Broadening access to Skala creates a faster path to predictive DFT

Summary

Microsoft Research's Skala 1.1 demonstrates the continuous improvement of their deep-learning DFT approach. Trained on 2.5× more data than its predecessor, it delivers substantially higher accuracy across key molecular simulation challenges, including thermochemistry, reaction kinetics, and molecular structure prediction. Skala is now available in CP2K and is being integrated into Psi4, FHI-aims, ORCA, and VASP, bringing next-generation DFT accuracy closer to the communities that rely on these codes. Microsoft Research also introduces a living benchmark to track the computational performance of successive Skala releases, helping the community measure and accelerate progress toward greater accuracy and efficiency.