AIQA Blog
Understanding Credits and Test Runs
How AIQA meters usage and how to estimate runs for your team size.
AIQA uses credits because autonomous tests vary in size. A short crawl with a few screens does not consume the same resources as a long, multi-mode review of a large application.
What a credit measures
Credits translate the AI and processing resources used by a run into one understandable unit. Usage is based primarily on token consumption and the work performed while exploring and reviewing the application.
A baseline run is approximately 25 credits at roughly 250,000 tokens. This is an estimate, not a fixed price for every run.
Why runs consume different amounts
The completed run displays the credits charged, so teams can compare real projects rather than relying only on estimates.
- More reachable screens create more screenshots and review work.
- Complex navigation can require additional exploration steps.
- Design, logic, marketing, and full modes perform different analyses.
- Large screen descriptions and findings increase model usage.
Estimate capacity for your team
Begin with several representative runs: a small smoke check, a normal release candidate, and the broadest full test you expect to use. Record their credit totals and use the average that matches your release process.
For example, a pool of 1,250 credits represents about 50 baseline runs at 25 credits each, but the actual count can be higher or lower depending on scope and app complexity.
Monthly and purchased credits
Subscription plans provide a recurring credit allocation. One-time top-ups are available when a team needs additional capacity, and purchased credits do not expire.
Choose the smallest plan that covers normal monthly usage, then use measured run history to adjust. This keeps cost tied to actual QA activity instead of an arbitrary test-case count.