FLOP
A single basic arithmetic step by a computer, used to count how much calculation a training run needs.
FLOP stands for floating-point operation, which is one basic step of arithmetic, such as adding or multiplying two numbers with decimals. Counting them gives a common way to measure how much calculation a piece of work involves. The plural, FLOPs, is used for the total count. Do not confuse it with FLOPS, with a capital S, which means operations per second and describes the speed of a chip.
In AI, the total number of FLOPs used to train a model is a standard measure of the size of a training run. The numbers are enormous, so they are written in powers of ten. Comparing FLOPs lets people say roughly how much more work one model took than another, regardless of the hardware used.
The measure also appears in policy. Some rules use a FLOP threshold to decide which models count as especially large. The European Union’s AI Act presumes that a general-purpose model carries systemic risk, which brings extra obligations, if its training used more than 10 to the power of 25 FLOPs. A 2023 United States executive order, since revoked, set a reporting threshold ten times higher. Critics note that a raw count is a blunt tool, since better methods can achieve more with the same number of operations.