Inference & Serving

Explainers, primers, and context for complex AI topics.

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Inference & Serving

ComparisonsLatency vs. TTFT vs. Tokens per Second vs. ThroughputLatency is how long one inference request takes, TTFT is how long a streamed request takes to begin answering, tokens per second is a rate that may describe one stream or a whole system, and throughput is how much total work a system completes over time. The sharpest distinction is scope: latency and TTFT time a request, while throughput counts work across a measurement window.
ConceptsWhat Are Tokens per Second?Tokens per second (TPS or tok/s) measures how many tokens an AI system produces in one second. The number may describe the output speed of one response or the combined throughput of an entire serving system, so the label alone is incomplete.
ConceptsWhat Is Inference Latency?Inference latency is the elapsed time between an AI system receiving an input and producing a specified output. A latency number is meaningful only when you know where the timer starts, where it stops, and what kind of output counts as complete.
ConceptsWhat Is Inference Throughput?Inference throughput is the amount of model work an inference system completes per unit of time across all the requests it is serving. It may be measured in completed requests, inferences, samples, or tokens per second.
ConceptsWhat Is Inference in AI?Inference in AI is the process of running a trained model on an input to produce an output, without updating what the model learned. It is the use phase of a model: a photo goes in and a label comes out, or a prompt goes in and generated text comes out.
ConceptsWhat Is Time to First Token?Time to first token, or TTFT, is the elapsed time between starting a language-model request and getting the first token of its response. It measures the initial wait, not how fast the rest of the response arrives.