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Pretraining is where the model learns its core world knowledge, reasoning, and coding abilities. Over the last nine months, Meta rebuilt its pretraining stack with improvements to model architecture, optimization, and data curation. The payoff is substantial efficiency gains: Meta can reach the same capabilities with over an order of magnitude less compute than its previous model, Llama 4 Maverick. For devs, ‘an order of magnitude’ means roughly 10x more compute-efficient — a major improvement that makes larger future models more financially and practically viable.