OpenAI / MODEL EVIDENCE

GPT-3.5 Turbo

22 benchmarks · 74 observations · 19 sources

Scores at a glance

22 benchmarks · large dot: GPT-3.5 Turbo; small dots: closest models where reported

MMLU ↗68.54%
26.0383.93

GPT-3.5 Turbo · MMLU · EM · % ↗

1.224.4

GPT-3.5-Turbo · CollegeMath · CollegeMath accuracy · MathScale paper · MwpBench evaluation ↗

19.6455.8

GPT-3.5 Turbo · MathOdyssey · Overall accuracy · original model comparison ↗

4471.4

GPT-3.5-Turbo · AGIEval · Accuracy · English · few-shot ↗

5 more reported results

49.5% · GPT-3.5-Turbo · AGIEval · Accuracy · Chinese · few-shot · AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models ↗

47.2% · GPT-3.5-Turbo · AGIEval · Accuracy · All · few-shot · AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models ↗

54.1% · GPT-3.5-Turbo · AGIEval · Accuracy · English · zero-shot · AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models ↗

45% · GPT-3.5-Turbo · AGIEval · Accuracy · Chinese · zero-shot · AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models ↗

46% · GPT-3.5-Turbo · AGIEval · Accuracy · All · zero-shot · AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models ↗

12.3731.03

GPT-3.5-Turbo · BIPIA & InjecAgent (Indirect Prompt Injection) · BIPIA overall attack success · black-box defense comparison ↗

2 more reported results

18.84% · GPT-3.5-Turbo · BIPIA & InjecAgent (Indirect Prompt Injection) · BIPIA overall attack success · black-box defense comparison · Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models ↗

18.43% · GPT-3.5-Turbo · BIPIA & InjecAgent (Indirect Prompt Injection) · BIPIA overall attack success · black-box defense comparison · Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models ↗

32.386

GPT-3.5 Turbo · HumanEval+ · Pass@1 · Llama 3 report · post-trained models ↗

40.292

GPT-3.5 Turbo · HumanEval · Pass@1 · Llama 3 report · post-trained models ↗

MACHIAVELLI ↗22.5 points
16.835.2

gpt-3.5-turbo · MACHIAVELLI · Normalized reward · agent comparison ↗

3 more reported results

100 points · gpt-3.5-turbo · MACHIAVELLI · Normalized power · agent comparison · Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark ↗

102 points · gpt-3.5-turbo · MACHIAVELLI · Normalized disutility · agent comparison · Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark ↗

90 points · gpt-3.5-turbo · MACHIAVELLI · Normalized ethical violations · agent comparison · Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark ↗

14.861.2

gpt-3.5-turbo · τ-Bench · Retail · pass^1 · Original tau-bench · function-calling agents ↗

2 more reported results

10.8% · gpt-3.5-turbo · τ-Bench · Airline · pass^1 · Original tau-bench · function-calling agents · $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains ↗

15.4% · gpt-3.5-turbo · τ-Bench · Domain average · pass^1 · Original tau-bench · function-calling agents · $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains ↗

032

GPT-3.5 Turbo · HealthBench Hard · Weighted rubric score · original model comparison ↗

1.0340.99

GPT-3.5-Turbo · SciBench · Textbook overall accuracy · prompting and tool conditions ↗

3 more reported results

12.17% · GPT-3.5-Turbo · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗

11.99% · GPT-3.5-Turbo · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗

19.91% · GPT-3.5-Turbo · SciBench · Textbook overall accuracy · prompting and tool conditions · SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models ↗

7.641.3

GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Incomplete · compliance rate · reported model comparison ↗

11 more reported results

21% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Unsupported · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

16.9% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Indeterminate · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

8.1% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Safety · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

13.4% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Humanizing · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

95.3% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · No system prompt · Contrast set · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

25.3% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Incomplete · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

12.7% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Unsupported · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

9.9% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Indeterminate · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

0.8% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Safety · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

4.9% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Humanizing · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

90.8% · GPT-3.5-Turbo · CoCoNot (Contextual Non-Compliance) · With system prompt · Contrast set · compliance rate · reported model comparison · The Art of Saying No: Contextual Noncompliance in Language Models ↗

