RLTasksby ulam.ai
Models / Microsoft

Microsoft / MODEL EVIDENCE

wizardlm-13b / v1.2

2 benchmarks · 3 observations · 2 sources

Scores at a glance

2 benchmarks · large dot: wizardlm-13b / v1.2; small dots: closest models where reported

AgentBench & ToolBench ↗0.66 points
0.034.01

wizardlm-13b / v1.2 · AgentBench & ToolBench · AgentBench overall · Original standard test set ↗

Closest models by score

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

There are not enough shared scored settings to identify close comparisons reliably.

Filter comparisons to this model →

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. AgentBench: Evaluating LLMs as Agents — published result table ↗

    Xiao Liu, Hao Yu, Hanchen Zhang, Yifan Xu, Xuanyu Lei, Hanyu Lai et al. · 2023

    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

  2. FollowBench: A Multi-level Fine-grained Constraints Following Benchmark for Large Language Models — published result table ↗

    Jiang, Yuxin, Wang, Yufei, Zeng, Xingshan, Zhong, Wanjun, Li, Liangyou, Mi, Fei et al. · 2023

    All 10 authors

    Jiang, Yuxin, Wang, Yufei, Zeng, Xingshan, Zhong, Wanjun, Li, Liangyou, Mi, Fei, Shang, Lifeng, Jiang, Xin, Liu, Qun, Wang, Wei

Names used in source tables

WizardLM-13B-V1.2 · wizardlm-13b / v1.2