OpenAI has set GPT-Live-1 pricing at 0.05 US dollars per minute of conversation, billed per second — with backend model and tool usage charged separately on top. That figure comes straight from OpenAI's launch announcement, "Introducing GPT-Live-1 in the API", posted 10 September 2026 on the company's official developer forum. Five cents a minute means an hour of continuous voice conversation costs 3 US dollars on the voice layer, and per-second billing means a 40-second call bills as 40 seconds, not a rounded-up minute. If you are costing out a voice agent business — phone reception, booking lines, support triage — this page breaks down what that rate actually turns into at real call volumes, and where the hidden costs sit.
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GPT-Live-1 Pricing Breakdown
The published rate is simple, which is itself unusual for voice AI. Per the 10 September 2026 launch post: 0.05 US dollars per minute, billed per second, for the conversation itself. What is not included matters just as much. The announcement is explicit that backend model and tool usage are charged separately — GPT-Live-1 does the listening and talking, but when your agent looks up an order, checks a calendar or writes to a CRM, the model doing that thinking bills on its own meter. So the honest cost equation for a working voice agent is voice minutes plus backend tokens, and the second half depends entirely on which brain you attach and how busy each call keeps it.
Straight arithmetic on the voice side, using OpenAI's published per-minute rate:
| Monthly conversation volume | Voice-layer cost |
|---|---|
| 100 minutes (light testing) | 5 US dollars |
| 1,000 minutes (a quiet phone line) | 50 US dollars |
| 5,000 minutes (a busy reception desk) | 250 US dollars |
| 20,000 minutes (small call-centre scale) | 1,000 US dollars |
Those are illustrative volumes multiplied by the published rate, before backend costs. For most small-business use cases the voice layer is comfortably the minority of the bill at low volumes — and per-second billing keeps short, bursty calls cheap, which is exactly the traffic shape of a reception line.
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What You Get for the Money
The rate buys a genuinely different class of voice model. GPT-Live-1 is full duplex — it listens while it speaks, handles interruptions and backchannels, and detects when a caller has actually finished talking. OpenAI's launch post reports 83.6 percent task completion on Tau3 tasks against 45.7 percent for its previous GPT-Realtime-2.1 model, turn-taking latency of 0.798 seconds versus 1.41, and 87 percent tool-calling success. For a buyer, those numbers translate to fewer abandoned calls and fewer jobs half-done — which is what you are actually paying for, since a cheaper voice layer that completes half as many tasks is not cheaper. The launch post also lists 12 included voices with tone, pace and style steerable through system prompts, so there is no extra production cost for giving each client's agent its own personality.
The Backend Bill: the Part Most Cost Estimates Miss
Because GPT-Live-1 charges the conversation and not the thinking, your backend choice is the real pricing lever. The launch post notes the model can keep a conversation going while a backend agent works, which means the architecture is deliberately two-part: voice in front, agent brain behind. That brain can be a premium model or a budget one, and the market has moved fast on the budget end — DeepSeek's current rates, covered in the DeepSeek V4.1 Flash API pricing breakdown, show how far backend token costs have fallen this year. Weighing which brain is actually good enough for the job is exactly what the Goldie Bench write-up covers, comparing the main agent models in hands-on tests; and if you are leaning premium, the GPT-6 Astra guide covers OpenAI's own flagship option. Pair a five-cents-a-minute voice layer with a low-cost backend and the all-in economics of a working phone agent land far below what a human answering service charges.
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GPT-Live-1 Pricing as a Business: the Margin Question
Here is the sum that matters if you sell voice agents rather than merely run one. A client's reception line doing 1,000 minutes a month costs about 50 US dollars in voice fees plus backend usage. Voice agent services routinely retail for several hundred dollars a month per line — the gap between those numbers is the business. That is the same agency arithmetic behind the making money building AI agents guide: you are not selling API minutes, you are selling answered phones, booked appointments and captured leads that the client currently loses to voicemail.
The delivery patterns are already established. A phone-facing build rides the Telephony and SIP access the launch post describes; a chat-adjacent build follows the Telegram AI agent pattern; and a spoken layer over an existing automation stack looks like the Hermes voice agent setup. Whichever shape you sell, the agent behind the voice needs durable goals, memory and skills — the job of an operating layer like the Agent OS — because clients renew for reliability, not novelty. Run several client agents and you are into fleet territory, where the first-agent-to-fleet workflow guide covers keeping ten lines running without ten times the work. Done properly, a handful of maintained voice agents behaves like the recurring-revenue models in the passive income with AI breakdown — monthly retainers against largely automated delivery.
How GPT-Live-1 Costs Compare in Context
Voice AI pricing has historically been messy: separate meters for speech-to-text, the language model and text-to-speech, which made per-call costs genuinely hard to predict. A single published per-minute rate for the conversation layer, billed per second, is a materially simpler model to quote a client against — you can estimate a bill from call volume alone, then add backend usage. The caveats to keep in view: the 0.05 dollars per minute figure and every benchmark above are OpenAI's own published numbers from the 10 September 2026 announcement, vendor pricing can change, and your backend spend is a second bill that scales with how much work each call triggers. Pilot with real call recordings and measure both meters before you quote fixed prices to anyone.
A Worked Example: Costing One Client's Phone Line
Put the pieces together for a single, concrete scenario — a local clinic that misses around 30 calls a week outside reception hours. Assume the agent takes those 30 calls at an average of 3 minutes each: that is roughly 390 minutes a month. On GPT-Live-1 pricing of 0.05 US dollars per minute, the voice layer bills about 19.50 US dollars a month. Add backend usage for the booking lookups and confirmations each call triggers — modest at this volume on any current model, and genuinely small if the brain behind it is a budget option of the kind the DeepSeek pricing breakdown linked above covers. The all-in delivery cost lands in the tens of dollars a month.
Now price the value side: each after-hours call is a patient who would otherwise hit voicemail, and a service that reliably converts even a fraction of those into booked appointments is easily worth a few hundred a month to the clinic. The numbers in this example are illustrative assumptions — your call volumes and call lengths will differ — but the shape of the sum is the point. The published per-minute rate makes the cost side of the quote predictable enough to put in a proposal, and the gap between delivery cost and client value is wide enough to survive your assumptions being off by double.
Is GPT-Live-1 free to try?
The launch post does not describe a free tier — GPT-Live-1 is a paid API model at 0.05 US dollars per minute, billed per second. The practical way to trial it cheaply is per-second billing itself: a hundred minutes of structured testing costs about 5 US dollars on the voice layer.
Does the price include the agent doing the actual work?
No. Per the announcement, backend model and tool usage are charged separately. Budget the voice layer and the backend brain as two line items; the backend is the one that varies most with how complex each call is.
What affects the total cost of a voice agent most?
Call volume sets the voice-layer bill almost linearly at 0.05 dollars per minute. Beyond that, the biggest levers are your backend model choice and how many tool calls each conversation triggers — which is why the same phone line can cost wildly different amounts depending on how the agent behind it is built.
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