3061

GPT-3.5 Turbo · DarkBench · DarkScore · six-category mean · publisher website comparison ↗

6 more reported results

66% · GPT-3.5 Turbo · DarkBench · Anthropomorphization · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

31% · GPT-3.5 Turbo · DarkBench · Brand bias · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

85% · GPT-3.5 Turbo · DarkBench · Harmful generation · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

62% · GPT-3.5 Turbo · DarkBench · Sneaking · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

26% · GPT-3.5 Turbo · DarkBench · Sycophancy · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

95% · GPT-3.5 Turbo · DarkBench · User retention · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗

28.483.4

GPT-3.5-turbo · ClinicBench · MedQA · Accuracy · zero-shot main comparison ↗

16 more reported results

59.4% · GPT-3.5-turbo · ClinicBench · MedMCQA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

73.5% · GPT-3.5-turbo · ClinicBench · MMLU · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

70.2% · GPT-3.5-turbo · ClinicBench · PubMedQA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

81.1% · GPT-3.5-turbo · ClinicBench · Referral QA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

7.3 F1 points · GPT-3.5-turbo · ClinicBench · Treat Recom. · F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

14.1 ROUGE-L points · GPT-3.5-turbo · ClinicBench · MIMIC · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

10.3 ROUGE-L points · GPT-3.5-turbo · ClinicBench · IU-Xray · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

10.5 ROUGE-L points · GPT-3.5-turbo · ClinicBench · Hospitaliz. Summari. · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

9.2 ROUGE-L points · GPT-3.5-turbo · ClinicBench · Patient Education · ROUGE-L · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

52.3 F1 entity-level points · GPT-3.5-turbo · ClinicBench · BC5 · F1 entity-level · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

46.1 F1 entity-level points · GPT-3.5-turbo · ClinicBench · NCBI · F1 entity-level · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

49.3 Micro F1 points · GPT-3.5-turbo · ClinicBench · DDI · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

50.8 Micro F1 points · GPT-3.5-turbo · ClinicBench · GAD · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

66.4 Micro F1 points · GPT-3.5-turbo · ClinicBench · HoC · Micro F1 · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

57.3% · GPT-3.5-turbo · ClinicBench · Pharma. QA · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

47% · GPT-3.5-turbo · ClinicBench · Drug Inter. · Accuracy · zero-shot main comparison · Large Language Models in the Clinic: A Comprehensive Benchmark ↗

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.

  1. Baichuan 2: Open Large-scale Language Models ↗

    Yang, Aiyuan, Xiao, Bin, Wang, Bingning, Zhang, Borong, Bian, Ce, Yin, Chao et al. · 2023

    All 55 authors

    Yang, Aiyuan, Xiao, Bin, Wang, Bingning, Zhang, Borong, Bian, Ce, Yin, Chao, Lv, Chenxu, Pan, Da, Wang, Dian, Yan, Dong, Yang, Fan, Deng, Fei, Wang, Feng, Liu, Feng, Ai, Guangwei, Dong, Guosheng, Zhao, Haizhou, Xu, Hang, Sun, Haoze, Zhang, Hongda, Liu, Hui, Ji, Jiaming, Xie, Jian, Dai, JunTao, Fang, Kun, Su, Lei, Song, Liang, Liu, Lifeng, Ru, Liyun, Ma, Luyao, Wang, Mang, Liu, Mickel, Lin, MingAn, Nie, Nuolan, Guo, Peidong, Sun, Ruiyang, Zhang, Tao, Li, Tianpeng, Li, Tianyu, Cheng, Wei, Chen, Weipeng, Zeng, Xiangrong, Wang, Xiaochuan, Chen, Xiaoxi, Men, Xin, Yu, Xin, Pan, Xuehai, Shen, Yanjun, Wang, Yiding, Li, Yiyu, Jiang, Youxin, Gao, Yuchen, Zhang, Yupeng, Zhou, Zenan, Wu, Zhiying

  2. Do the Rewards Justify the Means? Measuring Trade-Offs Between Rewards and Ethical Behavior in the MACHIAVELLI Benchmark — published result table ↗

    Alexander Pan, Jun Shern Chan, Andy Zou, Nathaniel Li, Steven Basart, Thomas Woodside et al. · 2023

