Math
We track 130 benchmarks in math. They run from everyday level to research frontier level.
OpenAI held the top math score 55% of the contested time
That's about 25 of the 46 months since January 2023, averaged over these benchmarks. We only count time while other labs are still testing, and stop once a model passes 85%. Faded stretches no longer count.
Sources: Official leaderboards, Epoch AI runs (CC BY 4.0) and labs’ model cards
Each benchmark counts from the one source its own page leads with: its official leaderboard when that is current, else Epoch AI’s own runs, else labs’ own numbers. We date independent runs by the model’s release and lab reports by when they came out.
Sources: Official leaderboards, Epoch AI runs (CC BY 4.0) and boards copied by Epoch AI (CC BY 4.0)
Every independent run: each benchmark’s own leaderboard, Epoch AI’s runs and boards Epoch AI copied, dated by the model’s release. We leave out benchmarks that only labs report.
Sources: Official leaderboards, Epoch AI runs (CC BY 4.0), boards copied by Epoch AI (CC BY 4.0), labs’ model cards and claims collected by Epoch AI (CC BY 4.0)
Every score, including labs’ own numbers and claims Epoch AI collected from reports and papers. Labs pick their own settings, so a claim can beat an independent run of the same model.
From everyday to research frontier level
Grouped by who could solve the tasks, from things most adults can do to open research problems. The bar under each name is its best score.
School
Students, from grade school to high school
University
Undergraduates and entry-level professionals
Competition
The strongest students, in olympiad-style contests
- AIME 2025
- OTIS Mock AIME 2024-2025
- MATH
- AIME 2024
- MATH-500
- HMMT 2025
- AIME 2026
- MATH Level 5
- PolyMath
- IMO-AnswerBench
- HMMT Nov 2025
- MathArena (Apex, IMO, USAMO)
- HMMT 2026
- MathArena Apex Shortlist
- BRUMO 2025
- SMT 2025
- IneqMath proofs
- CMIMC 2025
- AMO-Bench
- IMO-ProofBench proofs
- Beyond AIME
- IMO 2025 proofs
- PutnamBench proofs
- CNMO 2024
- HiddenMath
- USAMO 2026 proofs
- Omni-MATH
- USAMO 2025 proofs
- OlympiadBench
- miniF2F proofs
- CombiBench proofs
- Putnam 2025 proofs
- AMC
- CMO 2025 proofs
- LiveMathBench
- HRM8K-KSM
- Ko-AIME 2025 (Upstage)
- OMEGA
- AMC 10 2023
- AMC 12 2023
- AMC 8 2023
- QuantBench
- AIME 1983-2024
- Functional MATH
- HiddenMath-Hard
- Past IMO (Seed-Prover formal set) proofs
- Putnam 2024 proofs
- AMC 10 2022
- AMC 10/12 (November 2024)
- AMC 12 2022
- AMC 12 2024
- CMO 2024 proofs
- FormalMATH proofs
- FormalMATH Lite proofs
- IMO 2026 proofs
- IMO Shortlist 2024 proofs
- IMO-LeanProofBench proofs
- Ko-AIME 2024 (Upstage)
- AIME 2023
- BrokenMath proofs
- CNML-Level Problems (DeepSeek) proofs
- HMMT February 2024
- IMO-GradingBench
- LiveMath
- ProcessBench
- ProofRank proofs
- USAMO 2024 proofs
Expert
Specialists with years of training, often over hours of work
Research frontier
Researchers, on open problems or tasks that take days
- FrontierMath Tier 4 v2
- FrontierMath Tier 4
- Riemann-bench
- Leipzig Benchmark
- LiveMathematicianBench
- ArXivMath
- FrontierMath Erdős proofs
- HorizonMath
- IMProofBench proofs
- ArXivLean proofs
- BrokenArXiv proofs
- FLTEval
- FATE-X proofs
- First Proof Third Batch proofs
- Fermat's Last Theorem in Lean (Anthropic)
- Miklós Schweitzer 2025 proofs
- First Proof proofs
- First Proof Second Batch proofs
- FrontierMath: Open Problems
- OpenFrontiers-Bench proofs
- Soohak
- TCS-Bench proofs
By kind
Word problems
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| GSM8K 8.5K grade-school math word problems. Final numeric answer scored by exact match. | School | Checked automatically | | Fading |
| U-MATH Models solve 1,100 unpublished open-ended university math problems from teaching materials, balanced across six subjects. About 20% include images, and an LLM judge checks each solution. | University | Graded by a model | 86.8% | Not in cards |
| SnorkelSequences Models compute values over integer sequences built from chains of filters, transforms and operators. The 250 procedurally generated questions test compositional multi-step math. | School | Checked automatically | 77.6% | Not in cards |
