The technical report https://microsoft.ai/wp-content/uploads/2026/06/main_2026060... has a lot of detail about decontaminating their training data and developing new in-house benchmarks to ensure reliable evaluation. If other models were just overfit to public benchmarks while Microsoft produced something that generalizes better to unseen data, they could've used those in-house benchmarks to argue that point.

Instead, they only do cherry-picked comparisons against Anthropic's small models, and not the full spectrum of competitors.

Without evidence to the contrary, I'll interpret this as just what happens when you're late to the party and insist on doing everything from scratch.

Maybe coaxing reasoning behavior out of their base model without kickstarting it by distilling from existing models provided them with valuable experience that will help improve their future models, or maybe it was an unnecessary waste of time.