Big-O Operation Count Calculator

Big-O describes how the amount of work an algorithm does grows as the input size increases. This tool shows the raw operation count for each complexity class so you can compare how they scale for a given input size.

Exponential and factorial growth explode so quickly that the counts exceed the range a standard double-precision number can hold. The tool labels these as overflow to show that the algorithm is intractable at that input size.

Constant and logarithmic algorithms barely grow at all, and linear and linearithmic growth stays manageable. Quadratic growth becomes painful in the thousands, while exponential and factorial growth explode so fast that even modest inputs are intractable. Favor logarithmic and linearithmic algorithms when inputs are large.