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.

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Sources

Every plotted observation links to its evaluation. Reported configurations, benchmark versions and task subsets can differ; similarity describes shared scores, not training lift.

Aider refactoring benchmark ↗
Paul Gauthier, Aider contributors
WildBench: Benchmarking LLMs with Challenging Tasks from Real Users in the Wild — published result table ↗
Lin, Bill Yuchen, Deng, Yuntian, Chandu, Khyathi, Brahman, Faeze, Ravichander, Abhilasha, Pyatkin, Valentina et al. · 2024
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 ↗
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
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
One Thousand and One Pairs: A "novel" challenge for long-context language models — published result table ↗
Marzena Karpinska, Katherine Thai, Kyle Lo, Tanya Goyal, Mohit Iyyer · 2024
WildHallucinations: Evaluating Long-form Factuality in LLMs with Real-World Entity Queries — published result table ↗
Wenting Zhao, Tanya Goyal, Yu Ying Chiu, Liwei Jiang, Benjamin Newman, Abhilasha Ravichander et al. · 2024
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
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
DTBench — Conceptual Reasoning Index ↗
Conceptual Reasoning Index
LMCA — Conceptual Reasoning Index ↗
Conceptual Reasoning Index
Holistic Evaluation of Language Models (HELM) ↗
Stanford Center for Research on Foundation Models
SimpleBench ↗
Epoch AI
AI benchmarks & capabilities ↗
Epoch AI
Is Your Code Generated by ChatGPT Really Correct? Rigorous Evaluation of Large Language Models for Code Generation — published result table ↗
Liu, Jiawei, Xia, Chunqiu Steven, Wang, Yuyao, Zhang, Lingming · 2023
LiveBench — model evaluation leaderboard ↗
LiveBench Team
GPQA Diamond — evaluation methodology and results ↗
Vals AI · 2026
LiveCodeBench — evaluation methodology and results ↗
Vals AI · 2026
LegalBench — evaluation methodology and results ↗
Vals AI · 2026
MedQA — evaluation methodology and results ↗
Vals AI · 2026
MMLU Pro — evaluation methodology and results ↗
Vals AI · 2026

Names used in source tables

Command R+ · Command-R+ · Command-R-Plus · command-r-plus