Advancing voice intelligence with new models in the API

We’re introducing three audio models in the API that unlock a new class of voice apps for developers. With these models, developers can build voice experiences that feel more natural, respond more intelligently, and take action in real time:

GPT‑Realtime‑2 , our first voice model with GPT‑5‑class reasoning that can handle harder requests and carry the conversation forward naturally.

GPT‑Realtime‑Translate , a new live translation model that translates speech from 70+ input languages into 13 output languages while keeping pace with the speaker.

Preambles: Developers can enable short phrases before a main response, like “let me check that” or “one moment while I look into it,” so users know the agent is working on the request.

Adjustable reasoning effort: Developers can now select from minimal, low, medium, high, and xhigh reasoning levels, with low as the default , balancing lower latency for straightforward interactions with more deliberate reasoning for complex requests.

The magic of GPT‑Realtime‑2 shows up across a variety of different use cases:

Voice is becoming one of the most natural ways for people to use software. It lets someone ask for help while driving, change a travel plan while walking through an airport, get support in their preferred language, or move through a task without stopping to type.

Voice-to-voice, where AI can help live conversations continue across languages, tasks, or changing context. For example, Deutsche Telekom is building voice support experiences where customers can speak in the language they’re most comfortable using, while the model translates the conversation in real time.

Longer context for agentic workflows: We’re increasing the context window from 32K to 128K to support longer, more coherent sessions and more complex task flows.

GPT‑Realtime‑Whisper , a new streaming speech-to-text that transcribes speech live as the speaker talks.

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But building useful voice products takes more than fast turn-taking or a natural-sounding voice. A voice agent needs to understand what someone means, keep track of context, recover when a request changes, use tools while the conversation continues, and respond in a way that feels appropriate to the moment.