01
Overview
OpenAI's GPT-Live-1 API launch makes telephony one of the clearest business uses for its full-duplex voice model. OpenAI explicitly cites phone workflows such as restaurant reservations and customer support and exposes telephony/SIP as part of its Live developer surface.
That does not mean GPT-Live-1 is a complete call-center product by itself. It is best understood as the live conversational layer inside a larger phone-agent system.
02
Reference architecture
A practical architecture is:
Caller <-> phone/SIP connection <-> GPT-Live-1 <-> backend reasoning + tools <-> business systems.
The phone layer gets audio into and out of the application. GPT-Live-1 manages the continuous conversation. A backend model and tools handle jobs such as checking availability, retrieving customer information, creating a booking, updating an order, or deciding that a human should take over.
This separation is useful because the model that produces a natural spoken interaction does not have to be the same component performing every high-stakes action.
03
Why full duplex matters on a phone call
Phone conversations are full of interruptions, pauses and acknowledgements. A caller may say 'actually, make that Friday' while an agent is speaking, pause to check information, or respond with a short 'yeah' without intending to take over the entire turn.
OpenAI says GPT-Live-1 continuously reasons over incoming and outgoing audio, improving interruption handling compared with chained speech-to-text, language-model and text-to-speech systems. That is a vendor claim, but it identifies the key behavior teams should test in a phone deployment.
04
Delegate business actions instead of stuffing them into the prompt
A phone agent usually needs more than conversation. It may need to query inventory, search a knowledge base, book an appointment, update a CRM, create a ticket or issue a handoff.
GPT-Live-1 can delegate reasoning and tool calls to a backend model or agent harness. Keep permissions explicit. The voice layer can gather intent and maintain the conversation while the backend checks the real system of record and returns the result.
For irreversible or sensitive actions, add confirmation and authorization rules rather than assuming conversational fluency equals operational correctness.
05
Prompt for spoken behavior
Define the agent's role and boundaries in the system prompt. Include the desired pace and tone, how to react to silence, what information must be confirmed, when not to interrupt, what actions require confirmation, and when to escalate.
Keep spoken answers concise. A phone agent that reads long blocks of policy text can technically be correct while delivering a poor user experience.
06
Use transcripts carefully
GPT-Live-1 provides native ASR transcripts and response text and supports keyword biasing. This can help with names, codes and business vocabulary, but critical information should still be confirmed when an error would matter.
Phone workflows should explicitly test addresses, account identifiers, dates, times, prices and unusual proper nouns rather than relying on average transcription quality.
07
Pricing a GPT-Live-1 phone agent
OpenAI lists the GPT-Live-1 front-end voice layer at $0.05 per minute. That is only one line in the cost model.
A deployed phone agent may also incur backend model charges, tool/API charges, telephony/SIP charges, phone-number costs, infrastructure and observability expenses. OpenAI's launch page does not provide one universal all-in price for a phone agent.
This is why comparisons should use end-to-end cost per successful call or task rather than the voice-layer rate alone.
08
Good initial use cases
Lower-risk, repetitive workflows are sensible places to evaluate the system: reservation intake, appointment scheduling, order-status questions, FAQ/support triage and lead qualification. More sensitive workflows should add stronger identity, approval and human-escalation controls.
09
Production testing checklist
Test callers interrupting the agent; long pauses; noisy streets and speakerphone audio; simultaneous background speech; corrections to dates/numbers; backend timeouts; unavailable tools; transfers/escalations; long calls; and hang-up/reconnection behavior.
Measure task completion, incorrect actions, escalation rate, latency, caller abandonment and total cost—not merely how human the voice sounds.
10
What is confirmed vs still variable
Confirmed by OpenAI: GPT-Live-1 is available in the API; it supports full-duplex interaction and telephony; it can delegate reasoning/tool calls; and the front-end voice layer is listed at $0.05/minute.
Implementation-dependent: the telephony provider, phone-number pricing, backend model, tool stack, exact workflow permissions, total cost and production reliability in a specific business environment.
That distinction matters. GPT-Live-1 supplies a new voice primitive; the quality and safety of the complete phone agent still depend on the surrounding system.
Sources
Primary and supporting sources
Facts were rechecked against the linked sources immediately before publication. Pricing, product availability and rollout status can change.