Deep Principle releases open-weight Hydrogen-1.0 and says it beats GPT-6-Astra at science

Deep Principle co-founder and CTO Chenru Duan announced on November 2nd that the Hangzhou startup released Hydrogen-1.0, an open-weight scientific research model post-trained on Z.ai's GLM-5.3 using Deep Principle's internal lab records and discovery trajectories. Duan said Hydrogen-1.0 scores 38.3% on FrontierScience-Research versus 33.3% for GPT-6-Astra, and the company priced the weights at GLM-5.3 rates so researchers can rerun the FrontierScience-Research and GPQA-Diamond claims.

Deep Principle releases open-weight Hydrogen-1.0 and says it beats GPT-6-Astra at science Co-founder Chenru Duan says the GLM-5.3 post-train, trained on Deep Principle's own lab records, scores 38.3% on FrontierScience-Research against GPT-6-Astra's 33.3%. By Ryan Merket https://runtimewire.com/author/ryan-merket · Published Primary source: x.com https://x.com/chenru duan/status/2117249292469665838 Why it matters Hydrogen-1.0 tests whether a materials startup's own lab records and discovery trajectories are a training advantage that general labs cannot copy from public data. Because the weights are open and priced by the company at GLM-5.3 rates, other researchers can rerun the FrontierScience-Research and GPQA-Diamond claims and judge whether post-training on full experiment cycles produces better scientific decisions, not better answers. Deep Principle co-founder and CTO Chenru Duan @chenru duan https://x.com/chenru duan introduced Hydrogen-1.0 on November 2nd. It is the Hangzhou startup's first open-weight model for scientific research, built by post-training Z.ai's GLM-5.3 https://runtimewire.com/models/together/zai-org-glm-5.3-ab35037a1203d76c on the company's internal scientific data, laboratory records and discovery trajectories.… When you purchase through links in our articles, we may earn a small commission https://runtimewire.com/affiliate-monetization-standards . This doesn’t affect our editorial independence.