| SnorkelGraph Models solve 200 procedurally generated graph problems, such as minimum vertex cover, given as node and edge lists in text. Answers are checked against verifiable ground truth. | University | Checked automatically | 84.5% | Not in cards |
| MathBench Models answer 3,709 math questions in five stages from basic arithmetic to college, in Chinese and English. Each stage also tests theory knowledge, and Circular Evaluation reshuffles answer options to check consistency. | University | Checked automatically | 70.9% | Not in cards |
| GSM8K Platinum Initial 268 Models answer the original 268-question cleaned GSM8K subset. The live matrix reports each model configuration separately. | School | Checked automatically | 99.6% | Not in cards |
| GSM1k Models solve new grade school math word problems written to mirror GSM8K in style and difficulty. The gap between GSM8K and GSM1k accuracy shows overfitting or contamination. | School | Checked automatically | 96.6% | Not in cards |
| CMATH 1.7K Chinese elementary-school math word problems. Final-answer accuracy. | School | Checked automatically | | Fading |
| GSM8K-Platinum Models solve the GSM8K test problems after MIT researchers fixed wrong labels and removed badly written questions. Errors on it are more likely real model mistakes. | School | Checked automatically | 99.8% | System cards only |
| UGMathBench Models solve 5,062 undergraduate math problems across 16 subjects. Each problem has three randomized versions, and effective accuracy counts problems solved in all versions. | University | Checked automatically | 81.9% | System cards only |
| DeepMind Mathematics Models answer generated school-level math questions across algebra, arithmetic, calculus, probability and other modules. Answers are checked for an exact match. | School | Checked automatically | 81.9% | Fading |
| GRE Quantitative Models take the GRE quantitative reasoning section. Scored on the 130 to 170 scale. | University | Checked automatically | 163.0 | System cards only |
| GSM-Symbolic Models solve grade-school word problems generated from symbolic templates of GSM8K questions, with names and numbers changed. P1 and P2 add one or two extra clauses. | School | Checked automatically | 87.4% | Fading |
| HRM8K Models solve 8,011 math problems given as English and Korean parallel pairs. It measures how much math reasoning drops when problems are in Korean. | School | Checked automatically | | Fading |
| Hungarian National High-School Exam Models answer the 33 questions of the 2023 Hungarian national high school mathematics finals. Answers are graded by hand with the official rubric. | School | Graded by people | 59% | Dropped |
| SuperCLUE-Math6 Models solve thousands of multi-step Chinese math word problems. Scores combine reasoning-step quality and accuracy into a comprehensive score and a reasoning level. | School | Graded by a model | | System cards only |
| GMAT Quantitative Models answer the quantitative section of the official GMAT online exam. Scored as accuracy. | University | Checked automatically | | System cards only |
| GSM-Plus Models solve GSM8K problems after perturbations such as changed numbers, added distractors and reversed questions. | School | Checked automatically | 64.8% | Dropped |
| Math23K Models solve Chinese elementary-school math word problems from a set of about 23,000. Scored by final-answer accuracy. | School | Checked automatically | 88.5% | System cards only |
| Math401 Models compute 401 arithmetic expressions covering addition, multiplication, exponents, logarithms and trigonometry. Scored by exact numeric accuracy. | Everyday | Checked automatically | | System cards only |
| MathQA Models answer multiple-choice math word problems drawn from AQuA. Each problem is annotated with an operation program. Scored by accuracy. | School | Checked automatically | | System cards only |
| SAT Math Models take the SAT math section. Scored on the 200 to 800 scale. | School | Checked automatically | 700.0 | System cards only |
| MAWPS Models solve one-unknown arithmetic and algebra word problems drawn from several earlier collections. Each problem has an equation and a numeric answer, and the final answer is scored by exact match. | School | Checked automatically | Not in cards | |
