Benchmark By Score Rank
Overall 1
AA Intelligence Index4.3.2 Artificial Analysis combines tests of knowledge, reasoning, coding and tool use into one score AA 16.1 #141 of 339
Knowledge 4
AA OmniscienceAccuracy Measures correct answers on the AA Omniscience factual knowledge test AA 39.1% #51 of 323+1 versions & slices Hallucination Rate Measures how often attempted answers are incorrect on the AA Omniscience factual knowledge test AA 90.9% #260 of 323
AA Omniscience Index Scores factual knowledge while penalizing incorrect answers to encourage admitting uncertainty AA -16.4 #112 of 323
IFBench (instructions) Checks whether the model follows precise formatting and content instructions AA 48.7% #122 of 248
Reasoning 4
ARC-AGI-1public evaluation Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 56.4% #53 of 64+1 versions & slices semi-private Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 41% #56 of 67
ARC-AGI-2public evaluation Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 5.1% #50 of 66+1 versions & slices semi-private Models infer transformations from examples and solve unseen grid puzzles; the evaluation split is explicit ARC 4.9% #52 of 69
Math 20
FrontierMath Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 14.1% #24 of 40
FrontierMath Tier4 Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 4.2% #16 of 33
FrontierMath Tier 4 (v2) Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 0% #54 of 55
FrontierMath Tiers 1–3 (v2) Models solve expert-written advanced mathematics problems on the named tier and edition Epoch 24.6% #61 of 70
MathArenaAIME 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 88.3% #15 of 30+15 versions & slices Apex Answer accuracy on the named mathematics competition under the recorded effort MathArena 0.5% #31 of 34BRUMO 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 90% #14 of 24CMIMC 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 58.1% #21 of 22Project Euler Answer accuracy on the named mathematics competition under the recorded effort MathArena 27% #11 of 11HMMT February 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 82.5% #13 of 30HMMT November 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 80% #12 of 14IMO 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 31.6% #2 of 4Kangaroo 2025 1-2 Answer accuracy on the named mathematics competition under the recorded effort MathArena 64.6% #14 of 17Kangaroo 2025 11-12 Answer accuracy on the named mathematics competition under the recorded effort MathArena 89.2% #13 of 17Kangaroo 2025 3-4 Answer accuracy on the named mathematics competition under the recorded effort MathArena 64.6% #12 of 17Kangaroo 2025 5-6 Answer accuracy on the named mathematics competition under the recorded effort MathArena 66.7% #13 of 17Kangaroo 2025 7-8 Answer accuracy on the named mathematics competition under the recorded effort MathArena 82.5% #14 of 16Kangaroo 2025 9-10 Answer accuracy on the named mathematics competition under the recorded effort MathArena 95.8% #9 of 16SMT 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 84.9% #14 of 24USAMO 2025 Answer accuracy on the named mathematics competition under the recorded effort MathArena 24.4% #2 of 3
Science 3
Humanity's Last Exam Very hard expert questions across many fields, written to stump today’s models AA 22.5% #113 of 339
CritPt (physics) Research-level physics problems that need many careful reasoning steps AA 2.6% #99 of 326
SciCode Writing code for real scientific computing problems (physics, biology, math) AA 46.3% #70 of 142
Coding 6
Terminal-Bench4.0 Agents use a terminal to complete executable coding, system administration and research tasks in the 4.0 suite 0% #77 of 134+1 versions & slices 2.1 Older, easier version of Terminal-Bench; Still widely reported AA 28.5% #99 of 156
WebDev Arena Human pairwise preferences in the stated webdev vote pool Arena 1,226 #94 of 97+2 versions & slices October 23, 2026 Human pairwise preferences in the stated webdev vote pool Arena 1,226 #95 of 98October 19, 2026 Human pairwise preferences in the stated webdev vote pool Arena 1,226 #94 of 97
Terminal-Bench Hard Agents solve difficult software, system-administration and data-processing tasks in a terminal AA 26.5% #68 of 242
Agents 5
AutomationBench-AA Agents orchestrate SaaS workflows through APIs; objectives receive credit only when the task has no guardrail violation AA 2.2% #98 of 135
AA-Briefcase1.1 · Elo Agents produce professional deliverables; blind pairwise comparisons produce the source Elo rating AA 302 #112 of 142
GDPval-AA (work tasks)2.1 Real work tasks from many professions (reports, spreadsheets, analyses), graded against expert work AA 455 #106 of 177
