Copilot Cowork is now generally available!
Over the last few months of preview in Frontier, we’ve seen you use Cowork to help with so many different tasks. We’ve also been listening closely to your feedback and with GA, we’re bringing you more improvements + new features across model choice, extensibility through plugins, browser automation, and cost management controls.
Here’s a quick demo showing the latest updates in action - inspired by some of my own day-to-day tasks. You can also read more in the blog linked below...
We just shared with our team the realities we need to navigate as we work to reset the XBOX business. We won't succeed by hiding hard truths, nor will we succeed by doing the same thing and expecting different results. See the note here: https://t.co/IahtBNzwnR
AI is great, but choice is greater. Adding “-ai” to your query on Bing will now suppress AI summaries, and we’ve launched a browser extension to allow you to toggle it on/off for all your queries. I’d love to hear your feedback about how this impacts your overall experience.
Chopped it up with @swyx on @latentspacepod and we ran the gamut on this one. We talked platform, how roles are evolving, the agentic era, the future of open source, and what we’re building next. Spoiler: check out the @github Copilot app. 😉
Super excited to announce seven new world-class MAI models today. They represent what we consider a new era in AI designed to keep you in control and on the frontier.
First is our text foundation model, MAI-Thinking-1, exceptionally strong on reasoning and SWE tasks.
- It’s a 35B active parameter MoE with a 256K context window. Independent human raters on Surge prefer it for overall quality in blind side-by-sides versus Sonnet 4.6, and it’s achieved 97% on AIME 2025, the key measure of its general-purpose reasoning abilities.
- It's at 53% on SWE Bench Pro, placing it right alongside Opus 4.6 on one of the toughest coding benchmarks.
- And since we co-designed our models with our own silicon, MAI-Thinking-1 is optimized on our MAIA 200 chip. Benchmarking head-to-head against the GB200, we see 30% better performance per dollar as well as a 1.4x performance-per-watt gain when running our MAI models on the MAIA 200 end-to-end.
Next is MAI-Image-2.5 and its Flash variant. Two super strong models now at #2 on the leaderboards, surpassing the score of Nano Banana 2 on image editing.
Last for now is MAI-Code-1-Flash, our new inference efficient coding model, especially tuned for VS Code and GitHub Copilot CLI.
- Code-1-Flash achieves 51% on SWE Bench Pro, despite having just 5B parameters, putting it closer to Haiku in size but cheaper in cost.
All of this is the foundation for Microsoft Frontier Tuning. It lets you customize our models to create custom, company-specific agents that only you control. You can make our model, your model. Your data. Your agents. Your moat.
Early adopters are already seeing a difference. When we tuned our models for McKinsey’s tasks, MAI delivered the highest win rate, outperforming GPT-5.5 on quality, while being 10x lower on cost.
Also really excited to be collaborating with the amazing team at Mayo Clinic to jointly train a new frontier AI model for healthcare.
Our announcements today mark another milestone on the road to humanist superintelligence. You can learn more and about our other new models in our latest blog: https://t.co/v65eop5Ixq
Here are the details from my sneak peek in Redmond last week — Inside Microsoft’s Project Solara: A new platform for devices that run AI agents instead of apps https://t.co/mxDqtEkiRy via @GeekWire
I actually like this badgey thing. This can be SUPER useful for retail popups and a whole bunch of stuff in the service industry like bars, restaurants etc. #MSBuild