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

Developers often start LLM selection by choosing a model such as Claude, Llama, Gemini, or DeepSeek, then treat the provider as a secondary decision. That’s understandable. But the model choice alone doesn’t tell you how the model performs through a specific provider endpoint. The same model can run through multiple provider endpoints, and each endpoint can bring different infrastructure, routing behavior, quantization choices, and failure patterns. Your users and systems see those differences in practical ways. One provider may return the first token quickly, but slow down during the rest of the response. Another may serve a lower-precision variant that drifts on harder prompts. Another may perform well under normal traffic but fail under load. Provider evaluation compares serving environments rather than treating the model as a standalone product. It asks how long users wait for the first token, how quickly the rest of the response arrives, how the provider behaves under load, and what precision level the model runs at. This guide works through those questions in the order in which you can act on them: latency, throughput, uptime, and quantization. Once you can measure those trade-offs, the next step is to turn the results into routing logic so…