Deep Principle introduced Hydrogen-1.0 on November 4, 2026, describing it as an open-weight model for chemistry and materials research. It can help plan experiments, run computational workflows and explore material candidates, and is available through downloads, an API and the company’s Mira AI Scientist. In a five-round evaluation of transition-metal complexes, the company says Hydrogen-1.0 reached a mean best-so-far HOMO–LUMO gap of 4.318 eV, compared with 3.689 eV for GPT-6-Astra and 3.353 eV for Kimi-K3. The announcement does not provide independent validation or detailed settings for these evaluations.
Why it matters
Chemistry and materials teams can download or access a model built for research workflows, but the announcement alone does not establish how well it performs in independent laboratory use.