| SVAMP Models solve 1,000 grade-school arithmetic word problems. The problems are variations of problems from earlier datasets, made to catch solvers that ignore the question or the word order. The final numeric answer is scored by exact match. | School | Checked automatically | Not in cards |
Competition problems with answers
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| AIME 2025 Models answer the 30 problems from the 2025 AIME I and II exams. Each answer is an integer from 0 to 999, scored by match. | Competition | Checked automatically | 100% | In use |
| OTIS Mock AIME 2024-2025 Models solve 45 problems from three OTIS Mock AIME exams written by students of the OTIS program. Integer answers are scored by exact match. | Competition | Checked automatically | 100% | Not in cards |
| MATH 12,500 competition math problems with step-by-step solutions. Final answer scored by exact match. | Competition | Checked automatically | | Fading |
| AIME 2024 Models solve the 30 problems of the 2024 AIME I and II. Answers are integers from 0 to 999, scored by exact match. | Competition | Checked automatically | 96.6% | Fading |
| MATH-500 Models solve 500 competition math problems drawn from the MATH test set. Final answers are checked against the reference answers. | Competition | Checked automatically | | Fading |
| HMMT 2025 Models answer the 30 problems from the February 2025 Harvard-MIT Mathematics Tournament. Final answers are checked against the official answers. | Competition | Checked automatically | 100% | Fading |
| AIME 2026 Models solve the 30 integer-answer problems from the 2026 AIME I and II math competitions. Scored by exact answer match. | Competition | Checked automatically | 100% | In use |
| MATH Level 5 Models solve the 1,324 hardest MATH test problems, drawn from competitions such as AMC and AIME. Scored by final answer match. | Competition | Checked automatically | 98.1% | Dropped |
| PolyMath Models solve 9,000 parallel math problems in 18 languages across four difficulty levels, from school math to frontier math. Final answers are checked. | Competition | Checked automatically | | In use |
| IMO-AnswerBench 400 olympiad problems with short verifiable answers, robustified against memorization. Scored by answer match. | Competition | Checked automatically | 91% | In use |
| HMMT Nov 2025 Models solve the 30 problems of the November 2025 Harvard-MIT Mathematics Tournament. Final answers are checked automatically against the answer key. | Competition | Checked automatically | 99.2% | Fading |
| MathArena (Apex, IMO, USAMO) Evaluates models on newly released math competitions after release. Final-answer or human/LLM-judged proof scores. | Competition | Checked automatically | 81.3% | In use |
| HMMT 2026 Models solve the 33 final-answer problems from the February 2026 Harvard-MIT Mathematics Tournament. Scored by exact answer match. | Competition | Checked automatically | 98.5% | In use |
| MathArena Apex Shortlist Models solve 47 hard final-answer problems that MathArena selected from 2025 competitions, where the best models scored about 50% at selection. Scored by accuracy over repeated attempts. | Competition | Checked automatically | 98.4% | In use |
| BRUMO 2025 Models answer the 30 final-answer problems of the 2025 Brown University Math Olympiad. MathArena scores the average accuracy over four attempts. | Competition | Checked automatically | | Not in cards |
| SMT 2025 Models answer 53 final-answer problems from the 2025 Stanford Math Tournament. MathArena scores the average accuracy over four attempts. | Competition | Checked automatically | | Not in cards |
| CMIMC 2025 Models answer 40 final-answer problems from the 2025 Carnegie Mellon Informatics and Mathematics Competition. MathArena scores the average accuracy over four attempts. | Competition | Checked automatically | | Not in cards |
| AMO-Bench Models solve 50 original math problems at or above IMO difficulty that need only a final answer. Answers are graded automatically for accuracy. | Competition | Checked automatically | 52.4% | Fading |
