LLMOPS & AI INFRASTRUCTURE • 279 / 397
Operate AI like production: serving, GPUs, latency, capacity, routing and reliability.

Prefix Cache

Prefix caching reuses computation for repeated prompt prefixes shared across requests.

Think of it like

Think of Prefix Cache 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 Prefix Cache to keep cost and latency under control.

SRE lens

A large common system prompt can be cheaper and faster when cacheable.

Remember thisPrefix caching reuses computation for repeated prompt prefixes shared across requests.
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