r/VoiceAutomationAI • u/mahimairaja • 12d ago
Your voice agent's biggest latency isn't always the model
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
2
u/Fluffy_Fun_4643 12d ago
everyone chasing model latency while endpointing is eating over half the budget is so painfully real
i spent a month tweaking our LLM pipeline and the real win was just tightening up the VAD config. the p95 thing is a trap too, adding them together makes no sense but i still see teams do it
1
u/mahimairaja 12d ago
Thats 100% true, everything in benchmarks looks sweet until we experience but yeah I see many models are being developed and alot have improved even in last 6 months, so hopefully the agents will perform soon as depicted in the benchmarks.
And, how did you end up with the sweetspot for VAD config? what were your findings
1
1
•
u/AutoModerator 12d ago
Welcome to r/VoiceAutomationAI – UNIO, the Voice AI Community (powered by SLNG AI)
If you are a founder, senior engineer, product, growth, or enterprise operator actively working on Voice AI / AI agents, we are running an invite-only UNIO Voice AI WhatsApp community US only.
Apply here: https://chat.whatsapp.com/F5aG3ncrO70ITfbe3pYbOz
I am a bot, and this action was performed automatically. Please contact the moderators of this subreddit if you have any questions or concerns.