| Beyond AIME Models answer 100 original competition-style math problems at or above the hardest AIME level. Each answer is a positive integer checked by exact match. | Competition | Checked automatically | | Fading |
| CNMO 2024 Models answer problems from the 2024 Chinese National High School Mathematics Olympiad. DeepSeek reports Pass@1 averaged over 16 samples. | Competition | Checked automatically | | Dropped |
| HiddenMath Models solve 179 competition-level math problems that experts wrote from scratch. Answers are graded automatically. | Competition | Checked automatically | | Dropped |
| Omni-MATH Models solve 4,428 Olympiad-level competition math problems across 33 subdomains and 10 difficulty levels. A GPT-4 or Omni-Judge grader checks answers. | Competition | Checked automatically | 60.5% | Dropped |
| OlympiadBench Models solve bilingual olympiad-level math and physics problems in Chinese and English, many with images. Answers are checked against a key. | Competition | Checked automatically | 18% | Dropped |
| AMC Models solve problems from the AMC 8, 10, and 12 competitions. Gemini 1.5 used 250 problems from 2022 and 2023, scored by accuracy. | Competition | Checked automatically | | Fading |
| LiveMathBench Models solve recent competition math problems, sampled many times. The G-Pass@k metric rewards both peak accuracy and stable answers across samples. | Competition | Checked automatically | | Not in cards |
| HRM8K-KSM Models solve the 1,428 problems of the Korean School Math subset of HRM8K. Problems come from Korean olympiad and competition exams. | Competition | Checked automatically | | Fading |
| Ko-AIME 2025 (Upstage) Models solve AIME 2025 competition problems in Korean. Upstage built the set in house. | Competition | Checked automatically | | Fading |
| OMEGA Models solve generated competition-style math problems that test exploratory, compositional and transformative generalization beyond training patterns. Answers are checked automatically. | Competition | Checked automatically | | Fading |
| Project Euler (MathArena) Models solve recent Project Euler problems that need both mathematical insight and code. MathArena adds problems as Project Euler releases them, starting from problem 943. | Expert | Checked automatically | | Not in cards |
| AMC 10 2023 Models take the 2023 AMC 10 A and B exams. Scored out of 150 points. | Competition | Checked automatically | 72.0 | System cards only |
| AMC 12 2023 Models take the 2023 AMC 12 A and B exams. Scored out of 150 points. | Competition | Checked automatically | 63.0 | System cards only |
| AMC 8 2023 Models take the 25 question 2023 AMC 8 exam. Scored out of 150 points. | Competition | Checked automatically | 84.0 | System cards only |
| QuantBench Models answer 25 multiple choice versions of quant trading firm reasoning puzzles. Scored as cons@16 accuracy. | Competition | Checked automatically | 60% | System cards only |
| AIME 1983-2024 Models solve 949 past AIME problems from 1983 to 2024. Integer answers are checked exactly. | Competition | Checked automatically | | System cards only |
| CSAT Math 2025 Models solve the mathematics sections of South Korea's 2025 College Scholastic Ability Test in Korean. The score averages the three elective subjects: calculus, statistics and geometry. | School | Checked automatically | | Dropped |
| Functional MATH Models solve new instances of MATH problems that code generates for each snapshot. The gap from static MATH accuracy measures memorization. | Competition | Checked automatically | | Dropped |
| Gaokao Math 2026 Models sit the five 2026 Chinese Gaokao mathematics papers (National I, National II, Beijing, Shanghai and Tianjin). Each paper is graded out of 150 points. | School | Checked automatically | | In use |
| HiddenMath-Hard Models solve the harder part of an expert-written, never-published set of AIME and AMC style competition problems. | Competition | Checked automatically | | System cards only |
| Hy-Math Models solve Tencent in-house math problems without tools. Task and scoring details are not published. | Expert | Checked automatically | | In use |