    All 10 authors

    Alexander Pan, Jun Shern Chan, Andy Zou, Nathaniel Li, Steven Basart, Thomas Woodside, Jonathan Ng, Hanlin Zhang, Scott Emmons, Dan Hendrycks

  3. SciBench: Evaluating College-Level Scientific Problem-Solving Abilities of Large Language Models — published result table ↗

    Wang, Xiaoxuan, Hu, Ziniu, Lu, Pan, Zhu, Yanqiao, Zhang, Jieyu, Subramaniam, Satyen et al. · 2023

    All 10 authors

    Wang, Xiaoxuan, Hu, Ziniu, Lu, Pan, Zhu, Yanqiao, Zhang, Jieyu, Subramaniam, Satyen, Loomba, Arjun R., Zhang, Shichang, Sun, Yizhou, Wang, Wei

  4. Benchmarking and Defending Against Indirect Prompt Injection Attacks on Large Language Models — published result table ↗

    Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie et al. · 2023

    All 7 authors

    Jingwei Yi, Yueqi Xie, Bin Zhu, Emre Kiciman, Guangzhong Sun, Xing Xie, Fangzhao Wu

  5. Evaluating Very Long-Term Conversational Memory of LLM Agents — published result table ↗

    Maharana, Adyasha, Lee, Dong-Ho, Tulyakov, Sergey, Bansal, Mohit, Barbieri, Francesco, Fang, Yuwei · 2024

  6. GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers — published result table ↗

    Qintong Li, Leyang Cui, Xueliang Zhao, Lingpeng Kong, Wei Bi · 2024

  7. MathScale: Scaling Instruction Tuning for Mathematical Reasoning — published result table ↗

    Zhengyang Tang, Xingxing Zhang, Benyou Wang, Furu Wei · 2024

  8. Large Language Models in the Clinic: A Comprehensive Benchmark — published result table ↗

    Liu, Fenglin, Li, Zheng, Zhou, Hongjian, Yin, Qingyu, Yang, Jingfeng, Tang, Xianfeng et al. · 2024

    All 19 authors

    Liu, Fenglin, Li, Zheng, Zhou, Hongjian, Yin, Qingyu, Yang, Jingfeng, Tang, Xianfeng, Luo, Chen, Zeng, Ming, Jiang, Haoming, Gao, Yifan, Nigam, Priyanka, Nag, Sreyashi, Yin, Bing, Hua, Yining, Zhou, Xuan, Rohanian, Omid, Thakur, Anshul, Clifton, Lei, Clifton, David A.

  9. MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures — published result table ↗

    Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain et al. · 2024

    All 8 authors

    Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain, Graham Neubig, Yang You

  10. $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains — published result table ↗

    Yao, Shunyu, Shinn, Noah, Razavi, Pedram, Narasimhan, Karthik · 2024

  11. AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents — published result table ↗

    Edoardo Debenedetti, Jie Zhang, Mislav Balunović, Luca Beurer-Kellner, Marc Fischer, Florian Tramèr · 2024

  12. MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data — published result table ↗

    Meng Fang, Xiangpeng Wan, Fei Lu, Fei Xing, Kai Zou · 2024

  13. The Art of Saying No: Contextual Noncompliance in Language Models — published result table ↗

    Brahman, Faeze, Kumar, Sachin, Balachandran, Vidhisha, Dasigi, Pradeep, Pyatkin, Valentina, Ravichander, Abhilasha et al. · 2024

    All 14 authors

    Brahman, Faeze, Kumar, Sachin, Balachandran, Vidhisha, Dasigi, Pradeep, Pyatkin, Valentina, Ravichander, Abhilasha, Wiegreffe, Sarah, Dziri, Nouha, Chandu, Khyathi, Hessel, Jack, Tsvetkov, Yulia, Smith, Noah A., Choi, Yejin, Hajishirzi, Hannaneh

  14. The Llama 3 Herd of Models — published result table ↗

    Grattafiori, Aaron, Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad et al. · 2024

