Microsoft AI’s MAI-Transcribe-2 undercuts OpenAI, Google and ElevenLabs on worth and velocity
Microsoft AI on Thursday launched MAI-Transcribe-2, a speech-recognition mannequin the corporate says is quicker, extra correct, and cheaper than something OpenAI, Google, or ElevenLabs presently sells. Then it priced the factor at 10 cents per hour of audio.
That determine deserves a pause. When Microsoft AI shipped the primary mannequin on this line simply 5 months in the past, it charged $0.36 an hour. Thursday's early-bird worth cuts that by roughly 72%. For an enterprise processing 100,000 hours of call-center audio a yr — a modest quantity for a big financial institution or telecom — the invoice drops from $36,000 to $10,000. At that degree, transcription stops being a line merchandise anybody argues about.
The launch arrives as Microsoft executes a technique that may have appeared implausible two years in the past: constructing its personal frontier-class fashions one modality at a time, then steadily swapping them into merchandise that after ran on OpenAI's know-how. Transcription is the modality the place that plan has moved quickest, and MAI-Transcribe-2 is its clearest proof level but. It additionally presents a preview of how the planet's Most worthy software program firm intends to compete in AI with out relying on the accomplice it spent $13 billion to domesticate.
What MAI-Transcribe-2 does and why the characteristic checklist issues to enterprise consumers
The mannequin transcribes audio in 60 languages, up from 43 in June's MAI-Transcribe-1.5 and 25 in April's unique launch. It runs on Microsoft Foundry, the corporate's mannequin market for builders, and in MAI Playground, its testing atmosphere. Microsoft says it constructed the mannequin for the messy audio that actual companies generate — background noise, low-quality recordings, overlapping speech — slightly than clear studio situations.
More necessary than the language depend is what Microsoft has bundled into the bottom product. Speaker diarization kinds out who mentioned what in a multi-person recording, which is the distinction between a wall of textual content and a usable assembly transcript. Word-level timestamps connect a exact time marker to each phrase, enabling search, enhancing, and alignment with video. Keyword biasing lets builders feed the mannequin an inventory of drug names, product codes, or worker names so it stops mangling area jargon. Automatic language identification means customers now not must declare the language upfront.
Two options stand out for his or her specificity. A configurable output fashion presents a "verbatim" mode that preserves each "um," false begin, and stutter for compliance and authorized groups, alongside a "clear" mode that strips fillers for readable captions and notes. And code switching handles conversations that drift between languages mid-sentence; Microsoft explicitly names Hinglish and Spanglish, a nod to the Indian and U.S. Hispanic exchanges the place a single customer-service name would possibly toggle languages a dozen instances. Specialty distributors have traditionally charged premiums for every of those capabilities. Microsoft is together with all of them for a dime.
How to learn Microsoft's FLEURS and Artificial Analysis benchmark claims
Microsoft makes three efficiency claims, every resting on a unique measuring stick, and technical consumers ought to perceive what each captures and what it misses.
The first is that MAI-Transcribe-2 ranks primary on FLEURS throughout 60 languages with a mean phrase error charge of 5.2%. FLEURS is a benchmark Google researchers published in 2022, constructed from native audio system studying roughly 2,000 sentences in every of 102 languages — about 12 hours of speech per language. It is the usual yardstick for multilingual speech recognition as a result of it enables you to evaluate a mannequin's Swahili towards its Swedish on equivalent content material. Word error charge, its metric, merely counts substitutions, insertions, and deletions towards a human reference; 5.2% means roughly one phrase in 20 is improper. But FLEURS is learn speech, not dialog, and Microsoft's common has really risen from the three.7% it reported for MAI-Transcribe-1.5 in June. That virtually definitely displays broader protection slightly than regression — averaging throughout 60 languages as an alternative of 43 means folding in low-resource languages the place each mannequin struggles — however consumers ought to request the per-language breakdown.
The second declare is that the mannequin ranks second on the Artificial Analysis word-error-rate leaderboard and defines that agency's accuracy-latency Pareto frontier. Artificial Analysis is an impartial benchmarker that checks fashions by their public APIs, measuring what a buyer really will get. Its index blends simulated agent conversations, European Parliament speeches, and company earnings calls, weighting closely towards English trade speech. In June, the agency ranked MAI-Transcribe-1.5 third at 2.4% WER, behind Alibaba's Fun-Realtime-ASR-preview and ElevenLabs' Scribe v2, whereas calling it the quickest mannequin within the high 10. Climbing to second suggests Microsoft has cleared ElevenLabs. "Pareto frontier" is the phrase practitioners ought to observe: it means no rival beats the mannequin on accuracy with out being slower, and none beats it on velocity with out being much less correct.
