Token billing was slowing down the whole team
A dev team with big ambitions and a billing model that said no for them. They never settled, and found a way to ship faster.
The Challenge
The team had momentum. Engineers wanted to iterate fast. Product wanted more experiments. The roadmap was full of AI features that could set them apart.
But every prototype, every experiment, every test run came with a price tag. Token billing made exploration expensive. Teams started rationing AI usage. Features got cut not because they weren't valuable, but because testing them cost too much.
The engineering culture shifted: AI became something to use sparingly, not something to build around. Ambition met a paywall. They could either accept the ceiling or find another way.
The Solution
QDivZero's capacity pricing changed the math entirely. Instead of meters running with every API call, they paid by the hour—a flat, predictable rate that removed the per-token tax on experimentation.
The team stopped counting tokens and started counting features. Prototypes that used to be "too expensive to test" became trivial to run. Experimentation velocity increased. AI features that stayed on the roadmap for months got shipped in weeks.
How QDivZero fits in
Flat hourly rate
Predictable cost per GPU hour, no per-token markup.
Unlimited inference
Run as many tests as needed without watching the meter.
Production-ready models
Deploy directly from catalog with one API call.
What the client did
Replaced per-token billing with QDivZero Compute capacity pricing
Shipped three AI features in the first three weeks instead of three months
Ran unlimited experiments at the same budget that previously covered one prototype
Scaled GPU capacity up and down based on development cycles, not token consumption