Pretraining progress seems to be coming mostly from data improvements. @who_is_jerbear and I pretrained combinations of year-representative open model recipes and data corpuses across 2019 to 2025 at various small scales. Data improvements contributed 3.24x as many compute multipliers as model improvements did (12.0x vs 3.7x). And the gains stack independently - a better dataset helps every architecture about equally, and vice versa. Here are full results, plus what we think this means for…