Microsoft AI explains how small-model ladders guided its 2.8T-parameter MAI-Base-2
hboelman · x · 2026-10-16
Microsoft AI's new lab note on MAI-Base-2 (2.8 trillion parameters) explains its experiment methodology: since you can't run a 2.8T experiment a hundred times, they train a ladder of small models with the same recipe and use them to predict the big model's behavior.
A clever detail: the small runs repeat their data as often as the big run will, so small tests mimic real conditions. The note covers base models, mixture-of-experts, the efficiency story, a bug found via a stability fix, and data provenance. The author also published a plain-language illustrated guide.
Related event: Microsoft AI Completes Pre-training of 3T-Parameter MAI-Base-2(8 posts)→
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