qwenlm.github.io2024-12-24officialauthorityHN 5 pts · 0 comments1,156 words
QVQ-72B-Preview is an open-weight multimodal reasoning model built upon Qwen2-VL-72B that achieves a score of 70.3 on the MMMU benchmark. The model evaluates on four datasets, including OlympiadBench which contains 8,476 problems from Olympic mathematics and physics competitions, effectively closing the gap with the o1 model in math and science tasks. However, users should note limitations such as potential language mixing, recursive reasoning loops, and a tendency to lose focus on image content during multi-step visual reasoning.written, reviewed, cited
- The model may mix languages or switch between them unexpectedly, affecting response clarity.
- The team plans to integrate additional modalities into a unified model in the near future.