The third declare is uncooked velocity — 10 instances sooner than OpenAI's GPT-Transcribe, seven instances sooner than ElevenLabs' Scribe v2, 5 instances sooner than Google's Gemini 3.5 Transcribe, per Artificial Analysis evaluations. In batch transcription, velocity issues much less as a result of anybody is ready and extra as a result of throughput is value. A mannequin operating at 300 instances real-time wants a fraction of the GPU-hours of 1 operating at 30 instances. That effectivity is what lets Microsoft cost a dime and, presumably, nonetheless make cash.
Three speech fashions in 5 months: inside Microsoft AI's speedy launch cadence
The tempo is the story inside the story. On April 2, MAI-Transcribe-1 launched with 25 languages at $0.36 per hour. On June 2, MAI-Transcribe-1.5 arrived with 43 languages, key phrase biasing, and a third-place rating on Artificial Analysis. Today, MAI-Transcribe-2 shipped with 60 languages, diarization, timestamps, code switching, a second-place rating, and a worth of $0.10.
Three releases in 5 months, every increasing language protection by roughly 40% whereas including options rivals gate behind premium tiers. That cadence is attribute of a workforce that has settled on a steady structure and is now turning the crank on knowledge and scale — the part the place speech fashions have a tendency to enhance shortly and predictably. It can be the cadence of an organization that intends to make transcription a commodity earlier than anybody else can.
The organizational wager behind that velocity is one Mustafa Suleyman, Microsoft AI's chief govt, described to The Verge in April. He credited the primary mannequin to "a small, centered 10-person workforce" that had been "liberated from any of the forms," with a bigger surrounding group dealing with vendor administration and knowledge acquisition.
He additionally advised The Verge the mannequin ran at "half the GPU value of the opposite state-of-the-art fashions," calling it "an enormous cost-saving" for Microsoft. Meta, Amazon, Google, and Anthropic have all experimented with related flattened constructions, The Verge famous. Microsoft's transcription line is essentially the most seen take a look at but of whether or not the strategy produces business outcomes slightly than analysis papers.
Why Microsoft is constructing its personal AI fashions regardless of its $13 billion OpenAI wager
Microsoft has invested greater than $13 billion in OpenAI, and hosts OpenAI's fashions throughout Azure, Office, and Copilot. For a lot of the previous 4 years, the plain query about any Microsoft-built mannequin has been: why hassle? The reply has sharpened over the previous yr, and it begins with independence.
When Microsoft hired Suleyman from Inflection AI in March 2024, together with most of Inflection's workers, Salesforce CEO Marc Benioff learn it as a declaration of intent. "Microsoft is constructing their very own AI and I don't assume Microsoft will use OpenAI sooner or later. They'll have their very own frontier fashions," Benioff told CNBC in January 2025. "That's why they employed Mustafa Suleyman." Benioff had his personal motives — Salesforce competes with Microsoft and invests in Anthropic — however occasions have largely borne him out.
In October 2025, Microsoft and OpenAI restructured their partnership in a deal that, per Microsoft's personal announcement, allowed Microsoft to "independently pursue AGI alone or in partnership with third events" for the primary time. Suleyman advised The Verge that renegotiation "unlocked [Microsoft's] ability to pursue superintelligence," and Microsoft introduced its MAI Superintelligence workforce weeks later. In April 2026, the businesses amended the deal once more, ending Microsoft's exclusive access to OpenAI's models and eliminating Microsoft's revenue-share payments, in response to studies on the time. Each modification loosened the tie. Each one was adopted by extra MAI fashions.
How Microsoft's in-house fashions are reducing prices throughout Teams, Word, and Excel
The second half of the reply is margin. Every immediate Microsoft routes to an OpenAI mannequin carries a value. Every immediate it routes to its personal mannequin by itself GPUs carries a smaller one. In July, Bloomberg reported that Microsoft had begun using MAI models to reply a portion of person prompts in Word and Excel — merchandise it had beforehand marketed as powered by OpenAI and Anthropic. TechCrunch framed the shift as a part of a broader industry pullback on AI spending, with Amazon, Uber, Meta, and Accenture all reportedly trimming.
Transcription is the pure first goal for this substitution as a result of the issue is bounded and the metric is goal. Microsoft owns Teams, which generates an infinite quantity of assembly audio. It owns Nuance, whose scientific documentation trade runs on speech recognition. It owns the Azure speech providers that 1000’s of enterprises already name. Every a kind of workloads is a candidate to maneuver onto MAI-Transcribe-2, and each hour that strikes is an hour Microsoft now not pays anybody else for.
Suleyman has been unusually candid that that is the purpose. Superintelligence, he told The Verge in April, "is admittedly about, 'Are these fashions able to delivering product worth for the hundreds of thousands of enterprises that rely on us to ship world-class language fashions?'" Whatever one thinks of making use of the phrase "superintelligence" to a transcription API, the business logic is obvious: construct the aptitude as soon as, deploy it throughout a dozen merchandise, and cease writing checks to a accomplice that’s more and more a competitor.
