Billing and Credits

How BBoxML billing, storage, and credits work.

This page explains how subscription credits, purchased credit packs, storage allowances, and AI labelling charges work together so your usage is predictable before you run a large dataset through the app.

Usage & BillingGetting Started

Subscriptions and renewals

Monthly subscriptions renew every month. Annual subscriptions renew once per year at the published annual catalog price. Monthly plans include a monthly credit allowance, while annual plans deliver the full year of included credits upfront for the current annual term.

  • Monthly plans refresh included credits each month.
  • Annual plans receive 12 months of included credits upfront for the year.
  • Unused included subscription credits do not roll over.
  • Purchased pack credits sit on top of subscription credits.
  • Free accounts include 50 one-time starter credits and 1 GB of storage.

Storage allowances

Every plan includes a storage allowance for the original images and project data stored in BBoxML. Free accounts include 1 GB, while paid subscriptions include 5 GB, 25 GB, or 100 GB depending on plan.

  • Storage is measured against the cloud files saved in your account.
  • Project usage and storage usage are visible in the Usage & Billing screen.
  • Storage allowance is separate from credits.

How AI labelling charges credits

Credits are charged per class requested on each image. If you ask the AI to look for three classes on one image, that run costs 3 credits.

  • 1 image with 1 selected class: 1 credit.
  • 1 image with 3 selected classes: 3 credits.
  • Manual labelling does not consume credits.

Batch AI charging

Batch AI uses the same model. Multiply the number of images by the number of classes you asked the AI to label, and that gives the total credit cost for the batch.

  • 5 images with 2 selected classes: 10 credits.
  • 10 images with 3 selected classes: 30 credits.
  • 100 images with 2 selected classes: 200 credits.

Worked examples

These examples match the charging logic used by the backend. Credit usage scales with the number of classes requested on each image.

1 image with 3 classes = 3 creditsRunning AI on one image while requesting 3 classes consumes 3 credits.
10 images with 2 classes = 20 creditsA 10-image batch with 2 selected classes costs 20 credits.
25 images with 1 class = 25 creditsIf you ask the AI to find one class across 25 images, the batch costs 25 credits.
100 images with 2 classes = 200 creditsTwo requested classes across 100 images costs 200 credits in total.