Claude 3 Opus · GPQA diamond · Best score (across scorers) · % ↗
Anthropic / MODEL EVIDENCE
Claude 3 Opus
41 benchmarks · 61 observations · 38 sources · released 2024-02-29
Scores at a glance
41 benchmarks · large dot: Claude 3 Opus; small dots: closest models where reported
Claude 3 Opus · MATH level 5 · Best score (across scorers) · % ↗
Claude 3 Opus · OTIS Mock AIME 2024-2025 · Best score (across scorers) · % ↗
Claude 3 Opus · SimpleQA Verified · Best score (across scorers) · % ↗
Claude 3 Opus · Chess Puzzles · Best score (across scorers) · % ↗
Claude 3 Opus · Cybench · Unguided % Solved · % ↗
Claude 3 Opus · MMLU · EM · % ↗
Claude 3 Opus · SimpleBench · Score (AVG@5) · % ↗
Claude 3 Opus · WeirdML · Accuracy · % ↗
Claude 3 Opus · Winogrande · Accuracy · % ↗
Claude 3 Opus · METR task performance & time horizons · Average task accuracy ↗
1 more reported result
3.95226 minutes · Claude 3 Opus · METR task performance & time horizons · 50% success task horizon · METR-Horizon-v1.1 · Epoch AI · METR Autonomy / Task-Horizon Suite · public result data ↗
Claude 3 Opus · LMCA · Score · % ↗
Claude 3 Opus · DTBench · Accuracy · % ↗
Claude 3 Opus · LiveBench · Global average · % ↗
Claude 3 Opus · EnigmaEval · Accuracy · % ↗
Claude 3 Opus · General ECI · 26 October 2026 fit ↗
Claude 3 Opus · Scale Labs · Score ↗
Claude 3 Opus · Scale Labs · Score ↗
Claude 3 Opus · MathOdyssey · Overall accuracy · original model comparison ↗
claude-3 / opus · AgentBench & ToolBench · AgentBench overall · Original standard test set ↗
Claude 3 Opus · BLINK · Test accuracy · 1,907 test items ↗
Claude 3 Opus · PlanBench · Blocksworld ↗
1 more reported result
0% · Claude 3 Opus · PlanBench · Mystery Blocksworld · PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change ↗
Claude-3-Opus · ComplexBench · DRFR · all constraints · RAL evaluation ↗
Claude 3 Opus · AgentHarm & AgentDojo · AgentDojo targeted attack success · agent comparison ↗
1 more reported result
66.61% · Claude 3 Opus · AgentHarm & AgentDojo · AgentDojo benign utility · agent comparison · AgentDojo: A Dynamic Environment to Evaluate Prompt Injection Attacks and Defenses for LLM Agents ↗
Claude-3 / Opus · BigCodeBench & BigCodeBench-Hard · BigCodeBench Complete · greedy accuracy ↗
1 more reported result
45.2% · Claude-3 / Opus · BigCodeBench & BigCodeBench-Hard · BigCodeBench Instruct · greedy accuracy · BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions ↗
Claude 3 Opus · SWE-bench (Original Full & Lite) · resolved rate · SWE-bench Full · BM25 retrieval ↗
1 more reported result
4.33% · Claude 3 Opus · SWE-bench (Original Full & Lite) · resolved rate · SWE-bench Lite · BM25 retrieval · SWE-bench: Can Language Models Resolve Real-World GitHub Issues? ↗
claude-3-opus · τ-Bench · Retail · pass^1 · Original tau-bench · function-calling agents ↗
2 more reported results
34.7% · claude-3-opus · τ-Bench · Airline · pass^1 · Original tau-bench · function-calling agents · $\tau$-bench: A Benchmark for Tool-Agent-User Interaction in Real-World Domains ↗
39.5% · claude-3-opus · 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 ↗
Claude 3 Opus · WildBench · WB-Score · reported comparison ↗
Claude-3 (Opus) · ChemBench · Overall accuracy · published model comparison ↗
1 more reported result
67% · Claude-3 (Opus) · ChemBench · Human-evaluation subset · accuracy · published model comparison · Are large language models superhuman chemists? ↗
Claude-3-Opus† · SysBench / RealGuardrails · instruction satisfaction rate · English-oriented models ↗