    All 561 authors

    Grattafiori, Aaron, Dubey, Abhimanyu, Jauhri, Abhinav, Pandey, Abhinav, Kadian, Abhishek, Al-Dahle, Ahmad, Letman, Aiesha, Mathur, Akhil, Schelten, Alan, Vaughan, Alex, Yang, Amy, Fan, Angela, Goyal, Anirudh, Hartshorn, Anthony, Yang, Aobo, Mitra, Archi, Sravankumar, Archie, Korenev, Artem, Hinsvark, Arthur, Rao, Arun, Zhang, Aston, Rodriguez, Aurelien, Gregerson, Austen, Spataru, Ava, Roziere, Baptiste, Biron, Bethany, Tang, Binh, Chern, Bobbie, Caucheteux, Charlotte, Nayak, Chaya, Bi, Chloe, Marra, Chris, McConnell, Chris, Keller, Christian, Touret, Christophe, Wu, Chunyang, Wong, Corinne, Ferrer, Cristian Canton, Nikolaidis, Cyrus, Allonsius, Damien, Song, Daniel, Pintz, Danielle, Livshits, Danny, Wyatt, Danny, Esiobu, David, Choudhary, Dhruv, Mahajan, Dhruv, Garcia-Olano, Diego, Perino, Diego, Hupkes, Dieuwke, Lakomkin, Egor, AlBadawy, Ehab, Lobanova, Elina, Dinan, Emily, Smith, Eric Michael, Radenovic, Filip, Guzmán, Francisco, Zhang, Frank, Synnaeve, Gabriel, Lee, Gabrielle, Anderson, Georgia Lewis, Thattai, Govind, Nail, Graeme, Mialon, Gregoire, Pang, Guan, Cucurell, Guillem, Nguyen, Hailey, Korevaar, Hannah, Xu, Hu, Touvron, Hugo, Zarov, Iliyan, Ibarra, Imanol Arrieta, Kloumann, Isabel, Misra, Ishan, Evtimov, Ivan, Zhang, Jack, Copet, Jade, Lee, Jaewon, Geffert, Jan, Vranes, Jana, Park, Jason, Mahadeokar, Jay, Shah, Jeet, van der Linde, Jelmer, Billock, Jennifer, Hong, Jenny, Lee, Jenya, Fu, Jeremy, Chi, Jianfeng, Huang, Jianyu, Liu, Jiawen, Wang, Jie, Yu, Jiecao, Bitton, Joanna, Spisak, Joe, Park, Jongsoo, Rocca, Joseph, Johnstun, Joshua, Saxe, Joshua, Jia, Junteng, Alwala, Kalyan Vasuden, Prasad, Karthik, Upasani, Kartikeya, Plawiak, Kate, Li, Ke, Heafield, Kenneth, Stone, Kevin, El-Arini, Khalid, Iyer, Krithika, Malik, Kshitiz, Chiu, Kuenley, Bhalla, Kunal, Lakhotia, Kushal, Rantala-Yeary, Lauren, van der Maaten, Laurens, Chen, Lawrence, Tan, Liang, Jenkins, Liz, Martin, Louis, Madaan, Lovish, Malo, Lubo, Blecher, Lukas, Landzaat, Lukas, de Oliveira, Luke, Muzzi, Madeline, Pasupuleti, Mahesh, Singh, Mannat, Paluri, Manohar, Kardas, Marcin, Tsimpoukelli, Maria, Oldham, Mathew, Rita, Mathieu, Pavlova, Maya, Kambadur, Melanie, Lewis, Mike, Si, Min, Singh, Mitesh Kumar, Hassan, Mona, Goyal, Naman, Torabi, Narjes, Bashlykov, Nikolay, Bogoychev, Nikolay, Chatterji, Niladri, Zhang, Ning, Duchenne, Olivier, Çelebi, Onur, Alrassy, Patrick, Zhang, Pengchuan, Li, Pengwei, Vasic, Petar, Weng, Peter, Bhargava, Prajjwal, Dubal, Pratik, Krishnan, Praveen, Koura, Punit Singh, Xu, Puxin, He, Qing, Dong, Qingxiao, Srinivasan, Ragavan, Ganapathy, Raj, Calderer, Ramon, Cabral, Ricardo Silveira, Stojnic, Robert, Raileanu, Roberta, Maheswari, Rohan, Girdhar, Rohit, Patel, Rohit, Sauvestre, Romain, Polidoro, Ronnie, Sumbaly, Roshan, Taylor, Ross, Silva, Ruan, Hou, Rui, Wang, Rui, Hosseini, Saghar, Chennabasappa, Sahana, Singh, Sanjay, Bell, Sean, Kim, Seohyun