Benchmark By Score Rank
Overall 1
AA Intelligence Index4.3.2 AA Intelligence Index 4.3.2: Artificial Analysis combines tests of knowledge, reasoning, coding and tool use into one score AA 46.4 #14 of 337
Knowledge 5
AA OmniscienceAccuracy AA Omniscience · Accuracy: Measures correct answers on the AA Omniscience factual knowledge test AA 47.5% #29 of 321+1 versions & slices Hallucination Rate AA Omniscience · Hallucination Rate: Measures how often attempted answers are incorrect on the AA Omniscience factual knowledge test AA 29.3% #31 of 321
AA Omniscience Index AA Omniscience Index: Scores factual knowledge while penalizing incorrect answers to encourage admitting uncertainty AA 32 #9 of 321
SimpleQA Verifiedv1 SimpleQA Verified v1: Accuracy on short factual questions with verified answers, answered without web access 56% #18 of 83
Mystery Game Puzzles Mystery Game Puzzles: Models choose the best move in puzzle positions from an undisclosed game Epoch 29% #25 of 64
Reasoning 6
ARC-AGI-1public evaluation ARC-AGI-1 · public-eval: Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 95.1% #23 of 61+1 versions & slices semi-private ARC-AGI-1 · semi-private: Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 89.5% #25 of 64
ARC-AGI-2public evaluation ARC-AGI-2 · public-eval: Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 60% #27 of 63+1 versions & slices semi-private ARC-AGI-2 · semi-private: Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 61.4% #23 of 66
ARC-AGI-3semi-private ARC-AGI-3 · semi-private: Measures interactive game solving through relative human action efficiency ARC 1.8% #9 of 18
Chess Puzzles Chess Puzzles: Models choose the best next move from a novel chess position Epoch 41% #28 of 68
Math 12
AA Analyst Agent AA Analyst Agent: Data-analyst tasks: the model explores data with tools and reports findings AA 52.5% #6 of 43
FrontierMath Erdos FrontierMath Erdos: Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 0% #6 of 13
FrontierMath Tier 4 (v2) FrontierMath Tier 4 (v2): Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 17.1% #42 of 54
FrontierMath Tiers 1–3 (v2) FrontierMath Tiers 1–3 (v2): Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 53% #44 of 69
MathArenaArXivMath · August 2026 MathArena · arxiv · 08/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 46.5% #7 of 12+7 versions & slices ArXivMath · June 2026 MathArena · arxiv · 06/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 70.1% #12 of 24ArXivMath · May 2026 MathArena · arxiv · 05/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 60.8% #11 of 19ArXivMath · September 2026 MathArena · arxiv · 09/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 45.3% #5 of 7BrokenArXiv · August 2026 MathArena · arxiv_false · 08/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 35.1% #8 of 12BrokenArXiv · June 2026 MathArena · arxiv_false · 06/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 52.8% #10 of 24BrokenArXiv · May 2026 MathArena · arxiv_false · 05/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 40% #9 of 18BrokenArXiv · September 2026 MathArena · arxiv_false · 09/2026: Answer accuracy on the named mathematics competition under the recorded effort MathArena 27.7% #5 of 7
Science 5
Humanity's Last Exam Humanity's Last Exam: Very hard expert questions across many fields, written to stump today’s models AA 43.1% #30 of 337
CritPt (physics) CritPt (physics): Research-level physics problems that need many careful reasoning steps AA 17.7% #36 of 324
Vals Science Index Vals Science Index: Scientific problem solving across the index’s component evaluations Vals 34.8% #12 of 18
SciCode SciCode: Writing code for real scientific computing problems (physics, biology, math) AA 57.4% #18 of 140
Terminal-Bench Science0.1 Terminal-Bench Science 0.1: Agents complete expert-authored research workflows across five scientific domains in a terminal AA 4.8% #20 of 33
Coding 6
Terminal-Bench4.0 Terminal-Bench 4.0 · source setting 2: Agents use a terminal to complete executable coding, system administration and research tasks in the 4.0 suite 25.8% #24 of 132
DeepSWE1.1 DeepSWE 1.1: Agents change repository code to resolve software engineering tasks under the stated DeepSWE edition 33.3% #30 of 44
FrontierCode1.1 FrontierCode 1.1: Agents implement changes in real repositories, graded against maintainer-defined requirements AA 33.8% #22 of 28
ITBench SRE ITBench SRE: IT incident tasks: diagnose and fix broken systems like a site-reliability engineer AA 42.1% #15 of 37
WebDev Arena WebDev Arena: Human pairwise preferences in the stated webdev vote pool Arena 1,637 #15 of 97+1 versions & slices full cohort WebDev Arena · snapshot 2026-10-19 · native board settings: Human pairwise preferences in the stated webdev vote pool Arena 1,637 #15 of 97
Agents 4
AutomationBench-AA AutomationBench-AA: Agents orchestrate SaaS workflows through APIs; objectives receive credit only when the task has no guardrail violation AA 65.6% #11 of 133
AA-Briefcase1.1 · Elo AA-Briefcase 1.1 · Elo: Agents produce professional deliverables; blind pairwise comparisons produce the source Elo rating AA 1,642 #7 of 140
