FP32

An INT8 quantization experiment on a TinyML ECG arrhythmia detection model cut its size from 87.5 KB in FP32 to 34.6 KB, a roughly 60% reduction, while reported accuracy held at 93.8%, according to th…

Integer quantization reduces neural network memory and energy costs by converting high-precision values to lower-bit integers, with INT8 additions consuming 30 times less energy than FP32. The techniq…