Deep Principle releases Hydrogen-1.0, an open-weight scientific reasoning model built on GLM-5.3

AIModelScope announces Hydrogen-1.0, an open-weight model from Deep Principle built on GLM-5.3 with a 1M context window for chemistry, materials science, and life sciences. The post says it outperforms GPT-6 Astra on FrontierScience-Research in the authors' evaluation and improves over GLM-5.3 on GPQA Diamond.

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The post separates the authors' own benchmark comparisons from the model's features, so readers can judge the claims and the open-weight release terms.

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Scientific reasoning shaped by laboratory experience. Hydrogen-1.0 is an open-weight model from Deep Principle, built on GLM-5.3 with 1M context for chemistry, materials science, and life sciences. 🤖 https://modelscope.cn/models/deep-principle/Hydrogen-1.0

🏆 Stronger scientific reasoning: Outperforms GPT-6 Astra on FrontierScience-Research in the authors' evaluation, while improving over GLM-5.3 on GPQA Diamond.

🔬 Learn from scientific work: Combines SFT and RL using domain knowledge, laboratory records, and complete discovery trajectories, including failed attempts and revised hypotheses.

🧬 Explore promising materials: After five search rounds, the mean best-so-far HOMO–LUMO gap reaches 4.318 eV, versus 3.689 for GPT-6 Astra and 3.353 for Kimi-K3 in the transition-metal-complex evaluation.

🛠️ Research with tools: Demonstrations span simulation debugging, reaction-network exploration, NMR analysis, and experimental protocol planning.

📜 Weights: MIT. Independently authored supporting code and documentation: Apache 2.0.

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ModelScope · x.comPublished Nov 2, 3:00 AM ET

Original title: Scientific reasoning shaped by laboratory experience. Hydrogen-1.0 is an open-weight model from Deep Principle, built on GLM-5.3 with 1M ...

Deep Principle releases Hydrogen-1.0, an open-weight scientific reasoning model built on GLM-5.3

AIWhy it matters.

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