text-davinci-002 / - · AgentBench & ToolBench · AgentBench overall · Original standard test set ↗
OpenAI / MODEL EVIDENCE
text-davinci-002 / -
3 benchmarks · 12 observations · 3 sources
Scores at a glance
3 benchmarks · large dot: text-davinci-002 / -; small dots: closest models where reported
Text-Davinci-002 · HaluEval 2.0 · Biomedicine · MaHR · published main comparison ↗
9 more reported results
15.07% · Text-Davinci-002 · HaluEval 2.0 · Biomedicine · MiHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
41.51% · Text-Davinci-002 · HaluEval 2.0 · Finance · MaHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
18.24% · Text-Davinci-002 · HaluEval 2.0 · Finance · MiHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
29.99% · Text-Davinci-002 · HaluEval 2.0 · Science · MaHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
9.19% · Text-Davinci-002 · HaluEval 2.0 · Science · MiHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
37.82% · Text-Davinci-002 · HaluEval 2.0 · Education · MaHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
17.8% · Text-Davinci-002 · HaluEval 2.0 · Education · MiHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
44.51% · Text-Davinci-002 · HaluEval 2.0 · Open Domain · MaHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
25.93% · Text-Davinci-002 · HaluEval 2.0 · Open Domain · MiHR · published main comparison · The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models ↗
text-davinci-002 · Accuracy ↗
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.
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
- The Dawn After the Dark: An Empirical Study on Factuality Hallucination in Large Language Models — published result table ↗
All 7 authors
Li, Junyi, Chen, Jie, Ren, Ruiyang, Cheng, Xiaoxue, Zhao, Wayne Xin, Nie, Jian-Yun, Wen, Ji-Rong
- Holistic Evaluation of Language Models (HELM) ↗
Names used in source tables
Text-Davinci-002 · text-davinci-002 · text-davinci-002 / -