Sonia, Edunov, Sergey, Nie, Shaoliang, Narang, Sharan, Raparthy, Sharath, Shen, Sheng, Wan, Shengye, Bhosale, Shruti, Zhang, Shun, Vandenhende, Simon, Batra, Soumya, Whitman, Spencer, Sootla, Sten, Collot, Stephane, Gururangan, Suchin, Borodinsky, Sydney, Herman, Tamar, Fowler, Tara, Sheasha, Tarek, Georgiou, Thomas, Scialom, Thomas, Speckbacher, Tobias, Mihaylov, Todor, Xiao, Tong, Karn, Ujjwal, Goswami, Vedanuj, Gupta, Vibhor, Ramanathan, Vignesh, Kerkez, Viktor, Gonguet, Vincent, Do, Virginie, Vogeti, Vish, Albiero, Vítor, Petrovic, Vladan, Chu, Weiwei, Xiong, Wenhan, Fu, Wenyin, Meers, Whitney, Martinet, Xavier, Wang, Xiaodong, Wang, Xiaofang, Tan, Xiaoqing Ellen, Xia, Xide, Xie, Xinfeng, Jia, Xuchao, Wang, Xuewei, Goldschlag, Yaelle, Gaur, Yashesh, Babaei, Yasmine, Wen, Yi, Song, Yiwen, Zhang, Yuchen, Li, Yue, Mao, Yuning, Coudert, Zacharie Delpierre, Yan, Zheng, Chen, Zhengxing, Papakipos, Zoe, Singh, Aaditya, Srivastava, Aayushi, Jain, Abha, Kelsey, Adam, Shajnfeld, Adam, Gangidi, Adithya, Victoria, Adolfo, Goldstand, Ahuva, Menon, Ajay, Sharma, Ajay, Boesenberg, Alex, Baevski, Alexei, Feinstein, Allie, Kallet, Amanda, Sangani, Amit, Teo, Amos, Yunus, Anam, Lupu, Andrei, Alvarado, Andres, Caples, Andrew, Gu, Andrew, Ho, Andrew, Poulton, Andrew, Ryan, Andrew, Ramchandani, Ankit, Dong, Annie, Franco, Annie, Goyal, Anuj, Saraf, Aparajita, Chowdhury, Arkabandhu, Gabriel, Ashley, Bharambe, Ashwin, Eisenman, Assaf, Yazdan, Azadeh, James, Beau, Maurer, Ben, Leonhardi, Benjamin, Huang, Bernie, Loyd, Beth, De Paola, Beto, Paranjape, Bhargavi, Liu, Bing, Wu, Bo, Ni, Boyu, Hancock, Braden, Wasti, Bram, Spence, Brandon, Stojkovic, Brani, Gamido, Brian, Montalvo, Britt, Parker, Carl, Burton, Carly, Mejia, Catalina, Liu, Ce, Wang, Changhan, Kim, Changkyu, Zhou, Chao, Hu, Chester, Chu, Ching-Hsiang, Cai, Chris, Tindal, Chris, Feichtenhofer, Christoph, Gao, Cynthia, Civin, Damon, Beaty, Dana, Kreymer, Daniel, Li, Daniel, Adkins, David, Xu, David, Testuggine, Davide, David, Delia, Parikh, Devi, Liskovich, Diana, Foss, Didem, Wang, Dingkang, Le, Duc, Holland, Dustin, Dowling, Edward, Jamil, Eissa, Montgomery, Elaine, Presani, Eleonora, Hahn, Emily, Wood, Emily, Le, Eric-Tuan, Brinkman, Erik, Arcaute, Esteban, Dunbar, Evan, Smothers, Evan, Sun, Fei, Kreuk, Felix, Tian, Feng, Kokkinos, Filippos, Ozgenel, Firat, Caggioni, Francesco, Kanayet, Frank, Seide, Frank, Florez, Gabriela Medina, Schwarz, Gabriella, Badeer, Gada, Swee, Georgia, Halpern, Gil, Herman, Grant, Sizov, Grigory, Guangyi, Zhang, Lakshminarayanan, Guna, Inan, Hakan, Shojanazeri, Hamid, Zou, Han, Wang, Hannah, Zha, Hanwen, Habeeb, Haroun, Rudolph, Harrison, Suk, Helen, Aspegren, Henry, Goldman, Hunter, Zhan, Hongyuan, Damlaj, Ibrahim, Molybog, Igor, Tufanov, Igor, Leontiadis, Ilias, Veliche, Irina-Elena, Gat, Itai, Weissman, Jake, Geboski, James, Kohli, James, Lam, Janice, Asher, Japhet, Gaya, Jean-Baptiste, Marcus, Jeff, Tang, Jeff, Chan, Jennifer, Zhen, Jenny, Reizenstein, Jeremy, Teboul, Jeremy, Zhong, Jessica, Jin, Jian, Yang, Jingyi, Cummings, Joe, Carvill, Jon, Shepard, Jon, McPhie, Jonathan, Torres, Jonathan, Ginsburg, Josh, Wang, Junjie, Wu, Kai, U, Kam