Your voice agent's biggest latency isn't always the model

Reddit r/ArtificialInteligence News

Summary

Voice agents often face latency issues not mainly from the model but from components like endpointing; optimizing VAD and using proper benchmarking can reduce turn latency effectively.

Something worth paying attention to when building voice agents: benchmarking every component individually can still leave a voice turn at ~1.5s. A typical turn has seven hops, and endpointing alone can account for ~700ms — roughly 53% of the budget. Teams often spend weeks optimizing LLM latency while overlooking VAD configuration. Another common mistake: adding per-hop p95s. Percentiles aren't additive, so that number can be misleading. A calculator on this site models the full voice-turn latency budget using published vendor numbers. If your real numbers differ, that gap may reveal where the actual bottleneck is
Original Article

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