Averages hide the users that hurt
In most products a small minority generates a large share of requests. Pricing against the mean works until those users arrive, and then the margin collapses on exactly the cohort that is hardest to remove.
The heavy-user share is modelled separately here rather than folded into an average, because that is where subscription AI products actually bleed.
Reading the margin
Inference is not your only cost. Support, hosting, payment processing and salaries come out of the same price, so an inference margin below about seventy percent is usually thin once everything else is counted.
If the margin is negative, the fix is structural: fewer tokens per request, cheaper models for simple work, or usage limits. Raising the price rarely survives contact with the market.