What changed
The s1 study curated 1,000 reasoning examples, fine-tuned an open model and used budget forcing to control test-time computation, reporting competitive mathematics results with a comparatively small training set.
Why it matters
It made test-time scaling easier to inspect and suggested that data curation and inference policy can matter as much as dataset size.
What to do
Reproduce the method on a narrow evaluation and measure accuracy, latency and token cost across fixed reasoning budgets.
Caveat
The results concentrated on benchmark reasoning and were published as a preprint, not a general production-reliability study.