UC Berkeley's NovaSky open-sources Sky-T1-32B: o1-preview-class reasoning for under $450 of H100 time
The NovaSky team at UC Berkeley released Sky-T1-32B-Preview on Hugging Face, the first reasoning model it describes as fully open: weights, the 17K-sample training set, the data-generation and evaluation code, and a technical report are all downloadable.
Sky-T1 is a supervised fine-tune of the open Qwen2.5-32B-Instruct base on 17K curated traces generated by QwQ-32B-Preview with rejection sampling — 5K coding from APPs and TACO, 10K math from AIME, MATH and Olympiad subsets, 1K science and puzzle data — trained for 3 epochs in 19 hours on 8 H100s for roughly $450 at Lambda Cloud pricing. It reports Math500 82.4 against o1-preview's 81.4, AIME2024 43.3 against 40.0, and LiveCodeBench-Medium 56.8 against 54.9.

WHY IT MATTERS
A fully reproducible, sub-$500 recipe for o1-preview-class reasoning with all data and code released is the clearest statement yet that reasoning capability is not scarce. The fine-tuning floor collapsed: frontier-adjacent reasoning is now a single-node, single-day, few-hundred-dollar job that any lab, startup or hobbyist can copy and improve on, which undercuts the claim that reasoning justifies the closed-lab price premium.


