Models New
Deep Principle releases Hydrogen-1.0, a roughly 753-billion-parameter open-weight model for chemistry, materials and life sciences built on GLM-5.3
Published:
Hangzhou-based Deep Principle released Hydrogen-1.0, a scientific model made by post-training Z.ai's GLM-5.3 on chemistry, materials-science and life-sciences data, together with laboratory records and agent trajectories from its own labs. The weights are on Hugging Face under an MIT licence, which lists about 753 billion parameters.
MarkTechPost reports a mixture-of-experts design with a 1-million-token context and 128,000-token maximum output, plus NVFP4 and MXFP4 builds. Citing the company's figures, it reports 38.3% on FrontierScience-Research against 33.3% for GPT-6 Astra, roughly matching Kimi K3 on GPQA-Diamond, while trailing GPT-6 Astra on NMR structure elucidation.
Deep Principle presents it as an open, inspectable alternative to the proprietary models behind recent AI science results. The full training datasets and recipes are not released, according to MarkTechPost.
Caveat. All benchmark results are self-reported and not independently reproduced. The announcement carries no timestamp: MarkTechPost reported it at 18:41 UTC on Monday, but the model files were last updated at 09:00 UTC, so the release may slightly predate this window. The afternoon edition did not carry it.
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