Using Math Tests to Gauge Pretrain Quality
RyanGreenblatt · x · 2026-07-17
This post explains a model evaluation approach: measuring a model's pretrain quality based on its performance on math tasks in a single forward pass.
The core points are:
- Although imperfect, this metric can serve as a proxy for pretrain quality;
- Crucially, it cannot be improved by post-training, making it a better reflection of the model's underlying capabilities;
- Ideally, one would look at loss, but for closed-weight models, the author cannot access the base model, making it impossible to test loss directly.
Related event: Evaluating Pretrain Quality via Math Zero-Shot Performance(2 posts)→
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