Hou, Saxena, Karan, Khandelwal, Kartikay, Zand, Katayoun, Matosich, Kathy, Veeraraghavan, Kaushik, Michelena, Kelly, Li, Keqian, Jagadeesh, Kiran, Huang, Kun, Chawla, Kunal, Huang, Kyle, Chen, Lailin, Garg, Lakshya, A, Lavender, Silva, Leandro, Bell, Lee, Zhang, Lei, Guo, Liangpeng, Yu, Licheng, Moshkovich, Liron, Wehrstedt, Luca, Khabsa, Madian, Avalani, Manav, Bhatt, Manish, Mankus, Martynas, Hasson, Matan, Lennie, Matthew, Reso, Matthias, Groshev, Maxim, Naumov, Maxim, Lathi, Maya, Keneally, Meghan, Liu, Miao, Seltzer, Michael L., Valko, Michal, Restrepo, Michelle, Patel, Mihir, Vyatskov, Mik, Samvelyan, Mikayel, Clark, Mike, Macey, Mike, Wang, Mike, Hermoso, Miquel Jubert, Metanat, Mo, Rastegari, Mohammad, Bansal, Munish, Santhanam, Nandhini, Parks, Natascha, White, Natasha, Bawa, Navyata, Singhal, Nayan, Egebo, Nick, Usunier, Nicolas, Mehta, Nikhil, Laptev, Nikolay Pavlovich, Dong, Ning, Cheng, Norman, Chernoguz, Oleg, Hart, Olivia, Salpekar, Omkar, Kalinli, Ozlem, Kent, Parkin, Parekh, Parth, Saab, Paul, Balaji, Pavan, Rittner, Pedro, Bontrager, Philip, Roux, Pierre, Dollar, Piotr, Zvyagina, Polina, Ratanchandani, Prashant, Yuvraj, Pritish, Liang, Qian, Alao, Rachad, Rodriguez, Rachel, Ayub, Rafi, Murthy, Raghotham, Nayani, Raghu, Mitra, Rahul, Parthasarathy, Rangaprabhu, Li, Raymond, Hogan, Rebekkah, Battey, Robin, Wang, Rocky, Howes, Russ, Rinott, Ruty, Mehta, Sachin, Siby, Sachin, Bondu, Sai Jayesh, Datta, Samyak, Chugh, Sara, Hunt, Sara, Dhillon, Sargun, Sidorov, Sasha, Pan, Satadru, Mahajan, Saurabh, Verma, Saurabh, Yamamoto, Seiji, Ramaswamy, Sharadh, Lindsay, Shaun, Lindsay, Shaun, Feng, Sheng, Lin, Shenghao, Zha, Shengxin Cindy, Patil, Shishir, Shankar, Shiva, Zhang, Shuqiang, Zhang, Shuqiang, Wang, Sinong, Agarwal, Sneha, Sajuyigbe, Soji, Chintala, Soumith, Max, Stephanie, Chen, Stephen, Kehoe, Steve, Satterfield, Steve, Govindaprasad, Sudarshan, Gupta, Sumit, Deng, Summer, Cho, Sungmin, Virk, Sunny, Subramanian, Suraj, Choudhury, Sy, Goldman, Sydney, Remez, Tal, Glaser, Tamar, Best, Tamara, Koehler, Thilo, Robinson, Thomas, Li, Tianhe, Zhang, Tianjun, Matthews, Tim, Chou, Timothy, Shaked, Tzook, Vontimitta, Varun, Ajayi, Victoria, Montanez, Victoria, Mohan, Vijai, Kumar, Vinay Satish, Mangla, Vishal, Ionescu, Vlad, Poenaru, Vlad, Mihailescu, Vlad Tiberiu, Ivanov, Vladimir, Li, Wei, Wang, Wenchen, Jiang, Wenwen, Bouaziz, Wes, Constable, Will, Tang, Xiaocheng, Wu, Xiaojian, Wang, Xiaolan, Wu, Xilun, Gao, Xinbo, Kleinman, Yaniv, Chen, Yanjun, Hu, Ye, Jia, Ye, Qi, Ye, Li, Yenda, Zhang, Yilin, Zhang, Ying, Adi, Yossi, Nam, Youngjin, Yu, Wang, Zhao, Yu, Hao, Yuchen, Qian, Yundi, Li, Yunlu, He, Yuzi, Rait, Zach, DeVito, Zachary, Rosnbrick, Zef, Wen, Zhaoduo, Yang, Zhenyu, Zhao, Zhiwei, Ma, Zhiyu

