The BraTS-PTG establishes a benchmark and defines a community standard for automated segmentation on post-treatment MRI, utilizing the largest, publicly available, expert-annotated post-treatment glioma MRI dataset. Compared with previous BraTS challenges, it comprises an entirely new dataset of exclusively post-treatment diffuse gliomas and includes a novel tissue class, the RC. Results show promising performance in segmenting sub-regions within the test dataset, indicating the potential of these models in capturing complex tumor structures. Given the significant effort required to annotate multilabel tissue classes in the post-treatment setting, the release of this dataset, which includes expert-voxelwise segmentations of tumor subregions, will support future studies seeking to validate automated segmentation tools for post-treatment diffuse gliomas. The developed models will provide a crucial tool for objectively assessing residual tumor volume for follow-up examinations and treatment planning, with the potential to improve patient management and outcomes. Additionally, they will lay the foundation for future studies aimed at identifying tumor subtypes, assessing aggressiveness, and predicting recurrence risk based solely on MRI findings.