The Hidden Tax of Per-Token Pricing
Public APIs charge you more precisely as AI becomes more useful. Here's why that's backwards, and what fixed-cost private AI changes.
There's a strange incentive baked into metered AI pricing: the more value your team gets from a tool, the more it costs you. Adoption, the thing you actually want, becomes the thing that inflates the bill.
The scaling penalty
Public AI APIs bill per token. Early on, that feels cheap. But the trajectory of a successful internal tool is more usage, not less:
- More people discover it works.
- They feed it longer documents.
- They build it into workflows that run all day.
Every one of those wins shows up as a bigger invoice. You end up rationing a tool you wanted everyone to use.
What fixed cost changes
Private AI running on dedicated infrastructure has a predictable, fixed cost. Heavy usage doesn't mean a heavier bill, which means you can do something you can't do under metered pricing: encourage adoption without watching a meter.
When usage is free at the margin, you stop optimizing for fewer queries and start optimizing for better outcomes.
It also decouples you from the vendor's schedule. Models can be deprecated or repriced on someone else's timeline, but when you own the deployment, you adopt new open models on your terms.
Fixed cost isn't just cheaper at scale. It changes what you're willing to let your team do.