Serverless Request Cost Calculator
Estimate the monthly cost of a serverless function from its request count, execution time, memory size and the per-request and GB-second rates.
How it works
GB-seconds = requests × (duration ÷ 1000) × (memory ÷ 1024) · Compute = GB-seconds × $/GB-s · Requests = (requests ÷ 1M) × price · Total = compute + requests
Serverless platforms charge on two axes: a flat fee per request and a compute fee measured in gigabyte-seconds — memory in GB multiplied by run time in seconds. Doubling either the memory you allocate or the duration of the function doubles the compute portion, so a slow function on a large memory tier can cost far more than its request count suggests. For short, high-volume functions the per-request fee dominates; for long-running or memory-heavy ones the GB-second compute charge takes over.
Worked example
Ten million requests at 200 ms and 512 MB use 10,000,000 × 0.2 × (512 ÷ 1024) = 1,000,000 GB-seconds. At $0.0000166667/GB-s that is about $16.67 of compute, plus (10 ÷ 1) × $0.20 = $2.00 of request charges, for roughly $18.67 a month.
Frequently asked questions
What is a GB-second?
A GB-second is one gigabyte of allocated memory held for one second of execution. If a function uses 512 MB (0.5 GB) and runs for 2 seconds, that is 0.5 × 2 = 1 GB-second. Providers bill compute in these units, so both memory size and run time drive the cost.
Should I lower the memory to save money?
Not always — higher memory tiers also get more CPU, so a function may run fast enough on more memory that the shorter duration offsets the higher per-second rate. Test a couple of memory settings and compare total GB-seconds, since the fastest tier is sometimes the cheapest overall.
Are free tiers included?
No — this calculator prices every request and GB-second. Most providers include a monthly free allotment (often 1M requests and 400,000 GB-seconds), so subtract that allowance from your totals if your usage is small enough to benefit.
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This calculator is for educational purposes. Double-check important results before acting on them.