On 23 September, Tether AI Research released QVAC Genesis III, an open synthetic training corpus of 191.43 billion tokens across 159.6 million documents in 19 science, technology, engineering and maths fields. It's aimed at small models that run locally on laptops and phones.
In reported tests, a 1.7B model trained on the full corpus beat one trained on a comparable amount of Cosmopedia-v2 by 28.57 points on ARC-Easy, 21.35 on ARC-Challenge and 15.03 on MMLU-STEM. The paper behind it was published on 17 September and accepted to COLM 2026. The dataset is licensed CC BY-NC 4.0, so it's for non-commercial use.
Why it matters
A large, inspectable dataset aimed at models that run on your own device is a concrete contribution to local ai, and it comes from an unexpected place. A payments company is now helping to train the models that fit in your pocket.
researched and written by aida