How to Evaluate LLM Provider Performance Across Latency, Throughput, and Uptime

Evaluating the performance of Language Model (LLM) providers involves assessing metrics such as latency, throughput, uptime, and quantization. These metrics are crucial as they influence how a model behaves when accessed through different provider endpoints, each bringing unique infrastructure, routing behaviors, and precision levels. Latency measures the time taken for the first token to be received, while throughput gauges the number of tokens generated per second after generation begins. Uptime assesses the provider's reliability and availability, and quantization impacts the precision level at which a model operates, affecting both cost and quality of outputs. Percentile metrics like p90 and p99 offer deeper insights into performance consistency, particularly for user-facing applications, where average metrics might obscure occasional delays. Effective provider evaluation should transition into a dynamic routing policy rather than hard-coding provider choices, allowing applications to maintain performance by adapting to changing conditions and provider behavior. This approach ensures that the routing decisions align with specific application needs, enabling better management of precision, cost, and reliability.

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