Gemini 1.5 Pro · Scale Labs · Risk elicitation score ↗
Google / MODEL EVIDENCE
Gemini 1.5 Pro
32 benchmarks · 51 observations · 25 sources
Scores at a glance
32 benchmarks · large dot: Gemini 1.5 Pro; small dots: closest models where reported
Gemini 1.5 Pro · Scale Labs · Score ↗
Gemini-1.5-pro · AIR-Bench (Audio Instruction & Reasoning) · Chat score · open-ended chat ↗
Gemini-1.5-pro · PhysBench · Overall accuracy · physical-world question answering ↗
Gemini-1.5-Pro · ZebraLogic · Grid-level accuracy · complete puzzles ↗
Gemini 1.5 Pro · PlanBench · Blocksworld ↗
Gemini-1.5-Pro · MedXpertQA (Text & MM) · Multimodal-model text subset ↗
1 more reported result
34.1% · Gemini-1.5-Pro · MedXpertQA (Text & MM) · Multimodal subset · MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding ↗
Gemini-1.5-Pro · HELMET (How to Evaluate Long-Context Models Effectively and Thoroughly) · 128k context · 128k inputs ↗
Gemini-1.5-Pro · RULER · 128k context · HELMET paper · RULER comparison ↗
Gemini-1.5-Pro · InfiniteBench · InfiniteBench aggregate · HELMET paper · original-author harness ↗
Gemini-1.5-Pro · Needle In A Haystack (NIAH) & MM-NIAH · Text NIAH · 128k · HELMET paper · 128k text retrieval ↗
Gemini 1.5 Pro · AgentHarm & AgentDojo · AgentDojo targeted attack success · agent comparison ↗
1 more reported result
45.63% · Gemini 1.5 Pro · AgentHarm & AgentDojo · AgentDojo benign utility · agent comparison · AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents ↗
Gemini 1.5 Pro · DocVQA · Test ANLS · Llama 3 vision report · published comparison ↗
Gemini 1.5 Pro · ChartQA · Test accuracy · chain of thought · Llama 3 vision report · published comparison ↗
Gemini 1.5 Pro · TextVQA · Validation accuracy · Llama 3 vision report · published comparison ↗
Gemini 1.5 Pro · AndroidWorld · Task success · original comparison ↗
2 more reported results
19.4% · Gemini 1.5 Pro · AndroidWorld · Task success · original comparison · AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents ↗
22.8% · Gemini 1.5 Pro · AndroidWorld · Task success · original comparison · AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents ↗
Gemini-1.5-pro · JudgeBench · Overall pairwise accuracy · Arena-Hard judge scaffold ↗
gemini-1.5-pro · τ-Bench · Retail · pass^1 · Original tau-bench · function-calling agents ↗
2 more reported results
14% · gemini-1.5-pro · τ-Bench · Airline · pass^1 · Original tau-bench · function-calling agents · $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains ↗
17.9% · gemini-1.5-pro · 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 ↗
Gemini-1.5-Pro · WildBench · WB-Score · reported comparison ↗
Gemini-1.5 Pro · MedAgentBench · Overall task success · original evaluation ↗
Gemini 1.5 Pro · FACTS Grounding · Final factuality score · judge average · eligibility-filtered evaluation ↗
Gemini 1.5 Pro · MixEval & MixEval-Hard · accuracy · original comparison ↗
1 more reported result
84.2% · Gemini 1.5 Pro · MixEval & MixEval-Hard · accuracy · original comparison · MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures ↗
Gemini 1.5 Pro · WildHallucinations · WildFActScore · all entities · original evaluation ↗
Gemini 1.5 Pro · HumanEval · Pass@1 · OpenAI Simple Evals · archived July 2025 ↗
Gemini 1.5 Pro · DROP (Discrete Reasoning Over Paragraphs) · F1 · three-shot · OpenAI Simple Evals · archived July 2025 ↗
Gemini 1.5 Pro · HARP · Human Annotated Reasoning Problems · Short-answer overall accuracy · zero-shot chain of thought ↗
Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · Text Retrieval · published average · 128k context test ↗
5 more reported results
83% · Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · Visual Retrieval · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
100% · Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · Audio Retrieval · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
53% · Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · RAG · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
38% · Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · SQL · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
68% · Gemini 1.5 Pro · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · Many-Shot ICL · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
Gemini-1.5 Pro · SpatialBench / VSI-Bench · overall average · original full-set evaluation ↗
Gemini 1.5 Pro · CountBench & PixMo-Count · CountBenchQA · test accuracy · Molmo and PixMo · Table 1 comparison ↗
1 more reported result
64.3% · Gemini 1.5 Pro · CountBench & PixMo-Count · test accuracy · Molmo and PixMo · Table 1 comparison · Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models ↗
Gemini 1.5 Pro · RealWorldQA · accuracy · Molmo and PixMo · Table 1 comparison ↗
Gemini 1.5 Pro · DarkBench · DarkScore · six-category mean · publisher website comparison ↗
6 more reported results
34% · Gemini 1.5 Pro · DarkBench · Anthropomorphization · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
31% · Gemini 1.5 Pro · DarkBench · Brand bias · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
37% · Gemini 1.5 Pro · DarkBench · Harmful generation · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
94% · Gemini 1.5 Pro · DarkBench · Sneaking · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
7% · Gemini 1.5 Pro · DarkBench · Sycophancy · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
83% · Gemini 1.5 Pro · DarkBench · User retention · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
gemini-1.5-pro† · Overall difficulty-adjusted Brier index ↗
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.
- AndroidWorld: A Dynamic Benchmarking Environment for Autonomous Agents — published result table ↗
All 15 authors
Christopher Rawles, Sarah Clinckemaillie, Yifan Chang, Jonathan Waltz, Gabrielle Lau, Marybeth Fair, Alice Li, William Bishop, Wei Li, Folawiyo Campbell-Ajala, Daniel Toyama, Robert Berry, Divya Tyamagundlu, Timothy Lillicrap, Oriana Riva
- WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild — published result table ↗
All 9 authors
Lin, Bill Yuchen, Deng, Yuntian, Chandu, Khyathi, Brahman, Faeze, Ravichander, Abhilasha, Pyatkin, Valentina, Dziri, Nouha, Bras, Ronan Le, Choi, Yejin
- MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures — published result table ↗
All 8 authors
Jinjie Ni, Fuzhao Xue, Xiang Yue, Yuntian Deng, Mahir Shah, Kabir Jain, Graham Neubig, Yang You
- $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains — published result table ↗
- Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? — published result table ↗
All 19 authors
Lee, Jinhyuk, Chen, Anthony, Dai, Zhuyun, Dua, Dheeru, Sachan, Devendra Singh, Boratko, Michael, Luan, Yi, Arnold, Sébastien M. R., Perot, Vincent, Dalmia, Siddharth, Hu, Hexiang, Lin, Xudong, Pasupat, Panupong, Amini, Aida, Cole, Jeremy R., Riedel, Sebastian, Naim, Iftekhar, Chang, Ming-Wei, Guu, Kelvin
- AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents — published result table ↗
- WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries — published result table ↗
All 11 authors
Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander, Khyathi Chandu, Ronan Le Bras, Claire Cardie, Yuntian Deng, Yejin Choi
- The Llama 3 Herd of Models — published result table ↗
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
- Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models — published result table ↗
All 50 authors
Deitke, Matt, Clark, Christopher, Lee, Sangho, Tripathi, Rohun, Yang, Yue, Park, Jae Sung, Salehi, Mohammadreza, Muennighoff, Niklas, Lo, Kyle, Soldaini, Luca, Lu, Jiasen, Anderson, Taira, Bransom, Erin, Ehsani, Kiana, Ngo, Huong, Chen, YenSung, Patel, Ajay, Yatskar, Mark, Callison-Burch, Chris, Head, Andrew, Hendrix, Rose, Bastani, Favyen, VanderBilt, Eli, Lambert, Nathan, Chou, Yvonne, Chheda, Arnavi, Sparks, Jenna, Skjonsberg, Sam, Schmitz, Michael, Sarnat, Aaron, Bischoff, Byron, Walsh, Pete, Newell, Chris, Wolters, Piper, Gupta, Tanmay, Zeng, Kuo-Hao, Borchardt, Jon, Groeneveld, Dirk, Nam, Crystal, Lebrecht, Sophie, Wittlif, Caitlin, Schoenick, Carissa, Michel, Oscar, Krishna, Ranjay, Weihs, Luca, Smith, Noah A., Hajishirzi, Hannaneh, Girshick, Ross, Farhadi, Ali, Kembhavi, Aniruddha
- HELMET: How to Evaluate Long-Context Language Models Effectively and Thoroughly — published result table ↗
All 8 authors
Howard Yen, Tianyu Gao, Minmin Hou, Ke Ding, Daniel Fleischer, Peter Izsak, Moshe Wasserblat, Danqi Chen
- JudgeBench: A Benchmark for Evaluating LLM-based Judges — published result table ↗
All 8 authors
Sijun Tan, Siyuan Zhuang, Kyle Montgomery, William Y. Tang, Alejandro Cuadron, Chenguang Wang, Raluca Ada Popa, Ion Stoica
- HARP: A challenging human-annotated math reasoning benchmark — published result table ↗
- Thinking in Space: How Multimodal Large Language Models See, Remember, and Recall Spaces — published result table ↗
- The FACTS Grounding Leaderboard: Benchmarking LLMs' Ability to Ground Responses to Long-Form Input — published result table ↗
All 26 authors
Alon Jacovi, Andrew Wang, Chris Alberti, Connie Tao, Jon Lipovetz, Kate Olszewska, Lukas Haas, Michelle Liu, Nate Keating, Adam Bloniarz, Carl Saroufim, Corey Fry, Dror Marcus, Doron Kukliansky, Gaurav Singh Tomar, James Swirhun, Jinwei Xing, Lily Wang, Madhu Gurumurthy, Michael Aaron, Moran Ambar, Rachana Fellinger, Rui Wang, Zizhao Zhang, Sasha Goldshtein, Dipanjan Das
- MedAgentBench: A Realistic Virtual EHR Environment to Benchmark Medical LLM Agents — published result table ↗
All 7 authors
Jiang, Yixing, Black, Kameron C., Geng, Gloria, Park, Danny, Zou, James, Ng, Andrew Y., Chen, Jonathan H.
- MedXpertQA: Benchmarking Expert-Level Medical Reasoning and Understanding — published result table ↗
All 9 authors
Yuxin Zuo, Shang Qu, Yifei Li, Zhangren Chen, Xuekai Zhu, Ermo Hua, Kaiyan Zhang, Ning Ding, Bowen Zhou
- ZebraLogic: On the Scaling Limits of LLMs for Logical Reasoning — published result table ↗
All 7 authors
Bill Yuchen Lin, Ronan Le Bras, Kyle Richardson, Ashish Sabharwal, Radha Poovendran, Peter Clark, Yejin Choi
- DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data — published result table ↗
- Forecastbench — methodology and published results ↗
- Scale Labs — evaluation methodology and results ↗
- Scale Labs — evaluation methodology and results ↗
- AIR-Bench: Benchmarking Large Audio-Language Models via Generative Comprehension — published result table ↗
All 11 authors
Qian Yang, Jin Xu, Wenrui Liu, Yunfei Chu, Ziyue Jiang, Xiaohuan Zhou, Yichong Leng, Yuanjun Lv, Zhou Zhao, Chang Zhou, Jingren Zhou
- PhysBench: Benchmarking and Enhancing Vision-Language Models for Physical World Understanding — published result table ↗
- PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change — published result table ↗
- Simple Evals — model benchmark results ↗
Names used in source tables
Gemini 1.5 Pro · Gemini-1.5 Pro · Gemini-1.5-Pro · Gemini-1.5-pro · gemini-1.5-pro · gemini-1.5-pro†