# Model Hub product release

Benchling's Model Hub lets scientists discover, run and track scientific AI models inside Benchling, with each prediction's inputs, model version and timestamp wired back into the R&D record. Previously, running a model meant waiting for DevOps to stand up infrastructure, and results landed on a shared drive disconnected from the sequence that produced them. The hub currently carries structure prediction models including AlphaFold 2, Chai-1, Boltz-2, OpenFold 2, OpenFold 3 and Protenix, plus property prediction models such as Lilly TuneLab, Inductive Bio and open-source DeepSP, with batch prediction and a v3 alpha API.

Benchling's Model Hub lets scientists discover, run and track scientific AI models inside Benchling, with each prediction's inputs, model version and timestamp wired back into the R&D record. Previously, running a model meant waiting for DevOps to stand up infrastructure, and results landed on a shared drive disconnected from the sequence that produced them. The hub currently carries structure prediction models including AlphaFold 2, Chai-1, Boltz-2, OpenFold 2, OpenFold 3 and Protenix, plus property prediction models such as Lilly TuneLab, Inductive Bio and open-source DeepSP, with batch prediction and a v3 alpha API.