Help CenterVoice AI AgentsUnderstanding Latency in Voice AI Agents

Understanding Latency in Voice AI Agents

What latency means on a live call, why Eleven v3 is slower than Flash, and how tools like book_appointment add delay — so you can set the right expectations.

5 min readUpdated 2026-02-26

Latency is the gap between the moment a caller stops speaking and the moment your agent starts replying. On a phone call, even small delays are noticeable — so it helps to understand what drives latency and which of your own settings push it up or down.

The short version
Flash v2.5 is the fastest engine (~75ms model inference). Eleven v3 sounds richer and more expressive but responds a bit slower. Enabling tools (like book_appointment) also adds delay, because the agent has to wait for an external system before it can answer.

Two different latency numbers

When people say 'latency' they usually mean one of two things, and the difference matters:

What they mean
Model inference
The time the voice model spends generating audio. ElevenLabs Flash models hit ~75ms for short replies. This is an internal number — it excludes the network and everything else in the pipeline.
Time-to-first-audio (TTFA)
The real-world delay your caller actually experiences — from the request leaving Voxinity to the first sound playing. It's always larger than model inference, and it's the number that defines how 'snappy' a call feels.

What happens between the caller speaking and the agent replying

Every spoken reply travels through a pipeline, and each stage adds a little time:

  1. Speech recognition (ASR) — the caller's words are transcribed to text.
  2. LLM — the AI reads the transcript (plus your prompt, knowledge base, and memory) and decides what to say.
  3. Text-to-speech (TTS) — the chosen voice model turns that text into audio.
  4. Network + playback — the audio streams back over the phone line and plays. Most players buffer a little to avoid stutter.

Voxinity streams audio as soon as the first chunk is ready, so callers hear the agent begin speaking instead of waiting for the whole sentence to finish. That keeps perceived latency low even when the full reply is long.

Model choice: Flash v2.5 vs Eleven v3

This is the single biggest lever you control. The difference between Flash and v3 is architectural, not a setting that can be tuned away — richer audio simply takes more computation.

Voice models
Flash v2.5
Fastest (~75ms model inference), 32 languages. The right default for live phone calls and real-time sales/support — use it 90% of the time.
Eleven v3
Most expressive and emotionally rich, 74 languages, supports emotion tags like [cheerful] and [laughs]. Responds noticeably slower than Flash. Best when natural, dramatic delivery matters more than raw speed.
v3 is a quality/speed trade-off
There's no way to get v3 quality at Flash speed — the richness comes from a larger model. If a call needs to feel instant, choose Flash. If a warm, expressive voice matters more, accept slightly higher latency with v3.

How Voxinity warms up your agent before every call

A voice model is fastest once it's already 'warm' — connected, loaded, and ready. The slowest response is almost always the very first one, while the model is still cold. Voxinity hides this cold-start so your caller never feels it — but it does it differently for outbound vs inbound, because what sounds natural is different in each case.

Outbound calls — a short delay warms the agent before the phone rings

On an outbound call, Voxinity boots the agent FIRST and holds a short warm-up window — it delays the call by a few seconds — BEFORE it actually dials the contact. During that brief delay the agent's brain (LLM) and voice (TTS) load in the background, while the contact's phone hasn't even started ringing. By the time it rings and they answer, the agent is already hot and replies almost instantly on their first words — instead of 8-12 seconds of dead air during the conversation, which makes leads say 'hello?' over and over or even hang up. The contact never hears anything during the delay, because they aren't on the line yet.

Outbound warm-up (auto, per voice model)
Flash v2.5
Uses the standard short delay — Flash loads fast, so the proven default is plenty. (Unchanged.)
Eleven v3
Gets a slightly longer delay — v3 is a larger model and cold-starts much slower, so it needs a bit more time to be ready before pickup.
Why v3 needs a longer delay
v3's richer voice comes from a bigger model that takes longer to spin up. Giving v3 the same short delay as Flash leaves it cold when the lead answers (the 8-12s lag). Delaying the call a little longer before it dials closes that gap — the same simple mechanism Flash uses, just scaled up a couple seconds for v3.

