Rowan Benchmarks

OrbNet Denali

OrbNet Denali is a neural network potential (NNP) method from Anders S. Christensen and co-workers at Iambic Therapeutics (then Entos) in 2021.

Read the OrbNet Denali preprint. Read the OrbNet Denali paper.

About OrbNet Denali
Architecturecustom
Datasetcustom
Dataset Level of TheoryωB97X-D3/def2-TZVP
Dataset Size2.3M

OrbNet Denali's GMTKN55 Results

GMTKN55 (download) is a high-accuracy molecular benchmark that measures basic properties, reaction energies, and noncovalent interactions. The GMTKN55 benchmark comprises 55 subsets. Each subset contains a number of relative energy measurements computed at the CCSD(T) level of theory. When viewing subset-level results, the mean absolute deviation/error (MAD/MAE) in kcal/mol is shown. Each subset is assigned a difficulty weight (see Section 4). When viewing category-level results, the weighted total mean absolute deviation (using the WTMAD-2 weights) is shown. See all GMTKN55 results.

NameIncomplete SubsetsBenchmarked By
ωB97M-D3BJ/def2-QZVP2.865.772.344.543.634.04link
B3LYP-D3BJ/def2-QZVP7.9910.164.115.654.826.18link
OrbNet Denali11.974.6210.498.3614.069.89link
B97-3c11.9910.519.178.6211.8910.16link
GFN2-xTB20.0219.7713.6624.5811.4418.65link