Video-MME ↗72.1%
InternVL2_5-78B · VideoMME · Overall (no subtitles) · % ↗
Shanghai AI Lab,SenseTime,Tsinghua University,Nanjing University,Fudan University,Chinese University of Hong Kong (CUHK),Shanghai Jiao Tong University / MODEL EVIDENCE
InternVL2 5-78B
2 benchmarks · 2 observations · 2 sources · released 2024-12-06
Scores at a glance
2 benchmarks · large dot: InternVL2 5-78B; small dots: closest models where reported
PhysBench ↗51.16%
InternVL2.5-78B 🥈 · PhysBench · Overall accuracy · physical-world question answering ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
2 of 2 shared benchmark comparisons
GPT-4V →OpenAI
2 of 2 shared benchmark comparisons
How similarity is measured
Mean absolute gap in percentile positions on shared benchmark settings; lower is closer. At least 60% overlap is required, with a minimum of three when available. Independent evaluations are used when there are at least three; otherwise published report comparisons are used. Repeated model observations within one setting are averaged before ranking. Writing-style traits and composite indices are excluded. This describes similarity, not an overall quality ranking.
Sources
Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.
- PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding — published result table ↗
- Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis ↗
All 21 authors
Fu, Chaoyou, Dai, Yuhan, Luo, Yongdong, Li, Lei, Ren, Shuhuai, Zhang, Renrui, Wang, Zihan, Zhou, Chenyu, Shen, Yunhang, Zhang, Mengdan, Chen, Peixian, Li, Yanwei, Lin, Shaohui, Zhao, Sirui, Li, Ke, Xu, Tong, Zheng, Xiawu, Chen, Enhong, Shan, Caifeng, He, Ran, Sun, Xing
Names used in source tables
InternVL2.5-78B 🥈 · InternVL2_5-78B