Dwarkesh Pretraining Replication Finds Data Gains Deliver 3.24x More Compute Multipliers Than Model Gains
josh_wills · x · 2026-09-09
Dwarkesh Patel and collaborator @whoisjerbear pretrained combinations of year-representative open model recipes and data corpora from 2019–2025 at various small scales. Key findings:
- Data improvements contributed 3.24x as many compute multipliers as model improvements (12.0x vs 3.7x), suggesting pretraining progress now comes mostly from data.
- The gains stack independently: a better dataset helps every architecture about equally, and vice versa.
Full results and implications for future AI progress are published in the linked writeup.
Related event: Dwarkesh Experiments: Data Drives Most Pretraining Progress(3 posts)→
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