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Headroom: What moving the face off the data centre adds up to

A live avatar's GPU time doesn't stay in the data centre. It turns up on the invoice, by the minute. We followed one support desk and one software product through a month of conversations.

At the end of the month, a support team's AI avatar has talked to customers for 500 hours. Most of those hours were ordinary: a delivery date, a password reset, a refund that hasn't arrived.

The invoice from its AI avatar provider has one line that matters, and it is counted in minutes. That line is not an accident of pricing. In the first piece in this series we showed that a cloud-rendered avatar holds part of a data-centre GPU for every second of the conversation. The minute on the invoice is that GPU, passed on.

This piece follows the same 500 hours through both ledgers: the data centre's and the customer's. What the face stops taking from both, once it moves to the device, is what we call headroom.

Where the face is drawn

A cloud-rendered avatar is a video stream. A GPU in the provider's data centre draws each frame and sends it to the customer's screen, for as long as the session is open. MeshLite draws the face on the customer's own device instead. A small audio model in the browser listens to the voice and picks the mouth shape for each moment, and the browser places the matching pre-made image on the face. MeshLite's servers run no inference for the avatar during the conversation, and no live video stream is sent. We explained why we built it this way in an earlier engineering note.

The look of the face is settled once, when the avatar is created in a one-time GPU job. During the conversation the browser doesn't generate the face; it places images that were already made. So this piece compares where the face is drawn and what that costs, not how it looks. For that, put the avatar on meshlite.io next to any cloud-rendered one you have seen.

Two things still use the cloud in both setups: that one-time creation job, and the speech recognition, language model and voice, which run on servers from providers the customer chooses. They have their own costs. The comparisons below cover ongoing avatar rendering only.

One support desk, one month

We measured one live session of a cloud-rendered avatar at about a fifth of an entry-level data-centre GPU. At that rate, 500 conversation-hours hold 100 GPU-hours for the faces alone.

Avatar-rendering load for 500 conversation-hours a month
500 conversation-hours a month Cloud-rendered avatar MeshLite, during the conversation
Data-centre GPU-hours held ~100 0
Electricity, including cooling ~11–23 kWh 0
The same, in phone charges ~510–1,060 0
Water, including power generation ~53–111 L 0

How we got these numbers: 500 hours × 20% of a GPU = 100 GPU-hours. We assume an entry-level GPU drawing 72–150 W (NVIDIA L4 to A10), the industry-average data-centre efficiency (PUE 1.56, Uptime Institute 2024), LBNL's water factors (0.36 L per kWh on site, 4.52 L per kWh through electricity) and 0.022 kWh per phone charge (Luccioni and colleagues). We count GPU power only; servers, memory and networking add more. Larger photoreal models on bigger GPUs hold several times as much.

On its own, that is small: a few hundred phone charges a month. Over a year it is 1,200 GPU-hours, roughly 130–280 kWh and up to 1,300 litres of water. What matters is how it grows. It grows with every minute of conversation and with nothing else. A contact centre running 10,000 conversation-hours a month holds about 2,000 GPU-hours, close to three entry-level GPUs running day and night to draw lips and blinks.

The device that draws the face instead is already switched on, and with a cloud avatar it would be decoding a live video stream anyway. We have not yet measured the device's share, so we present the net saving as analysis, not as a measured figure.

The same month in dollars

The fairest comparison is HeyGen's LiveAvatar in LITE mode, because it covers the same ground as MeshLite: the avatar only, with the customer bringing speech recognition, the language model and the voice. LiveAvatar Business costs $475 a month for 6,000 credits. LITE uses one credit per minute of session time, so the plan covers 100 hours, and each further credit costs $0.09: $5.40 for every extra hour.

MeshLite Business is a flat $499 a month, billed annually ($5,988 a year; $599 billed monthly), for one company's internal use with up to 200 simultaneous sessions. There is no per-minute rendering fee.

Monthly avatar-only plan costs (USD)
Avatar hours a month LiveAvatar Business (LITE) MeshLite Business (billed annually)
100 $475 $499
200 $1,015 $499
500 $2,635 $499
2,000 $10,735 $499

List prices, avatar only. LiveAvatar: $475 + (hours − 100) × $5.40. LiveAvatar's FULL mode uses two credits a minute but includes its own voice and language model, so it is not the same scope.

For our support desk, 500 hours a month comes to $31,620 a year on the per-minute plan and $5,988 on the flat one.

The comparison runs the other way at low volume, and buyers should know where the line is. The two plans cost the same at about 105 hours a month, roughly three and a half hours of conversation a day. Below that, LiveAvatar's included minutes are cheaper, and a team that uses its avatar for an hour a day should take them. Against a flat $0.09 a minute with no included hours, the crossover comes earlier, at about 92 hours. Paying MeshLite monthly moves it later, to about 123.

One product, a year of users

The arithmetic changes shape when the avatar sits inside a product a company sells. Usage is no longer one team's working day. It is every user's practice session, onboarding call and follow-up question.

Take a training app with 600 monthly users who each talk to its avatar for about 22 minutes a week, 96 minutes a month. That is 960 conversation-hours a month. Rendered in the cloud, the faces hold about 190 GPU-hours a month, around 2,300 a year, and use roughly 22–45 kWh of electricity a month.

Built on LiveAvatar Business in LITE mode, those 960 hours cost $5,119 a month, or $61,428 a year. MeshLite Embedded Starter covers up to 1,000 monthly users in a single product for $11,988 a year ($999 a month, billed annually). The crossover is about 197 hours a month, roughly 125 users at the same 96 minutes. If the app grows from 600 users to 1,000, the per-minute bill grows by two-thirds. The flat fee doesn't move until the product outgrows its tier, and then it steps to the next one.

What a discount can and can't change

These are list prices. Large buyers negotiate, and HeyGen advertises enterprise rates as low as $0.01 a minute at volume. A discount moves the dollar line. It does not move the GPU line: the provider still holds a share of a GPU for every minute of every session, and its price has to cover that, at whatever rate.

That is what we mean by headroom. Every conversation drawn on the device leaves GPU time, power, cooling and grid capacity in the data centre for work that only a data centre can do. The customer sees the same headroom as an invoice that doesn't follow the minutes.

The cheapest GPU-hour is the one a conversation never asks for.

Next

Every figure in this piece rests on one number we had to measure ourselves: how much of a GPU a single conversation holds. It decides both the energy and the invoice, and none of the large AI avatar providers we looked at publishes it. Next, we turn that gap into questions a buyer can put to any provider before signing: which GPU draws the face, how many conversations share it, and what happens to the bill on the busiest day of the year. After that, we look at why a talking face weighs so much more than the chat reply behind it.

Sources: LiveAvatar, credits and billing documentation (read 2026-10-19) and pricing · MeshLite pricing · Uptime Institute, Global Data Center Survey 2024 · LBNL, 2024 United States Data Center Energy Usage Report · Luccioni, Jernite and Strubell, Power Hungry Processing, ACM FAccT 2024 · NVIDIA L4 and A10 specifications.