  15. HealthBench: Evaluating Large Language Models Towards Improved Human Health — published result table ↗

    Arora, Rahul K., Wei, Jason, Hicks, Rebecca Soskin, Bowman, Preston, Quiñonero-Candela, Joaquin, Tsimpourlas, Foivos et al. · 2025

    All 12 authors

    Arora, Rahul K., Wei, Jason, Hicks, Rebecca Soskin, Bowman, Preston, Quiñonero-Candela, Joaquin, Tsimpourlas, Foivos, Sharman, Michael, Shah, Meghan, Vallone, Andrea, Beutel, Alex, Heidecke, Johannes, Singhal, Karan

  16. Are large language models superhuman chemists? — published result table ↗

    Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Martiño Ríos-García, Benedict Emoekabu, Aswanth Krishnan et al. · 2024

    All 35 authors

    Adrian Mirza, Nawaf Alampara, Sreekanth Kunchapu, Martiño Ríos-García, Benedict Emoekabu, Aswanth Krishnan, Tanya Gupta, Mara Schilling-Wilhelmi, Macjonathan Okereke, Anagha Aneesh, Amir Mohammad Elahi, Mehrdad Asgari, Juliane Eberhardt, Hani M. Elbeheiry, María Victoria Gil, Maximilian Greiner, Caroline T. Holick, Christina Glaubitz, Tim Hoffmann, Abdelrahman Ibrahim, Lea C. Klepsch, Yannik Köster, Fabian Alexander Kreth, Jakob Meyer, Santiago Miret, Jan Matthias Peschel, Michael Ringleb, Nicole Roesner, Johanna Schreiber, Ulrich S. Schubert, Leanne M. Stafast, Dinga Wonanke, Michael Pieler, Philippe Schwaller, Kevin Maik Jablonka

  17. DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data — published result table ↗

    Esben Kran, Hieu Minh Nguyen, Akash Kundu, Sami Jawhar, Jinsuk Park, Mateusz Maria Jurewicz · 2025

  18. LawBench: Benchmarking Legal Knowledge of Large Language Models — published result table ↗

    Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, Fengzhe Zhou, Zhuo Han, Songyang Zhang et al. · 2023

    All 9 authors

    Zhiwei Fei, Xiaoyu Shen, Dawei Zhu, Fengzhe Zhou, Zhuo Han, Songyang Zhang, Kai Chen, Zongwen Shen, Jidong Ge

  19. AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models — published result table ↗

    Wanjun Zhong, Ruixiang Cui, Yiduo Guo, Yaobo Liang, Shuai Lu, Yanlin Wang et al. · 2023

    All 9 authors

    Wanjun Zhong, Ruixiang Cui, Yiduo Guo, Yaobo Liang, Shuai Lu, Yanlin Wang, Amin Saied, Weizhu Chen, Nan Duan

Names used in source tables

GPT-3.5 Turbo · GPT-3.5-Turbo · GPT-3.5-turbo · gpt-3.5-turbo