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Announcements

Building a hill-climbing machine: Launching seven new MAI models

Mustafa Suleyman

June 2, 2026

Announcements

Mustafa Suleyman

LI

FB

Today we are announcing a family of seven new models developed in-house at Microsoft AI. Beyond these models, we’re building a superintelligence lab – a system and an approach we believe will define the next phase of AI.

This is an extraordinary time in technology. The compute used to train frontier models has increased by a factor of one trillion. Now we expect another thousand-fold increase over the next three years, which in turn means more advanced capabilities, and the continued rollout of ever more effective AI.

This epic compute ramp will change the nature of work, business and daily life. We all have to prepare for this reality. Our job at MAI is to help you do this – to push the frontier, and to build a hill-climbing machine to keep you at the frontier.

Here’s our first steps along the way.

Our Models

Our new models across image, voice, transcription, coding, and reasoning, together form the MAI model family: a multimodal ecosystem designed to work across the kinds of tasks that matter in the real world.

MAI-Thinking-1, Microsoft AI’s flagship reasoning model. It is a medium-sized model that stands among the strongest models in its weight class: it matches leading models on key software engineering benchmarks, and reaches human preference parity with Sonnet 4.6 in blind side-by-side evaluations. We trained it from the ground up on clean data, without distillation from third-party models.

MAI-Code-1-Flash is an inference-efficient agentic coding model. This model is tailor-made for and deeply integrated into GitHub Copilot, VS Code and the Microsoft stack, and, with 5 billion parameters, is comparable to Haiku but cheaper.

MAI-Image-2.5 including its ultra-efficient Flash variant, supports both world-class text-to-image and image editing, surpassing the Arena score of Nano Banana Pro.

MAI Transcribe-1.5 is the best transcription model in the world, with SOTA accuracy. It’s five times faster than competing models, with built-in support for domain-specific terminology across 43 languages.

MAI-Voice-2 brings high-quality, natural-sounding speech generation across 15 languages, with the ability to adapt to a voice from a short sample, alongside strong safeguards against misuse. MAI-Voice-2-Flash, coming soon, does it in a lower cost, ultra-efficient package.

Alongside distribution on Foundry and optimization for our 1P products, our models are also going to be widely available for developers on Open Router, as well as Fireworks and Baseten. For the first time developers will be able to tune the weights of the model themselves.

All these models are built on a shared foundation, hill-climbing from the bottom with zero distillation. They share the same data discipline, the same infrastructure and the same evaluation framework. They are designed to work together, and to integrate directly into the products people use every day. But the models themselves are only part of the story.

The most important shift lies in what you can do with them.

Adapted for you

AI is moving into a new phase. With reinforcement learning in real-world environments, AI can fully adapt to the specifics of a given workflow for the first time. We call this Microsoft Frontier Tuning. We think it’s the future for how AI shows up.

In this set-up the most valuable data is yours: the trace of real work an agent completes, the sequence of steps, the decisions, the actions taken that define how tasks actually get done inside an organization.

Our reinforcement learning environments (RLEs) allow your MAI models to learn directly from your workflows. Think of them as training gyms for AI, accessible only to you.

With Frontier...