AgentBench & ToolBench ↗0.7 points
openchat-13b / v3.2 · AgentBench & ToolBench · AgentBench overall · Original standard test set ↗
Reported model / MODEL EVIDENCE
openchat-13b / v3.2
1 benchmarks · 1 observations · 1 sources
Scores at a glance
1 benchmarks · large dot: openchat-13b / v3.2; small dots: closest models where reported
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
1 of 1 shared benchmark comparisons
wizardlm-13b / v1.2 →Microsoft
1 of 1 shared benchmark comparisons
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.
- AgentBench: Evaluating LLMs as Agents — published result table ↗
All 22 authors
Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai, Yu Gu, Hangliang Ding, Kaiwen Men, Kejuan Yang, Shudan Zhang, Xiang Deng, Aohan Zeng, Zhengxiao Du, Chenhui Zhang, Sheng Shen, Tianjun Zhang, Yu Su, Huan Sun, Minlie Huang, Yuxiao Dong, Jie Tang
Names used in source tables
openchat-13b / v3.2