Last updated: 2026-06-22

LLM monthly cost explained

The monthly cost of a large language model workload is the recurring spend produced by issuing API calls at a steady volume over a billing month. It scales a single call's price — itself a function of input and output token counts and the model's per-million-token rates — by the number of requests per day and the number of days in the month. The same daily figure projects forward to an annual total.

How a per-call price scales

Recurring cost is built in three multiplications. The cost of one request is the per-call token cost; multiplying by the daily request count gives the daily spend; multiplying that by the billing days gives the monthly figure. Because every factor is linear, doubling any one of them — token usage, request volume, or the rate — doubles the projected spend.

The formula

With average $n_{in}$ input and $n_{out}$ output tokens per call at per-million prices $p_{in}$ and $p_{out}$, the cost of one request is

For $N_d$ requests per day across $D$ billing days, the daily, monthly, and annual costs are

The annual figure multiplies the daily cost by 365 directly rather than by twelve months, so it does not inherit the approximation in the monthly day count.

Worked example

Take a workload of $N_d = 1000$ requests per day, each averaging 1500 input and 500 output tokens at $3 and $15 per million. The per-request cost is C_r = \0.012$. The daily spend is

Over a 30-day month that is C_m = 12 \times 30 = \360$, and over a full year$C_y = 12 \times 365 = $4{,}380$. Note that twelve 30-day months total 360 days, five short of a year, which is why the annual figure exceeds twelve times the monthly one.

Notes and variations

A projection assumes average usage and volume hold steady; real traffic varies by day and by season. The effective rate can also drop below the headline figure — prompt caching discounts repeated context, batch processing lowers the rate in exchange for latency, and committed-use agreements reduce the unit price. The day count is a modelling choice: 30 is a round approximation, while $365/12 \approx 30.44$ is the exact mean month length.

Application

Monthly cost turns a single-call estimate into a budget line. The per-call figure it scales from is the subject of the Token Cost Calculator, and workloads where each task issues many sequential calls are estimated with the Agent Cost Calculator. When projected volume approaches a provider's throughput ceiling, LLM Rate-Limit Planning Calculator checks whether the rate limits can sustain it.