Microsoft launches 3 new AI models in direct shot at OpenAI and Google

Microsoft on Wednesday launched three new foundational AI models it built entirely in-house — a state-of-the-art speech transcription system, a voice generation engine, and an upgraded image creator — marking the most concrete evidence yet that the $3 trillion software giant intends to compete directly with OpenAI, Google, and other frontier labs on model development, not just distribution.

The trio of models — MAI-Transcribe-1, MAI-Voice-1, and MAI-Image-2 — are available immediately through Microsoft Foundry and a new MAI Playground. They span three of the most commercially valuable modalities in enterprise AI: converting speech to text, generating realistic human voice, and creating images. Together, they represent the opening salvo from Microsoft's superintelligence team, which Suleyman formed just six months ago to pursue what he calls "AI self-sufficiency."

"I'm very excited that we've now got the first models out, which are the very best in the world for transcription," Suleyman told VentureBeat in an exclusive interview ahead of the launch. "Not only that, we're able to deliver the model with half the GPUs of the state-of-the-art competition."

The announcement lands at a precarious moment for Microsoft. The company's stock just closed its worst quarter since the 2008 financial crisis, as investors increasingly demand proof that hundreds of billions of dollars in AI infrastructure spending will translate into revenue. These models — priced aggressively and positioned to reduce Microsoft's own cost of goods sold — are Suleyman's first answer to that pressure.

Microsoft's new transcription model claims best-in-class accuracy across 25 languages

MAI-Transcribe-1 is the headline release. The speech-to-text model achieves the lowest average Word Error Rate on the FLEURS benchmark — the industry-standard multilingual test — across the top 25 languages by Microsoft product usage, averaging 3.8% WER. According to Microsoft's benchmarks, it beats OpenAI's Whisper-large-v3 on all 25 languages, Google's Gemini 3.1 Flash on 22 of 25, and ElevenLabs' Scribe v2 and OpenAI's GPT-Transcribe on 15 of 25 each.

The model uses a transformer-based text decoder with a bi-directional audio encoder. It accepts MP3, WAV, and FLAC files up to 200MB, and Microsoft says its batch transcription speed is 2.5 times faster than the existing Microsoft Azure Fast offering. Diarization, contextual biasing, and streaming are listed as "coming soon." Microsoft is already testing MAI-Transcribe-1 inside Copilot's Voice mode and Microsoft Teams for conversation transcription — a detail that underscores how quickly the company intends to replace third-party or older internal models with its own.

Alongside it, MAI-Voice-1 is Microsoft's text-to-speech model, capable of generating 60 seconds of natural-sounding audio in a single second. The model preserves speaker identity across long-form content and now supports custom voice creation from just a few seconds of audio through Microsoft Foundry. Microsoft is pricing it at $22 per 1 million characters. MAI-Image-2, meanwhile, debuted as a top-three model family on the Arena.ai leaderboard and now delivers at least 2x faster generation times on Foundry and Copilot compared to its predecessor. Microsoft is rolling it out across Bing and PowerPoint, pricing it at $5 per 1 million tokens for text input and $33 per 1 million tokens for image output. WPP, one of the world's largest advertising holding companies, is among the first enterprise partners building with MAI-Image-2 at scale.

The contract renegotiation with OpenAI that made Microsoft's model ambitions possible

To understand why these models matter, you have to understand the contractual tectonic shift that made them possible. Until October 2025, Microsoft was contractually prohibited from independently pursuing artificial general intelligence. The original deal with OpenAI, signed in 2019, gave Microsoft a license to OpenAI's models in exchange for building the cloud infrastructure OpenAI needed. But when OpenAI sought to expand its compute footprint beyond Microsoft — striking deals with SoftBank and others — Microsoft renegotiated. As Suleyman explained in a December 2025 interview with Bloomberg, the revised agreement meant that "up until a few weeks ago, Microsoft was not allowed — by contract — to pursue artificial general intelligence or superintelligence independently." The new terms freed Microsoft to build its own frontier models while retaining license rights to everything OpenAI builds through 2032.

Suleyman described the dynamic to VentureBeat in characteristically blunt terms. "Back in September of last year, we renegotiated the contract with OpenAI, and that enabled us to independently pursue our own superintelligence," he said. "Since then, we've been convening the compute and the team and buying up the data that we need."

He was quick to emphasize that the OpenAI partnership remains intact. "Nothing's changing with the OpenAI partnership. We will be in partnership with them at least until 2032 and hopefully a lot longer," Suleyman said. "They have been a phenomenal partner to us." He also highlighted that Microsoft provides access to Anthropic's Claude through its Foundry API, framing the company as "a platform of platforms." But the subtext is unmistakable: Microsoft is building the capability to stand on its own. In March, as Business Insider first reported, Suleyman wrote in an internal memo that his goal is to "focus all my energy on our Superintelligence efforts and be able to deliver world class models for Microsoft over the next 5 years." CNBC reported that the structural shift freed Suleyman from day-to-day Copilot product responsibilities, with former Snap executive Jacob Andreou taking over as EVP of the combined consumer and commercial Copilot experience.

How teams of fewer than 10 engineers built models that rival Big Tech's best

Perhaps the most striking detail Suleyman shared with VentureBeat is how small the teams behind these models actually are. "The audio model was built by 10 people, and the vast majority of the speed, efficiency and accuracy gains come from the model architecture and the data that we have used," Suleyman said. "My philosophy has always been that we need fewer people who are more empowered. So we operate an extremely flat structure." He added: "Our image team, equally, is less than 10 people. So this is all about model and data innovation, which has delivered state of the art performance."

This matters for two reasons. First, it challenges the prevailing industry narrative that frontier AI development requires thousands of researchers and billions in headcount costs. Meta, by contrast, has pursued what Suleyman described in his Bloomberg interview as a strategy of "hiring a lot of individuals, rather than maybe creating a team" — including reported compensation packages of $100 million to $200 million for top researchers. Second, small teams producing state-of-the-art results dramatically improve the economics. If Microsoft can build best-in-class transcription with 10 engineers and half the GPUs of competitors, the margin structure of its AI business looks fundamentally different from companies burning through cash to achieve similar benchmarks.

The lean-team philosophy also echoes Suleyman's broader views on how AI is already reshaping the work of building AI itself. When asked by VentureBeat how his own team works, Suleyman described an environment that resembles a startup trading floor more than a traditional Microsoft engineering org. "There are groups of people around round tables, circular tables, not traditional desks, on laptops instead of big screens," he said. "They're basically vibe coding, side by side all day, morning till night, in rooms of 50 or 60 people."

Why Suleyman's "humanist AI" pitch is aimed squarely at enterprise buyers

Suleyman has been steadily building a philosophical