τ³-benchbanking · 1.0.1 τ-bench official · 3-banking-1.0.1: Customer-service agents converse with simulated users, retrieve domain knowledge and change state through tools Sierra 13.7% #19 of 21
τ³-BankingAA Agents retrieve banking knowledge and execute tools to resolve customer-support workflows AA 9.7% #92 of 134
Multimodal 2
MMMU-Pro (vision) College-level questions that require understanding images: charts, diagrams, photos AA 74.9% #53 of 128
Arena Vision Human pairwise preferences in the stated vision vote pool Arena 1,263 #36 of 88
Writing 17
Arena Textcreative writing · October 22, 2026 Human pairwise preferences in the stated text vote pool Arena 1,454 #22 of 197+16 versions & slices creative writing Human pairwise preferences in the stated text vote pool Arena 1,443 #34 of 195overall Human pairwise preferences in the stated text vote pool Arena 1,445 #57 of 196Chinese Human pairwise preferences in the stated text vote pool Arena 1,507 #32 of 198English Human pairwise preferences in the stated text vote pool Arena 1,458 #36 of 205French Human pairwise preferences in the stated text vote pool Arena 1,473 #30 of 164German Human pairwise preferences in the stated text vote pool Arena 1,487 #11 of 167instruction following Human pairwise preferences in the stated text vote pool Arena 1,437 #48 of 205Japanese Human pairwise preferences in the stated text vote pool Arena 1,461 #16 of 152Korean Human pairwise preferences in the stated text vote pool Arena 1,434 #22 of 156non-English Human pairwise preferences in the stated text vote pool Arena 1,452 #27 of 205Polish Human pairwise preferences in the stated text vote pool Arena 1,479 #12 of 142Russian Human pairwise preferences in the stated text vote pool Arena 1,461 #28 of 203Spanish Human pairwise preferences in the stated text vote pool Arena 1,474 #16 of 168overall · October 15, 2026 Human pairwise preferences in the stated text vote pool Arena 1,458 #31 of 188creative writing · October 15, 2026 Human pairwise preferences in the stated text vote pool Arena 1,454 #22 of 187overall · October 22, 2026 Human pairwise preferences in the stated text vote pool Arena 1,458 #31 of 198
Health & law 3
MLCR-AA Models synthesize long medical records; the headline credits concise answers judged both accurate and complete AA 12.2% #45 of 103
Vals MedCode Medical coding accuracy on patient encounters Vals 50.6% #14 of 78
Vals MedScribe Accuracy of clinical notes produced from consultation transcripts Vals 73.6% #63 of 80
Documents 3
AA-LCR (long context)1.1 Questions that need reading and connecting facts across very long documents (around 100K tokens) AA 69% #133 of 317
GDP.pdfAA all-pass Models reason over professional PDF documents; an attempt passes only when every atomic criterion passes 10.2% #61 of 135
Arena Document Human pairwise preferences in the stated document vote pool Arena 1,421 #28 of 33
Other 1
AA Speech to textRecorded audio word error rate Measures transcription errors as a share of reference words in the non-streaming test AA 2.9% #13 of 55
Legacy · saturated or no longer reported 13
AIME2025 · AA archived AA evaluates the 30 integer-answer problems from the 2025 AIME mathematics competition AA 87.7% #26 of 140
LiveCodeBenchAA archived AA evaluates solutions to newly collected competitive-programming problems AA 80.1% #16 of 153
GPQA Diamond Graduate-level biology, chemistry and physics questions that can’t be solved by a quick web search 84.4% #88 of 315+1 versions & slices Epoch Models answer graduate-level science multiple-choice questions Epoch 85.3% #57 of 134
OTIS Mock AIME 20242025 Models solve the stated OTIS mock AIME mathematics problems Epoch 84.2% #67 of 131
SWE-bench VerifiedEpoch Swe Bench Verified: Agents modify real repositories to resolve the stated Verified issues Epoch 57.6% #22 of 24
SWE-rebenchall · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 23.5% #1 of 2+5 versions & slices Go · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 0% #1 of 2Java · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 0% #1 of 2Python · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 23.5% #1 of 2Rust · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 0% #1 of 2TypeScript · July 1, 2025 to November 1, 2025 Repository issue resolution over the exact fresh pull-request window, under the source agent version Nebius 0% #1 of 2
τ²-benchAA Tests service agents that use tools while coordinating with a simulated user AA 54.1% #107 of 245
No benchmark matches
CheaperGrok 4.5high×3.5-13%$0.76Context: 1M → 500K
OpenKimi K3max×2.7+75%$2.00Sampling parameters are fixed+3
CheaperMuse Spark 1.1xhigh×3-42%$1.69Only n=1 · Meta / Chat Completions+1
CheaperGLM 5.2xhighOpen×2.7-37%$1.40 / $4.40No image input
GPT-5.6 Solxhigh×3.4+133%$1.18
Qwen3.5 397B A17BenabledOpen-28%-61%$0.60 / $3.60Context: 1M → 262K