BedBench Reveals Significant 3D Reasoning Failures in VLMs

The BedBench benchmark shows that vision-language models struggle with 3D reasoning, with top models achieving only 7.2% accuracy on per-color counting tasks compared to 93.3% for humans. Results indicate that models often fail to use recovered properties consistently in composite reasoning tasks.