Structure prediction models like AlphaFold and Boltz can figure out how proteins are shaped - but only up to a point. The math behind them eats memory fast, and a single GPU tops out at a few thousand residues.

That’s fine for individual proteins. It's not fine for many of the massive molecular machines that drug hunters need to understand - multi-protein complexes far too large for a single GPU to handle. Over 70% of protein complexes in CORUM - a standard database of known mammalian complexes - were simply too big to predict.

NVIDIA’s new framework, Fold-CP, fixes this by splitting the work across many GPUs without losing prediction quality. Applied to the open-source Boltz models and announced at GTC, it pushes the limit from around 2,000 residues on one GPU to over 30,000 on 64.