Claude 3 Opus · MixEval & MixEval-Hard · accuracy · original comparison ↗
1 more reported result
88.1% · Claude 3 Opus · MixEval & MixEval-Hard · accuracy · original comparison · MixEval: Deriving Wisdom of the Crowd from LLM Benchmark Mixtures ↗
Claude 3 Opus · WildHallucinations · WildFActScore · all entities · original evaluation ↗
Claude 3 Opus · SimpleQA · Correct answers · OpenAI Simple Evals · archived July 2025 ↗
Claude 3 Opus · HumanEval · Pass@1 · OpenAI Simple Evals · archived July 2025 ↗
Claude 3 Opus · DROP (Discrete Reasoning Over Paragraphs) · F1 · three-shot · OpenAI Simple Evals · archived July 2025 ↗
Claude 3 Opus · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · Text Retrieval · published average · 128k context test ↗
3 more reported results
47% · Claude 3 Opus · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · RAG · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
20% · Claude 3 Opus · LOFT (Long-Context Frontiers in Retrieval & Reasoning) · SQL · published average · 128k context test · Can Long-Context Language Models Subsume Retrieval, RAG, SQL, and More? ↗
74% · Claude 3 Opus · 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? ↗
Claude-3 Opus · CountBench & PixMo-Count · CountBenchQA · test accuracy · Molmo and PixMo · Table 1 comparison ↗
1 more reported result
43.3% · Claude-3 Opus · 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 ↗
Claude 3 Opus · RealWorldQA · accuracy · xAI · Grok-1.5 Vision release · April 12, 2024 ↗
1 more reported result
49.8% · Claude-3 Opus · RealWorldQA · accuracy · Molmo and PixMo · Table 1 comparison · Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Vision-Language Models ↗
Claude 3 Opus · Chatbot Arena · Chatbot Arena Vision · English Elo · 2024-11-13 · November 13, 2024 snapshot ↗
Claude 3 Opus · DarkBench · DarkScore · six-category mean · publisher website comparison ↗
6 more reported results
14% · Claude 3 Opus · DarkBench · Anthropomorphization · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
21% · Claude 3 Opus · DarkBench · Brand bias · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
15% · Claude 3 Opus · DarkBench · Harmful generation · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
66% · Claude 3 Opus · DarkBench · Sneaking · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
1% · Claude 3 Opus · DarkBench · Sycophancy · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
84% · Claude 3 Opus · DarkBench · User retention · publisher website comparison · DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data ↗
Claude 3 Opus · Michelangelo (Latent Structure Queries) · MRCR · cumulative mean through 128K · chart reading · Michelangelo original report · MRCR at 128K context ↗
Closest models by score
Similar positions on shared benchmark leaderboards. Smaller gaps are closer.
5 of 7 shared benchmark comparisons
5 of 7 shared benchmark comparisons
7 of 7 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
- SWE-bench: Can Language Models Resolve Real-World GitHub Issues? — published result table ↗
All 7 authors
Jimenez, Carlos E., Yang, John, Wettig, Alexander, Yao, Shunyu, Pei, Kexin, Press, Ofir, Narasimhan, Karthik
- 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 ↗
- BigCodeBench: Benchmarking Code Generation with Diverse Function Calls and Complex Instructions — published result table ↗
All 33 authors
