Princeton's ChefNMR2 elucidates small-molecule structures from NMR spectra, 100-1000x faster than frontier LLMs
ZhongingAlong · x · 2026-11-03
- Princeton researchers (Zhong & Seyedsayamdost labs, with Edison Scientific) released ChefNMR2: a generative model plus scientific reasoning agent that performs de novo structure elucidation from molecular formulae and 1D ¹H/¹³C NMR spectra.
- Key points:
- ChefNMR2 is an atomic flow-matching model generating 3D atomic structures directly, unlike SMILES/graph approaches, aiming at large natural products.
- ChefNMR2-Agent augments it with LLMs to reason over and refine candidates.
- It substantially outperforms existing tools, offers calibrated confidence estimates, and runs 2-3 orders of magnitude faster than frontier LLMs.
- Code, weights, a web app and an MCP tool are released. The predecessor ChefNMR (NeurIPS 2025) trained on simulated spectra of 111k+ natural products and hit >65% accuracy on challenging compounds.
Related event: Princeton's ChefNMR2 Decodes Molecular Structures from NMR Spectra(3 posts)→
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