Estimate peak memory use for a space complexity class at a given input size.
Space complexity often decides feasibility before time complexity does, because exceeding memory fails outright rather than merely running slowly. Quadratic space becomes impractical at input sizes linear space handles easily. Streaming and in-place algorithms trade time for constant space, which is what makes very large inputs processable at all.
Big O Space Complexity
Memory = space growth function of n × bytes per unit
Memory = space growth function of n × bytes per unit Space complexity often decides feasibility before time complexity does, because exceeding memory fails outright rather than merely running slowly. Quadratic space becomes impractical at input sizes linear space handles easily.
Streaming and in-place algorithms trade time for constant space, which is what makes very large inputs processable at all.
This calculator takes 4 inputs: Input size n, Space complexity class, Bytes per unit of space, Available memory. The pre-filled defaults are a realistic starting point — replace them with figures from your own environment for a result you can act on.