Periodic Labs trains Neon on just 1,300 H200s to beat GPT-6 Astra on materials analysis
LiamFedus · x · 2026-09-16
Liam Fedus's Periodic Labs built high-throughput materials labs in Menlo Park that close the loop between experiments and models: the labs generate fresh data, the models learn from it and guide what to try next. Using only 1,300 H200s plus months of proprietary experimental data, the team mid-trained and RL'd an open-weight model (Kimi K2.6) into Neon, a 1T-parameter model that surpasses GPT-6 Astra on their FrontierXRD analysis benchmark. First targets include superconductors, magnets, and semiconductor materials.
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