OpenAI / MODEL EVIDENCE

MM-ReAct-GPT-3.5

1 benchmarks · 1 observations · 1 sources

Scores at a glance

1 benchmarks · large dot: MM-ReAct-GPT-3.5; small dots: closest models where reported

13.444.6

MM-ReAct-GPT-3.5 · MM-Vet & MM-Vet v2 · MM-Vet total · original integrated-capability evaluation ↗

Closest models by score

Similar positions on shared benchmark leaderboards. Smaller gaps are closer.

6.7 percentile-point gap

1 of 1 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.

  1. MM-Vet: Evaluating Large Multimodal Models for Integrated Capabilities — published result table ↗

    Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu et al. · 2023

    All 8 authors

    Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, Lijuan Wang

Names used in source tables

MM-ReAct-GPT-3.5