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Design real-time voice inference with 300 ms from the end of the user's turn to the first audio. Where does every millisecond go?

Voice moves the latency target from the first token to the first audible clause, and the largest item in the budget is not a model at all. The answer allocates 300 ms line by line, then sizes the LLM tier from it.

Updated Oct 2026 · Worked answers on inference mechanisms, with calculations, implementation details, and follow-up questions.

Voice moves the latency target from the first token to the first audible clause, and the largest item in the budget is not a model at all. The answer allocates 300 ms line by line, then sizes the LLM tier from it.

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Next in this trackPlan capacity for a 70B fleet that mixes H100 and B200 nodes under one latency SLO. How do you count capacity and route across them?Next in this trackDesign batch inference over 1 billion documents: embed each one and run a 70B model over each. How many GPUs, how long, what cost?Next in this trackCut inference cost per million output tokens by 70% while preserving quality and latency. Can you defend the target?
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