GDPval-AA (work tasks)2.1 GDPval-AA (work tasks) 2.1: Real work tasks from many professions (reports, spreadsheets, analyses), graded against expert work AA 60.6 #8 of 175
Furniture Assembly Furniture Assembly: Models inspect furniture assembly photos, identify incorrect builds and locate the mistaken step Epoch 20.8% #29 of 31
Multimodal 3
MMMU-Pro (vision) MMMU-Pro (vision): College-level questions that require understanding images: charts, diagrams, photos AA 78.2% #33 of 127
Arena Vision Arena Vision · overall: Human pairwise preferences in the stated vision vote pool Arena 1,231 #54 of 88
Chartography Chartography: Expert chart reasoning over professional scientific, medical, financial and engineering charts Surge 14.7% #31 of 37
Writing 18
Arena Textcreative writing Arena Text · creative writing: Human pairwise preferences in the stated text vote pool Arena 1,424 #49 of 195+14 versions & slices overall Arena Text · overall: Human pairwise preferences in the stated text vote pool Arena 1,444 #58 of 196Chinese Arena Text · chinese: Human pairwise preferences in the stated text vote pool Arena 1,453 #77 of 181English Arena Text · english: Human pairwise preferences in the stated text vote pool Arena 1,412 #90 of 188French Arena Text · french: Human pairwise preferences in the stated text vote pool Arena 1,443 #67 of 149German Arena Text · german: Human pairwise preferences in the stated text vote pool Arena 1,353 #97 of 154instruction following Arena Text · instruction following: Human pairwise preferences in the stated text vote pool Arena 1,408 #74 of 188Japanese Arena Text · japanese: Human pairwise preferences in the stated text vote pool Arena 1,355 #68 of 138Korean Arena Text · korean: Human pairwise preferences in the stated text vote pool Arena 1,385 #52 of 144non-English Arena Text · non english: Human pairwise preferences in the stated text vote pool Arena 1,386 #89 of 188Polish Arena Text · polish: Human pairwise preferences in the stated text vote pool Arena 1,411 #63 of 133Russian Arena Text · russian: Human pairwise preferences in the stated text vote pool Arena 1,400 #81 of 186Spanish Arena Text · spanish: Human pairwise preferences in the stated text vote pool Arena 1,405 #80 of 155overall · full cohort Arena Text · overall · snapshot 2026-10-15 · native board settings: Human pairwise preferences in the stated text vote pool Arena 1,401 #90 of 188creative writing · full cohort Arena Text · creative writing · snapshot 2026-10-15 · native board settings: Human pairwise preferences in the stated text vote pool Arena 1,387 #71 of 187
EQ-Bench Longform Creative Writing1.11 Longform Creative Writing 1.11: Models plan, revise and write a story across eight turns, graded with a writing rubric EQ-Bench 83% #4 of 95
EQ-Bench Creative Writingv3 Creative Writing v3 · Elo: Judge-rated creative writing under the v3 prompt set and pairwise ranking EQ-Bench 2,007 #8 of 91
Lech Mazur Short-Story Lech Mazur Short-Story · comparison score: Judges compare stories written to ten required elements; the comparison score can be negative Lech 0.4 #20 of 44
Health & law 6
Harvey LAB-AA1.1 Harvey LAB-AA 1.1: Legal agents work from case documents; every rubric criterion must pass and material hallucinations receive no credit AA 9.4% #3 of 23
MLCR-AA MLCR-AA: Models synthesize long medical records; the headline credits concise answers judged both accurate and complete AA 15% #34 of 64
Vals LegalBench Vals LegalBench: Legal reasoning and legal-language understanding on LegalBench Vals 84.4% #29 of 89
Vals MedCode Vals MedCode: Medical coding accuracy on patient encounters Vals 49.6% #18 of 78
Vals MedScribe Vals MedScribe: Accuracy of clinical notes produced from consultation transcripts Vals 89.4% #7 of 80
Vals Legal Research Bench Vals Legal Research Bench: Grounded legal research; a task passes only if all criteria pass Vals 47.1% #11 of 69
Documents 2
AA-LCR (long context)1.1 AA-LCR (long context) 1.1: Questions that need reading and connecting facts across very long documents (around 100K tokens) AA 76.7% #80 of 275
GDP.pdfAA all-pass GDP.pdf · AA all-pass: Models reason over professional PDF documents; an attempt passes only when every atomic criterion passes 20% #25 of 133
Legacy · saturated or no longer reported 2
GPQA DiamondEpoch GPQA Diamond · source setting 2: Models answer graduate-level science multiple-choice questions Epoch 92.7% #17 of 133
OTIS Mock AIME 20242025 OTIS Mock AIME 2024 2025: Models solve the stated OTIS mock AIME mathematics problems Epoch 98.1% #23 of 130
No benchmark matches
CheaperClaude Opus 5.5xhigh+21%-7%$3.46No forced tool use+5
BetterGPT-6.1 Solhigh+8%-91%$0.32Remove unsupported parameters+5
OpenMiMo v2.6 Prothinkingsame-96%$0.13Pass back reasoning_content+3
Gemini 4 Argonhigh+13%-47%*$1.99Synchronous output stops at 65,536+2
DeepSeek V4.1 Flash 1017maxOpen-3%-93%$0.26Pass back reasoning_content · Chat Completions+4
GLM 5.3maxOpen-4%-46%$2.01No image input+4
Step 5 PreviewthinkingOpen-6%-73%$1.03No web search+3
Kimi K3maxOpen-6%-46%$2.00Sampling parameters are fixed+3