| AMC 10 2022 Models take a 2022 AMC 10 exam. Scored out of 150 points. | Competition | Checked automatically | 30.0 | System cards only |
| AMC 10/12 (November 2024) Models take the four November 2024 AMC 10 and 12 contests, 78 questions in all. Scored in contest points out of 150, averaged over tests. | Competition | Checked automatically | | System cards only |
| AMC 12 2022 Models take a 2022 AMC 12 exam. Scored out of 150 points. | Competition | Checked automatically | 60.0 | System cards only |
| AMC 12 2024 Models answer the 25 multiple-choice problems of the 2024 AMC 12 contests. Scored on the official 150-point scale. | Competition | Checked automatically | | System cards only |
| Ko-AIME 2024 (Upstage) Models solve AIME 2024 competition problems translated into Korean. Upstage built the set in house. | Competition | Checked automatically | | System cards only |
| AIME 2023 Models solve the 30 problems of the 2023 AIME I and II. Answers are integers from 0 to 999, scored by exact match. | Competition | Checked automatically | Not in cards | |
| HMMT February 2024 Models answer the problems from the February 2024 Harvard-MIT Mathematics Tournament. Final answers are checked against the official answers. | Competition | Checked automatically | Not in cards | |
| LiveMath Models solve 250 math problems written with six professional mathematicians. The sets are 150 regular high school problems, 50 at about AIME level and 50 multimodal problems with figures. | Competition | Checked automatically | Not in cards | |
| ProcessBench Models read step-by-step solutions to GSM8K, MATH, OlympiadBench and Omni-MATH problems and name the earliest wrong step, or say none is wrong. Scored by F1. | Competition | Checked automatically | Not in cards |
Written proofs
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| IneqMath Models solve Olympiad-level inequality problems, recast as two checkable tasks: estimating a tight bound and predicting the relation between two expressions. IMO-level medalists wrote and reviewed the 200 test problems. Five model judges check the final answer and look for toy-case reasoning, logical gaps and numerical shortcuts, and a solution counts only if it passes all five. | Competition | Graded by a model | 47% | Not in cards |
| IMO-ProofBench Models write proofs for 60 olympiad problems, split into a basic set and an advanced set up to IMO-hard. Each proof is graded from 0 to 7 by experts or a Gemini autograder. | Competition | Graded by people | 88.1% | Fading |
| IMO 2025 Models write full proofs for the six problems of the 2025 International Mathematical Olympiad. Graders score proofs out of 42 points, mapped to medal cutoffs. | Competition | Graded by people | | Fading |
| USAMO 2026 Models write full proofs for the six problems of the 2026 USA Mathematical Olympiad. Judges grade each proof from 0 to 7 against rubrics. | Competition | Graded by people | 98.2% | In use |
| USAMO 2025 Models write full proofs for the 6 problems of the 2025 USA Mathematical Olympiad. Expert human graders score each proof. | Competition | Graded by people | | Dropped |
| Putnam 2025 Models solve the 12 problems of the 2025 William Lowell Putnam competition with full proofs. Scored out of 120 points. | Competition | Graded by people | | Fading |
| Putnam-like Models write proofs for 96 university problems in 8 sets of 12, in the style of the easier and middle Putnam tiers. Each problem has a Lean statement and a point rubric for grading. | University | Graded by a model | | Not in cards |
| CMO 2025 Models write full proofs for the six problems of the 2025 China Mathematical Olympiad. Graders score proofs out of 126 points. | Competition | Graded by people | | Fading |
| AdvancedMathBench Models write proofs for 245 advanced problems at undergraduate and doctoral qualifying exam levels. A verifier trained on expert annotations grades each proof. | Expert | Graded by a model | | In use |
| Putnam 2024 Models write full proofs for the 12 problems of the December 2024 William Lowell Putnam competition. Proofs are graded out of 120 points. | Competition | Graded by people | | Dropped |
