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gpt-realtime-whisper

gpt-realtime-whisper is a streaming transcription model that converts live audio into text as the audio arrives, rather than waiting for a complete utterance or file upload. It is exposed as a Realtime API model that maintains a persistent streaming session, which makes it suited to continuous, low-latency scenarios such as live captioning, quality monitoring, or feeding a speech-to-speech or translation pipeline in parallel. The model is distinct from the offline transcription path served by POST /v1/audio/transcriptions on gpt-transcribe, so it is the right choice when transcript updates are needed while audio is still in progress rather than as a batch job.

Released alongside two other OpenAI Realtime Voice API models in early May 2026, gpt-realtime-whisper slots into a family of audio-first endpoints designed for voice agents and live audio stacks. Its practical fit is narrow but well defined: pair it with companion realtime models when you need a continuous source-language transcript flowing alongside translation, and reach for the offline gpt-transcribe endpoint instead when you only have pre-recorded files. For builders working on real-time voice experiences, this gives a cleaner separation between always-on streaming recognition and one-shot file transcription, with temperature-style controls available to tune output behavior.

Vercel AI Gatewayopenai/gpt-realtime-whisperwhisper

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Vercel AI Gateway
Model key
openai/gpt-realtime-whisper
Release date
May 7, 2026
Last updated
May 7, 2026
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Latest news about gpt-realtime-whisper

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CoverageRelease Notes

Microsoft's Azure OpenAI in Foundry Models changelog, dated September 10, 2026, documents new concept articles for GPT Realtime Translate and GPT Realtime Whisper. The GPT Realtime Whisper article covers low-latency streaming transcription for live captions, monitoring, and archival workflows, confirming Azure-hosted a The changelog places GPT Realtime Whisper in the May 2026 release section alongside the GPT Realtime 2.0 overview, which describes reasoning support, response phases including preamble and final answer, and stricter instruction following. This Azure documentation corroborates the cross-cloud availability of the same un

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