GPT-Live

GPT-Live is a family of full-duplex voice models developed by OpenAI for continuous spoken interaction. OpenAI released GPT-Live-1 and GPT-Live-1 mini on July 8, 2026, as the models behind a new Live option in ChatGPT Voice. GPT-Live-1 is intended for paid users, while GPT-Live-1 mini is the lower-cost version used for Free accounts. Both can process incoming speech while producing speech, instead of waiting for a clearly bounded user turn to end.^[1][2]

GPT-Live is both a model family and part of an orchestrated product. The voice model manages listening, speaking, interruptions, pauses, and short conversational responses. For questions that require web search or more computation, it can delegate work to a separate frontier model and continue the conversation while that work runs. At launch, GPT-Live-1 in Instant mode and GPT-Live-1 mini delegated to GPT-5.5 Instant. The Medium and High settings used GPT-5.5 Thinking with medium or high reasoning effort.^[1]

Release and product role

OpenAI announced and began the global consumer rollout on July 8, 2026, across ChatGPT.com and the iOS and Android applications. The launch made GPT-Live-1 the default Live model for Go, Plus, and Pro users and GPT-Live-1 mini the default for Free users. The older Advanced Voice Mode and Standard Voice remained available as separate options. Live did not support Business, Enterprise, or Edu workspaces on launch day, but OpenAI's help documentation later added early access for eligible Business, Enterprise, Edu, and Healthcare workspaces, subject to administrator settings.^[3][4]

The three ChatGPT Voice options use different interaction designs:

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GPT-Live is not the same product as the developer-facing OpenAI Realtime API. OpenAI said at launch that it planned to add GPT-Live-1 to the API and opened a notification form, but had not released API access by July 24, 2026.^[1][5] The API model catalog continued to list the separate GPT-Realtime family for developers. Consequently, GPT-Live had no public API model identifier, token price, context-window specification, or rate-limit table at that date.

Continuous interaction and delegation

Earlier voice systems treated conversation as a sequence of requests. Standard Voice waited for speech to end, transcribed it, sent the transcript to a language model, and synthesized the written response. Advanced Voice removed the transcription and synthesis handoffs, but still depended on detecting when one turn had finished before beginning the next. A pause or background sound could therefore be mistaken for the end of a turn.^[1]

GPT-Live continuously processes incoming audio while it generates output. OpenAI says the model makes interaction decisions many times per second, including whether to speak, keep listening, pause, stop, or invoke a tool. This permits conversational backchannels such as short acknowledgments, interruption while the model is talking, waiting through a user's pause, and live translation. It also changes turn detection from a single silence threshold into an ongoing model decision.^[1]

Delegation separates conversational timing from deeper work. GPT-Live can acknowledge a request and keep interacting while a second model searches or reasons in the background, then introduce the result when it is ready. This arrangement can reduce dead air, but it also means that the perceived intelligence of the ChatGPT experience is not a measurement of GPT-Live alone. OpenAI's system card states that its evaluations include delegation because that matches the deployed product.^[1][2]

OpenAI did not publish a single end-to-end latency number at launch. An independent test by Agora Media Lab measured the consumer ChatGPT application rather than direct model inference. On one iPhone 13, in English, with 30 trials per condition, it found about 1.1 seconds from the end of user speech to the first audible response. GPT-Live took about 1.4 seconds to stop after a deliberate interruption, roughly 0.5 seconds longer than Advanced Voice, but it was much less likely to stop for background speech. Under simulated 10% uplink packet loss, GPT-Live's median response delay increased by 314 milliseconds, compared with 2,448 milliseconds for Advanced Voice. The test was a launch-week snapshot from a communications vendor, not a broad independent benchmark.^[7]

Modalities and ChatGPT features

The core GPT-Live interaction is audio input and audio output, with simultaneous listening and speaking. In ChatGPT, spoken responses also appear as streamed text. Users can type messages or attach images in the same chat, and Live can return supported visual cards for information such as weather, markets, sports, or maps. These are capabilities of the deployed ChatGPT experience, and OpenAI has not disclosed which parts run directly in GPT-Live rather than through product-level routing or delegation.^[1][3]

The launch version did not accept live video or screen sharing. Those inputs remained available in Advanced Voice for eligible mobile subscribers. Live also initially excluded connected applications and plugins, was unavailable inside custom GPTs, and could not independently perform image generation, data analysis, or custom actions in a custom-GPT voice conversation. OpenAI's help page later documented a separate Voice in Work and Codex experience on the ChatGPT desktop application, where the voice interface can coordinate agents using the tools and permissions supplied by those products.^[3]

OpenAI provides nine preset ChatGPT voices for Live. The system is designed for conversation rather than voice cloning, and its safeguards are intended to prevent imitation of a real person's voice. OpenAI has not released the model weights, parameter counts, context limits, knowledge cutoff, architectural details beyond the full-duplex and delegation design, or a list of native input and output formats outside the ChatGPT product.^[1][2]

Access and usage limits

GPT-Live did not have standalone API pricing at launch because it was not available through the API. Consumer access was bundled into ChatGPT subscriptions and governed by rolling usage limits rather than per-token billing. OpenAI's July 24 help documentation listed the following allowances, while warning that limits can change:^[3]

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A single Live conversation can last no more than two hours. OpenAI separately listed Voice in Work and Codex at approximately 6 credits per minute for Business and Enterprise workspaces on flexible pricing, with delegated tasks charged against the relevant product's normal usage pool.^[3] These plan entitlements are product pricing rather than a price for running GPT-Live as a standalone model.