| CMO 2024 Models write full proofs for the six problems of the 2024 China Mathematical Olympiad. Experts grade the proofs for points. | Competition | Graded by people | | System cards only |
| IMC 2025 Models write proofs for the 10 problems of the 2025 International Mathematics Competition for University Students. Human judges grade each proof. | University | Graded by people | | Not in cards |
| IMO 2026 Models write full proofs for the six problems of the 2026 International Mathematical Olympiad. Proofs are scored out of 42 points. | Competition | Graded by people | 100% | System cards only |
| IMO Shortlist 2024 Models write proofs for the 31 problems of the 2024 IMO Shortlist. DeepSeek scores the proofs with its own verifier model. | Competition | Graded by a model | | System cards only |
| Miklós Schweitzer 2025 Models write proofs for the 2025 Miklós Schweitzer competition, a hard Hungarian university-level contest. MathArena runs and grades it. | Research frontier | Graded by people | 90% | Not in cards |
| BrokenMath Models are asked to prove false versions of 2025 competition problems. An LLM judge counts how often a model writes a proof instead of rejecting the statement. | Competition | Graded by a model | Not in cards | |
| CNML-Level Problems (DeepSeek) Models prove 91 theorems in algebra, geometry, number theory, combinatorics and inequalities at Chinese National High School Mathematics League level. A verifier model scores the proofs. | Competition | Graded by a model | System cards only | |
| IMO-GradingBench Models grade 1,000 olympiad proof attempts, and their grades are compared with human expert grades. Tests automatic evaluation of long-form math answers. | Competition | Checked automatically | Not in cards | |
| ProofRank Models write proofs for hard competition problems. An LLM judge compares correct proofs pairwise on conciseness, computational ease, simplicity, diversity and adaptivity, giving Elo ratings. | Competition | Graded by a model | Not in cards | |
| USAMO 2024 Models write full proofs for problems from the 2024 USA Mathematical Olympiad, graded by human experts. | Competition | Graded by people | Not in cards |
Formal proofs
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| ProofBench Models write Lean 4 proofs of graduate-level theorems, with Mathlib search and code tools for up to 40 turns. Scored by the share that compile. | Expert | Checked automatically | 78% | Not in cards |
| ProofBench v1.1 Models write Lean 4 proofs of graduate-level theorems from paired natural-language and formal statements. Scored by the share the Lean checker accepts. | Expert | Checked automatically | 100% | Not in cards |
| PutnamBench Models write formal Lean proofs of Putnam competition problems. A proof counts only when the verifier accepts it. | Competition | Checked automatically | | Fading |
| miniF2F Models write formal proofs of olympiad and high school competition statements, such as AMC, AIME and IMO problems. A proof assistant checks each proof, and scores are pass@k on the 244 test problems. | Competition | Checked automatically | | Fading |
| ArXivLean Models prove or disprove theorems from recent arXiv papers, stated in Lean 4. A strict comparator checks each submitted proof against the fixed reference statement. | Research frontier | Checked automatically | 47.2% | System cards only |
| CombiBench Provers solve 100 combinatorics problems formalized in Lean 4, from middle school to IMO and university level. Lean checks each proof. | Competition | Checked automatically | | Fading |
| FLTEval Agents complete the formal Lean proofs and define the new mathematical concepts in real pull requests to the Fermat's Last Theorem (FLT) formalization project. Lean and SafeVerify check each submitted diff. | Research frontier | Checked automatically | | Fading |
| miniCTX-v2 Provers prove Lean theorems from real projects using long repository context, with theorems taken after a November 28, 2024 cutoff. | Expert | Checked automatically | | Dropped |
| FATE-H Provers write Lean proofs for 100 abstract and commutative algebra problems at honors course or graduate exam level. The Lean compiler checks each proof. | Expert | Checked automatically | | Fading |