MAI-Transcribe-2 vs. OpenAI, Google, and ElevenLabs: the aggressive image
Microsoft's launch names 4 rivals: OpenAI's GPT-Transcribe, Google's Gemini 3.5 Transcribe, OpenAI's older Whisper V3-Large, and ElevenLabs' Scribe v2. It doesn’t point out Deepgram, AssemblyAI, Speechmatics, or Rev — the specialists which have offered transcription to enterprises for a decade. Microsoft is positioning towards the frontier labs, not the incumbents.
That framing is partly advertising and marketing and partly true. The frontier labs have handled speech as a checkbox characteristic of broader platforms, priced accordingly, and a devoted mannequin that beats them on velocity by 5 to 10 instances whereas matching their accuracy is a real differentiator. But the specialists will really feel the worth stress most acutely. At $0.10 an hour, Microsoft is pricing at or beneath the place a lot of them promote high-volume enterprise contracts, and it’s bundling diarization, timestamps, and 60 languages into the bottom charge. The specialists' remaining moat is area depth — medical vocabularies, authorized formatting, industry-specific integrations — and Microsoft's key phrase biasing characteristic is aimed squarely at it.
The one competitor Microsoft conspicuously doesn’t declare to beat on accuracy is Alibaba, whose fashions have posted main numbers on impartial leaderboards for a lot of 2026. TechCrunch reported in July that some U.S. companies had begun evaluating Chinese models as cheaper options regardless of safety issues. Microsoft's pitch to these consumers is implicit however unmistakable: comparable accuracy, sooner inference, lower cost, and a vendor your compliance workforce already trusts.
The questions technical determination makers ought to ask earlier than switching transcription distributors
For all its specificity on benchmarks, the discharge leaves a number of sensible questions open. The first is period: Microsoft calls $0.10 per hour a launch supply with out naming an finish date or an ordinary charge, and anybody constructing a value mannequin ought to get each in writing. The second is streaming. The launch emphasizes batch throughput and long-form audio however says nothing about real-time transcription, which voice brokers and stay captioning require. Artificial Analysis maintains a separate streaming leaderboard, and Microsoft's silence on it’s notable.
The third is per-language accuracy. A 5.2% common throughout 60 languages may imply 3% on main languages and 12% on low-resource ones, so consumers with particular wants ought to take a look at these languages straight. The fourth is diarization high quality. Word error charge doesn’t measure speaker attribution; a transcript can have near-perfect WER and nonetheless assign each different sentence to the improper individual. The launch presents no diarization error charge or comparable metric.
The fifth is knowledge dealing with. Enterprise transcription touches medical data, authorized privilege, and monetary disclosures, and the discharge says nothing about knowledge residency, retention, or whether or not audio submitted to Foundry feeds future coaching. Microsoft's April bulletins described coaching knowledge as a mixture of human-curated recordings, contractor-recorded noisy audio, and "huge quantities of information from the open internet," per The Verge — an outline that ought to immediate pointed questions from regulated industries. None of those gaps is uncommon for a launch announcement, however they’re precisely the questions that separate a leaderboard win from a manufacturing deployment.
What Microsoft's speech mannequin technique reveals about its broader AI ambitions
Step again from the speech-recognition particulars and a sample emerges that extends properly past transcription. Microsoft's AI unit now ships fashions for pictures, voice, transcription, code, reasoning, and cybersecurity. At Build in June, it introduced seven new MAI models in a singlekeynote. Each follows the identical playbook: goal a well-defined modality, optimize aggressively for inference value, worth beneath the frontier labs, distribute by Foundry, and quietly swap the mannequin into Microsoft's personal merchandise.
This just isn’t an try to construct one mannequin that beats GPT or Gemini at every part. It is an try to construct a portfolio of specialised fashions that, in mixture, let Microsoft serve most of its enterprise workloads with out paying anybody else — and to promote the excess capability to everybody else at costs the specialists can not match. Transcription occurred to be the primary modality the place the strategy totally matured, however the launch notes for MAI-Transcribe-2 learn much less like a product announcement than a template.
Suleyman has spent two years speaking about "humanist superintelligence" and AI assistants which might be "accountable to them, on their aspect." The vocabulary is lofty. The execution is a spreadsheet. Five months in the past, Microsoft charged 36 cents to show an hour of speech into textual content. On Thursday it charged a dime, threw in six options its rivals promote individually, and claimed the highest spot on the {industry}'s customary multilingual benchmark. The firm that spent $13 billion studying what frontier AI prices has determined it will slightly personal the manufacturing facility than lease the output — and now it’s promoting the output for lower than the lease.
MAI-Transcribe-2 is out there now by Microsoft Foundry and MAI Playground.
