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LLM Latency: TTFT vs. TPOT - Why Mean Latency Deceives Users

By PulseAugur Editorial · [1 sources] ·

A technical analysis highlights the discrepancy between Time To First Token (TTFT) and Time Per Output Token (TPOT) in LLM serving latency. While mean end-to-end latency can be misleadingly low, TTFT can increase dramatically under load, indicating user-perceived delays. The analysis uses a discrete-event simulation to demonstrate how factors like arrival rate, prompt length, and batch size disproportionately affect TTFT versus TPOT, suggesting that focusing solely on mean latency can obscure critical performance issues. AI

IMPACT Highlights how TTFT, not just mean latency, impacts user experience in LLM applications.

RANK_REASON Technical analysis of LLM serving latency metrics.

Read on dev.to — LLM tag →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

LLM Latency: TTFT vs. TPOT - Why Mean Latency Deceives Users

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Technical analysis of LLM serving latency metrics.
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COVERAGE [1]

  1. dev.to — LLM tag TIER_1 English(EN) · Devanshu Biswas ·

    TTFT and TPOT: The Latency Number You Report Hides the One Users Feel

    <p>Push a simulated serving queue from 0.2 to 3.0 requests a second and mean end-to-end latency gets <strong>17x</strong> worse.</p> <p>Over the same range, the 99th percentile time to first token gets <strong>762x</strong> worse — <strong>206 ms</strong> to <strong>157 s</strong…

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