H-optimus (Bioptimus)

H-optimus is a ViT-giant vision transformer for histopathology from the French company Bioptimus, pretrained with the DINOv2 self-supervised method so it learns tissue features without labels. H-optimus-0 (2024) was trained on hundreds of millions of tiles from 500k slides and led public benchmarks on release; H-optimus-1 followed. The weights are open and available for research and commercial licensing, which makes the model a common backbone for groups building their own biomarker or diagnostic classifiers. The gap is clinical: it has less clinical validation than commercial products that have gone through regulatory review, so users must validate downstream tasks themselves. For a newcomer: it is a strong, freely downloadable pathology model that other tools can be built on, not a diagnostic product in itself.