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Microsoft Launches MAI-Transcribe-2-Streaming and Two Voice Models

Microsoft’s streaming transcription model returns live partial hypotheses and final segments, supports 60 languages, and is available in public preview alongside two new voice models.
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Microsoft announced MAI-Transcribe-2-Streaming on October 1, 2026, alongside two text-to-speech models, MAI-Voice-2.1 and MAI-Voice-2.1-Flash. The new transcription model is designed to turn continuously arriving speech into live partial results and finalized transcript segments. It is in public preview, so Microsoft does not provide a service-level agreement for it and does not recommend it for production workloads.

What Microsoft announced

The launch comprises one streaming speech-to-text model and two speech-generation models. Microsoft presents them as components for conversational voice applications; the transcription model handles incoming audio, while the voice models turn text into speech.

Model Purpose Documented coverage or positioning
MAI-Transcribe-2-Streaming Streaming speech-to-text Supports 60 languages with automatic, continuous language detection.
MAI-Voice-2.1 Multilingual text-to-speech Supports 23 languages and 26 locales; designed to preserve one voice identity across supported languages.
MAI-Voice-2.1-Flash Faster text-to-speech variant Positioned for responsive, high-volume voice applications; a language count is not stated in the launch information.

How MAI-Transcribe-2-Streaming works

The model receives audio as a continuous stream rather than waiting for a complete recording. While a person is speaking, it can return intermediate hypotheses; after an utterance ends, it returns a final transcript segment. That distinction matters in an application: a partial result can help drive a live interaction, but it is provisional until the final segment arrives.

Microsoft says the model supports 60 languages and detects language automatically and continuously. This is intended to accommodate speech without requiring an application to select a language in advance. The launch information does not specify language-by-language accuracy or the conditions under which language switching is detected.

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How fast is the streaming transcription?

Microsoft reports that the first partial hypotheses arrive just over 100 milliseconds after the service receives audio. That measures from audio receipt, not from the instant a word is spoken. In a separate comparison, Microsoft says that words appear as early as 320 milliseconds after they are spoken in most cases, versus more than 500 milliseconds for the closest competition, according to its Community Hub article.

These figures describe different points in the audio-to-text path, so they should not be treated as interchangeable latency measurements. Both are Microsoft-reported figures, not independently reproduced test results. Actual end-to-end response time in an application can also depend on its audio capture, network, and processing path; the launch figures alone do not establish the latency a particular deployment will achieve.

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What Microsoft says about transcription accuracy

Microsoft says MAI-Transcribe-2-Streaming ranked number one for accuracy on both partial and final transcripts on the Artificial Analysis leaderboard. This is a vendor-reported evaluation claim. The launch information does not provide enough detail here to independently compare test conditions, language-by-language results, or performance on a specific customer workload.

How to access the model

Microsoft documents two integration routes for the streaming transcription model: an OpenAI Realtime-compatible WebSocket integration and the Azure Speech SDK. The SDK route is available to developers building around Azure Speech; the WebSocket route is an alternative integration path. Check Microsoft’s current Azure documentation for the precise setup steps and supported configuration, because region availability, API versions, and quotas can change.

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Is MAI-Transcribe-2-Streaming ready for production?

No. Microsoft lists the model as a public preview. Its documentation says preview features are provided without a service-level agreement and are not recommended for production workloads. A team evaluating it should treat preview availability as a constraint on reliability commitments, rather than assume that an SLA or production support is included.

How much does streaming transcription cost?

Microsoft announced an introductory price of $0.54 per hour of audio through December 31, 2026. It is a time-limited introductory price, not a confirmed ongoing rate. Check the live Azure pricing and product documentation before budgeting or deployment; the launch information does not establish the final price after the introductory period.

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Where the models fit

Live conversations and voice interfaces

Streaming partial results are suited to workloads where an application needs to respond while someone is still speaking. Microsoft names call centers, voice assistants, and voice-driven interfaces among the intended use cases. For these experiences, an application can use intermediate hypotheses for responsiveness and the finalized segment once the utterance is complete.

Captions and note taking

Meeting and lecture captioning and real-time note taking are also listed use cases. In these workflows, the distinction between a provisional partial transcript and a final segment can help set expectations for what appears live versus what is settled after each utterance.

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When batch transcription may fit better

Microsoft’s separate MAI-Transcribe-2 is the batch-oriented comparison named for this launch. Choose the streaming model when live action is the requirement; consider batch MAI-Transcribe-2 when diarization or word-level timestamps are the priority. The launch information does not establish a direct price or accuracy comparison between the two transcription models.

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.

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