Evaluation

OpenAI created head-to-head human evaluations using matched conversations lasting 5-10 minutes. It reported that both GPT-Live models were strongly preferred to their Advanced Voice predecessors for overall preference, turn-taking, interruptions, conversational flow, and perceived naturalness. The company did not publish the sample size, preference percentages, or full evaluation protocol on the launch page.^[1]

OpenAI also reported that GPT-Live-1 outperformed Advanced Voice on GPQA, BrowseComp, and an internal variant of the tau3-Voice Telecom task. These results included the deployed delegation system: Instant and mini used GPT-5.5 Instant, while Medium and High used GPT-5.5 Thinking. They therefore test the combined voice-and-reasoning product rather than isolating the voice model's own scientific knowledge or search ability.^[1][2]

The system card reports separate voice-native safety evaluations. On difficult production prompts selected from cases where Advanced Voice had not responded ideally, GPT-Live-1 was equal to or better than its predecessor in most measured categories. Its emotional-reliance score fell from 0.88 to 0.82, and the mini model's sexual-content score fell from 0.97 to 0.95; OpenAI said neither difference was statistically significant. On a synthetic adversarial set covering sexual content, illicit behavior, mental health, personal data, emotional reliance, self-harm, hate, and gore, both GPT-Live models matched or exceeded their predecessors in every reported category. OpenAI cautioned that neither set was prevalence-weighted and that the scores should not be treated as estimates of safety in ordinary use.^[2]

Safety work

OpenAI trained GPT-Live with data from publicly available internet sources, licensed or partnered sources, and material provided or generated by users, human trainers, and researchers. The system card describes filtering intended to reduce personal information and harmful or sensitive training material, but does not give dataset sizes or a detailed data inventory.^[2]

The safety evaluation program included audio prompts from users who had opted to share voice interactions, with permission and deletion checks, eligibility filtering, de-identification, and personal-information scrubbing. OpenAI also generated synthetic spoken prompts for rare or adversarial cases. Internal and external red teamers tested the models across languages for self-harm, emotional reliance, manipulation, child-coded voices, impersonation, speaker identification, and audio-specific perturbations.^[2]

Runtime safeguards examine inputs and outputs while a conversation unfolds. They can steer or interrupt a response, play a spoken safety message, display support resources, or end a higher-risk conversation. OpenAI also adapted its self-harm support flows for voice, added age-appropriate behavior for teen accounts, and began post-launch monitoring focused on emotional reliance.^[1][2]

Under OpenAI's Preparedness Framework, its Safety Advisory Group concluded that GPT-Live-1 and GPT-Live-1 mini, without delegation, could not plausibly reach the High threshold for biological and chemical risk, cybersecurity, or AI self-improvement. Delegated work inherits the safeguards of the model that performs it. The standalone voice models did not have code execution or broad independent tool access at launch, and OpenAI did not run AI self-improvement evaluations because the company found them less capable than GPT-5.5 Thinking on several intelligence tests.^[2]

Limitations

GPT-Live remains sensitive to conversational and acoustic conditions. OpenAI says it is designed mainly for one-on-one use and is not optimized for several people speaking together. Overlapping speech, background noise, network quality, microphone settings, and long pauses can still cause interruptions or missed speech. Transcripts may differ from what either party actually said. Agora's test also observed four unsolicited responses to background speakers in 30 noisy-room trials, a speaker-attribution failure not present in the two older modes in that test.^[3][7]

Language quality varies. OpenAI says it optimized the models for some of ChatGPT's most popular languages but did not publish the list. It warns that other languages may have non-native accents or gaps in fluency. At OpenAI's launch demonstration, TechCrunch described the Hindi translation as having a strong American accent and wording that sounded unnatural and overly formal.^[1][6]

The lack of API access limits independent reproduction. Researchers cannot directly control model settings, isolate GPT-Live from ChatGPT's delegation and interface, or compare usage cost under a fixed API workload. OpenAI's capability evaluations are developer-reported, and several measure the whole deployed system. Model size, context limits, training-compute details, and complete architectural specifications remain undisclosed.^[1][2][5]

References

1. OpenAI. "Introducing GPT-Live." July 8, 2026. https://openai.com/index/introducing-gpt-live/ ↩
2. OpenAI. "GPT-Live System Card." July 8, 2026. https://deploymentsafety.openai.com/gpt-live ↩
3. OpenAI Help Center. "ChatGPT Voice." Updated July 24, 2026. https://help.openai.com/en/articles/20001274-gpt-live-faq ↩
4. OpenAI Help Center. "ChatGPT Release Notes." July 8, 2026 entry. https://help.openai.com/en/articles/6825453-chatgpt-release-notes ↩
5. OpenAI. "GPT-Live-1 in the API." Accessed July 24, 2026. https://openai.com/form/gpt-live-1-in-the-api/ ↩
6. Ivan Mehta. "OpenAI releases new voice models for more natural live conversations." TechCrunch, July 8, 2026. https://techcrunch.com/2026/07/08/openai-releases-new-voice-models-for-more-natural-live-conversations/ ↩
7. Hermes Frangoudis. "OpenAI Didn't Publish GPT-Live's Latency. So We Measured It." Agora Media Lab, July 10, 2026. https://prod.agora.io/es/blog/openai-didnt-publish-gpt-lives-latency-so-we-measured-it ↩