Latency, Throughput and Cost

Key Metrics for Optimizing AI Product Performance

What it is

Latency is the time taken for a system to respond to an input. Throughput measures how many tasks the system can handle in a given time. Cost refers to the resources spent, including compute power and infrastructure, to run AI models efficiently.

How it works

Latency depends on model complexity and system speed; lower latency means faster responses. Throughput scales with available hardware and software efficiency, determining how many requests can be processed simultaneously. Cost is influenced by processing power, model size, and usage frequency, balancing speed and capacity against budget constraints.

Why it matters

Product managers must balance latency, throughput, and cost to ensure responsive, scalable AI services. High latency frustrates users, low throughput limits capacity, and high costs reduce profitability. Optimizing these metrics improves user experience, controls expenses, and supports scalable, sustainable AI deployment.