{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"FLOPs — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"

AI Glossary — gaks.ai

FLOPs (FLOPs)

Floating Point Operations: a measure of computational workload used to quantify the cost of training or running an AI model. A single FLOP is one arithmetic operation (addition, multiplication, etc.) on a floating-point number. Model size and training cost are often compared in terms of FLOPs, as in "this model required 10^23 FLOPs to train." See also: parameter, inference cost.

Source: gaks.ai/glossary/flops →
"}