Inbound calls — a ring or two before the AI answers

On an inbound call the caller DIALED you, so hearing the phone ring is exactly what they expect. Voxinity uses those rings as free warm-up time: it lets the line ring (one or two times) while the agent loads in the background, then the AI picks up already warm. Because ringing is natural when you're calling someone, the warm-up is completely invisible — this is why inbound calls feel so instant.

The number of rings before the AI answers is configurable per agent (default 1). More rings give a heavier agent — for example one with a large knowledge base or several tools — extra time to be fully ready before it speaks.

Same idea, both directions
Inbound warms during the natural ringing the caller already expects. Outbound warms during a short delay before the dial is even placed. Either way, the agent is warm before its first word — and v3, being slower to wake up, simply gets a couple more seconds of delay than Flash.

Tools & function calling add latency

When your agent calls a tool — book_appointment, check_availability, reschedule_appointment, add_tag, transfer_call, and so on — it has to pause, send a request to an external system (your calendar or CRM), wait for the response, and only then continue talking. That round-trip is outside the voice model and adds real delay, especially for calendar and CRM lookups.

Functions tab showing enabled tools like book_appointment and check_availability
Each tool you enable in the Functions tab can add latency when the agent invokes it mid-call.
  • The more tools an agent calls during a turn, the longer the caller waits for that reply.
  • Calendar and CRM tools (check_availability, book_appointment) are usually the slowest because they depend on a third-party API.
  • Only enable the tools an agent actually needs — extra tools widen the LLM's decision space and can slow responses.
Hide the wait with Pre-Tool Speech
The most effective way to deal with tool latency isn't making tools faster — it's making the pause feel natural. That's what Pre-Tool Speech does, and it's worth setting up on every agent that books appointments or checks a calendar.

Pre-Tool Speech — make tool pauses feel like normal conversation

Pre-Tool Speech lets the agent say a short, natural line BEFORE it runs a tool — so instead of dead silence while your calendar or CRM responds, the caller hears something like 'Let me check what we have available…' and the wait feels like a normal part of the conversation. You'll find it under Agent → Call Settings → Tool Execution Behavior.

Call Settings → Tool Execution Behavior with Pre-Tool Speech enabled and per-function phrases
Agent → Call Settings → Tool Execution Behavior: toggle Pre-Tool Speech on, then set a phrase per function (or leave it on AUTO).

With it switched on you get a per-function phrase list. Each function can work one of two ways:

Per-function phrases
AUTO
Leave the field blank and the AI writes a fitting line itself based on what it's about to do. Fine for most functions.
CUSTOM
Type your own line (e.g. 'Alright, sounds good — let me get that locked in for you…') to control tone and wording on the actions that matter most, like booking or transfers.
  • Put CUSTOM phrases on the slowest, highest-stakes tools — check_availability and book_appointment — where the wait is longest and the caller is most anxious.
  • Keep phrases short and conversational, and end with an ellipsis so the line flows naturally into the result.
  • Leave the faster tools (add_note, update_contact) on AUTO — they rarely pause long enough to need a scripted line.
Why this beats chasing raw speed
Perceived latency is what callers actually feel. A 3-second calendar lookup with a 'Let me check that for you…' lead-in feels responsive; the exact same 3 seconds of silence feels broken or like the call dropped. Pre-Tool Speech doesn't make tools faster — it makes the wait invisible.

Other things that affect latency

Factors
Geography
Calls routed far from the nearest ElevenLabs cluster carry more network delay. A test from one region may feel different elsewhere.
Voice type
Default and Instant Voice Clones synthesize faster than Professional Voice Clones (PVC), which add per-generation overhead.
Prompt length
Very long system prompts give the LLM more to read each turn. Keep prompts tight and push facts into the Knowledge Base instead.
Reply length
Long, rambling answers take longer to generate and speak. Instruct the agent to be concise.

How to keep calls feeling fast

  • Use Flash v2.5 for live calls unless you specifically need v3's expressiveness.
  • Enable only the tools the agent needs, and keep Pre-Tool Speech on.
  • Keep system prompts under ~700 words; move detailed facts into the Knowledge Base.
  • Tell the agent to answer concisely and avoid long monologues.
Set expectations
A small, natural pause — especially right after the agent looks something up — is normal and expected on AI calls. The goal isn't zero latency; it's a conversation that feels human and unhurried.
Still have questions?
Reach our team — replies within 1 business day.
Contact Support