LLMOPS & AI INFRASTRUCTURE • 281 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.
FP32
FP32 is 32-bit floating-point precision.
Think of it like
Think of FP32 like familiar infrastructure capacity and traffic engineering, except the scarce resources are often tokens, GPU memory and model latency.
Real life
High-scale AI services depend on FP32 to keep cost and latency under control.
SRE lens
High precision uses more memory than lower-precision inference formats.
Remember thisFP32 is 32-bit floating-point precision.