
What happened
Microsoft launched MAI-Transcribe-2-Streaming, its first streaming transcription model, priced at 54 cents per audio hour. It supports over 60 languages and returns first transcript hypotheses in 320 milliseconds on average.
Why it matters
The model lets developers build voice agents that display live captions or begin processing a request before the speaker finishes, which Microsoft says is needed for natural, humanlike conversation.
What to watch
Microsoft's push to cut costs hinges on whether it can replace providers like OpenAI and Anthropic whose models it still pays for. Suleyman told Bloomberg the goal is to "reduce and ultimately eliminate that cost."
WHO IT HITSDevelopers building voice agents and conversational AI applications will get a cheaper, faster option for real-time transcription. Microsoft's Copilot teams working on agents for platforms like Excel and Outlook may also benefit as the company aims to use its own models internally.
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Microsoft's new models mark a step in its effort to build voice agents that can converse naturally with people. The company already released MAI-Transcribe-2 last month, and the streaming variant adds continuous, real-time output rather than waiting for a speaker to finish. Alongside the transcription model, Microsoft introduced MAI-Voice-2.1 and MAI-Voice-2.1-Flash for generating speech, priced at $22 and $15 per million characters respectively.
The company says a complete voice agent needs three capabilities: understanding speech, deciding what to do, and generating an audible reply. MAI-Transcribe-2-Streaming handles the first, the MAI-Voice models handle the third, and Microsoft's Mai-Thinking-1 reasoning model sits in the middle. Using separate models, according to Microsoft, gives developers more control over quality, latency and cost.
The releases also signal Microsoft's move away from model providers it invests in. Suleyman's comments to Bloomberg about reducing costs to Anthropic suggest the MAI family is intended to eventually power Copilot agents in platforms like Excel and Outlook, though how quickly that transition proceeds may depend on whether the in-house models can match the performance of the outside providers.
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