video routes, poll the job status endpoint instead of blocking
3. Set a hard credit budget client-side so a runaway job cannot drain the balance

Docs: https://pixapi.ai/docs

This article was originally published at pixapi.ai - canonical source.