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Monthly AI Bill Forecaster

Users, requests per user and tokens per request turned into next month's bill, a quiet-month floor, a busy-month ceiling and a twelve-month projection.

Who is using it

What one request costs

Your own uncertainty

Next month, central case
$5,400 / month

Budget the range: $3,240 in a quiet month, $9,720 in a busy one. The width of that band is the two percentages you set, not a measurement.

Requests per month
360,000
Cost per request
$0.02
Input tokens per month
1,080,000,000
Output tokens per month
144,000,000
Input cost per month
$3,240
Output cost per month
$2,160
Cost per active user per month
$2.70
Month 3, central
$6,299
Month 6, central
$7,934
Month 12, central
$12,591
Twelve months, cumulative
$102,476
What this assumes: a month is the number of days you typed, and every active user behaves like the average in the central case. Growth compounds monthly and applies to users only — per-user intensity is held flat, which is the assumption most likely to be wrong, because engaged cohorts usually get heavier over time rather than lighter. The quiet and busy figures are your multipliers on the central case; they are not a confidence interval and nothing here has measured how your traffic is distributed. Retries, failed requests you are billed for, and any committed-spend discount are all excluded.

A forecast expressed as one number is a forecast that will be wrong, and being wrong by ten per cent in either direction is the normal outcome even when the model is sound. The reason to carry a band instead is that the two ends drive different decisions. The quiet figure is what you can commit to contractually. The busy figure is what your spend cap has to survive without taking the product down. A single central number answers neither question.

The band here is deliberately your own input rather than something computed for you. Request volumes across a user base are strongly skewed — a small fraction of users generate a large fraction of calls — and the shape of that skew is specific to your product. Nobody can hand you a distribution for it. What you can do is put a floor and a ceiling on it from what you have seen, and then check the ceiling against your rate limits rather than only against your budget, because the busy month is the one that discovers your tokens-per-minute cap.

The growth projection compounds users, not intensity. That is the conservative half of a forecast and the optimistic half of a budget: in practice per-user token consumption tends to climb as people learn what the feature can do and start pasting larger documents into it. If you want the pessimistic version, raise the input tokens per request along with the user count and watch how much faster month twelve moves. Cost per active user is the number worth tracking month to month — it is the one that tells you whether the product is getting more efficient or just larger.

Monthly AI Bill Forecaster · Multigrid