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The developer release targets the pauses and interruptions that make automated calls feel rigid, while allowing builders to select backend models for different speed, cost and reasoning needs.
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OpenAI’s GPT-Live-1 gives developers a $0.05-per-minute API for full-duplex voice applications, with 12 voices, transcripts, and configurable backend models. OpenAI reports higher scores, better tool calling, and lower turn-taking latency than GPT-Realtime-2.1, but those are company-run comparisons. Its banking-support result was only a 32% pass rate, making deployment evidence important.
GPT-Live-1 supports simultaneous listening and speaking, reducing rigid wait-for-the-user turn-taking in automated calls.
OpenAI reports 0.8-second turn-taking latency versus 1.4 seconds for GPT-Realtime-2.1.
The API includes 12 voices plus automatic speech-recognition transcripts and response text.
Automated voice apps can now respond without treating every spoken exchange as a rigid handoff. OpenAI has released GPT-Live-1 as a developer API, offering a model that can listen and speak at the same time for live voice interactions.
The release is aimed at the pauses common in automated calls, where a system waits for a person to finish before responding. GPT-Live-1 supports full-duplex interaction, and OpenAI lists the API price at $0.05 per minute.
Developers can pair GPT-Live-1 with different backend models based on the reasoning depth, speed and cost their application needs. That gives builders a way to make different model choices for different voice tasks rather than treating every conversation alike.
OpenAI says its testing shows the model is more responsive and capable in voice workflows than GPT-Realtime-2.1. Those comparisons are company benchmark results, not independent evaluations of deployed voice agents.
The company also reports a 32% pass rate for GPT-Live-1 in a banking voice-support benchmark, up from 12.4% for the previous model. The result suggests progress, but it also shows a system that did not pass most tasks in that reported test.
Yelp is using GPT-Live-1 for phone-based reservations and has reported improved call handling, according to CTO Alex Levy. Reservations may be a useful early test for the model because callers can change or clarify a request while speaking.
For developers, the immediate proposition is a more fluid voice interface and a choice of backend models. Whether that produces better customer-service outcomes will depend on how those systems perform in real deployments, beyond OpenAI’s benchmarks and Yelp’s early report.
Editorial analysis
GPT-Live-1’s practical test is whether a more natural-sounding conversation improves the tasks behind it. OpenAI’s benchmarks show large gains in interactivity, latency and tool-calling accuracy, while Yelp says it has improved phone-based reservation handling. But the API also lets developers pair the voice model with backends chosen for different reasoning depth, speed and cost. That flexibility makes the voice experience only one part of the eventual service. The next evidence to watch is whether customer deployments publish outcome measures beyond early call-handling reports and company benchmarks.
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