Terry Yue Zhuo, Minh Chien Vu, Jenny Chim, Han Hu, Wenhao Yu, Ratnadira Widyasari, Imam Nur Bani Yusuf, Haolan Zhan, Junda He, Indraneil Paul, Simon Brunner, Chen Gong, Thong Hoang, Armel Randy Zebaze, Xiaoheng Hong, Wen-Ding Li, Jean Kaddour, Ming Xu, Zhihan Zhang, Prateek Yadav, Naman Jain, Alex Gu, Zhoujun Cheng, Jiawei Liu, Qian Liu, Zijian Wang, Binyuan Hui, Niklas Muennighoff, David Lo, Daniel Fried, Xiaoning Du, Harm de Vries, Leandro Von Werra
- MathOdyssey: Benchmarking Mathematical Problem-Solving Skills in Large Language Models Using Odyssey Math Data — published result table ↗
- Benchmarking Complex Instruction-Following with Multiple Constraints Composition — published result table ↗
All 14 authors
Bosi Wen, Pei Ke, Xiaotao Gu, Lindong Wu, Hao Huang, Jinfeng Zhou, Wenchuang Li, Binxin Hu, Wendy Gao, Jiaxin Xu, Yiming Liu, Jie Tang, Hongning Wang, Minlie Huang
- 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
- SysBench: Can Large Language Models Follow System Messages? — published result table ↗
All 12 authors
Yanzhao Qin, Tao Zhang, Tao Zhang, Yanjun Shen, Wenjing Luo, Haoze Sun, Yan Zhang, Yujing Qiao, Weipeng Chen, Zenan Zhou, Wentao Zhang, Bin Cui
- Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries — published result table ↗
All 24 authors
Vodrahalli, Kiran, Ontanon, Santiago, Tripuraneni, Nilesh, Xu, Kelvin, Jain, Sanil, Shivanna, Rakesh, Hui, Jeffrey, Dikkala, Nishanth, Kazemi, Mehran, Fatemi, Bahare, Anil, Rohan, Dyer, Ethan, Shakeri, Siamak, Vij, Roopali, Mehta, Harsh, Ramasesh, Vinay, Le, Quoc, Chi, Ed, Lu, Yifeng, Firat, Orhan, Lazaridou, Angeliki, Lespiau, Jean-Baptiste, Attaluri, Nithya, Olszewska, Kate
- 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
- Are large language models superhuman chemists? — published result table ↗
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
- The Claude 3 Model Family: Opus, Sonnet, Haiku ↗
- DTBench — Conceptual Reasoning Index ↗
- LMCA — Conceptual Reasoning Index ↗
- Holistic Evaluation of Language Models (HELM) ↗
- Cybench: A Framework for Evaluating Cybersecurity Capabilities and Risks of Language Models ↗
All 27 authors
Zhang, Andy K., Perry, Neil, Dulepet, Riya, Ji, Joey, Menders, Celeste, Lin, Justin W., Jones, Eliot, Hussein, Gashon, Liu, Samantha, Jasper, Donovan, Peetathawatchai, Pura, Glenn, Ari, Sivashankar, Vikram, Zamoshchin, Daniel, Glikbarg, Leo, Askaryar, Derek, Yang, Mike, Zhang, Teddy, Alluri, Rishi, Tran, Nathan, Sangpisit, Rinnara, Yiorkadjis, Polycarpos, Osele, Kenny, Raghupathi, Gautham, Boneh, Dan, Ho, Daniel E., Liang, Percy
- DarkBench: Benchmarking Dark Patterns in Large Language Models — publisher leaderboard data — published result table ↗
- Chess Puzzles ↗
- GPQA Diamond ↗
- MATH Level 5 ↗
- OTIS Mock AIME 2024-2025 ↗
- SimpleQA Verified ↗
- SimpleBench ↗
- AI benchmarks & capabilities ↗
- WeirdML ↗
- EnigmaEval ↗
- Scale Labs — evaluation methodology and results ↗
- Scale Labs — evaluation methodology and results ↗
- LiveBench — model evaluation leaderboard ↗
- Measuring AI Ability to Complete Long Software Tasks ↗
- PlanBench: An Extensible Benchmark for Evaluating Large Language Models on Planning and Reasoning about Change — published result table ↗
- Simple Evals — model benchmark results ↗
- BLINK: Multimodal Large Language Models Can See but Not Perceive — published result table ↗
All 10 authors
Xingyu Fu, Yushi Hu, Bangzheng Li, Yu Feng, Haoyu Wang, Xudong Lin, Dan Roth, Noah A. Smith, Wei-Chiu Ma, Ranjay Krishna
- Grok-1.5 Vision Preview ↗
Names used in source tables
Claude 3 Opus · Claude-3 (Opus) · Claude-3 / Opus · Claude-3 Opus · Claude-3-Opus · Claude-3-Opus† · claude-3 / opus · claude-3-opus