| FATE-X Provers write Lean proofs for 100 algebra problems at or beyond PhD qualifying exam level, some beyond what Mathlib covers. The Lean compiler checks each proof. | Research frontier | Checked automatically | | Fading |
| Past IMO (Seed-Prover formal set) Provers write Lean proofs for 155 past IMO problems, mostly adapted from Compfiles and MiniF2F. | Competition | Checked automatically | | Dropped |
| ProverBench (DeepSeek) Provers write Lean 4 proofs for 325 formalized problems: 15 from AIME 2024 and 2025 and 310 from textbooks across number theory, algebra, calculus and analysis. Lean checks each proof. | University | Checked automatically | | Dropped |
| Fermat's Last Theorem in Lean (Anthropic) Agent teams formalize Fermat's Last Theorem in Lean. Scores measure the weighted proportion of 60 accepted intermediate theorems. | Research frontier | Checked automatically | 35% | System cards only |
| FormalMATH Provers write Lean 4 proofs for 5,560 formal statements from high-school olympiad problems to undergraduate theorems. The Lean checker scores each proof. | Competition | Checked automatically | | System cards only |
| FormalMATH Lite Models prove statements in the FormalMATH Lite subset. The board reports proof success at the stated sampling budget. | Competition | Checked automatically | | Not in cards |
| IMO-LeanProofBench Models write Lean 4 proofs for the 60 IMO-ProofBench problems, formalized by hand and checked by Lean experts. The Lean compiler verifies each proof. | Competition | Checked automatically | | Not in cards |
| ProofNet Provers write formal proofs for 371 undergraduate theorems from analysis, algebra and topology textbooks, each with a formal statement and a natural-language proof. The proof checker grades them. | University | Checked automatically | | System cards only |
| LeanDojo Benchmark Models prove theorems from Lean's mathlib library inside the Lean proof assistant, which checks every proof. The benchmark has 98,734 theorems and proofs with premise annotations. A novel-premises split tests whether a prover can use lemmas it never saw in training. | University | Checked automatically | Not in cards | |
| OpenFrontiers-Bench Agents try to rediscover proofs of research math problems, most resolved during 2026, stated in Lean 4. Two independent checkers grade the formal proofs, with closed-book, frozen-retrieval and live-web settings. | Research frontier | Checked automatically | Not in cards |
Research mathematics
| Benchmark | Level | Scored | Best score | Status |
|---|---|---|---|---|
| FrontierMath Tiers 1-3 v2 Models solve 295 unpublished math problems from undergraduate to advanced graduate level and submit answers that code checks automatically. Scored by share correct. | Expert | Checked automatically | 95.1% | In use |
| FrontierMath Unpublished research-level math problems with automatically verifiable answers. Tier 4 is the hardest tier. | Expert | Checked automatically | 50% | Fading |
| FrontierMath Tier 4 v2 Models solve 43 unpublished research-level math problems and submit answers that code checks automatically. Scored by share correct. | Research frontier | Checked automatically | 100% | In use |
| FrontierMath Tier 4 Models solve research-level math problems that take experts days, submitting answers through a Python function. Each answer is verified automatically as correct or incorrect. | Research frontier | Checked automatically | | Fading |
| Riemann-bench 25 private research-mathematics problems from professors and IMO medalists. Agents with tools, 100 runs per problem. | Research frontier | Checked automatically | 83.2% | In use |
| Leipzig Benchmark Models answer 100 research-level math questions with known answers, written by 49 mathematicians at a Max Planck Institute workshop in April and May 2026. | Research frontier | Checked automatically | 91% | Not in cards |
| LiveMathematicianBench Models answer multiple choice questions about theorems from arXiv papers published after their training cutoff. Wrong options follow plausible but invalid proof sketches. | Research frontier | Checked automatically | | System cards only |
| ArXivMath Final-answer research-level math problems extracted monthly from recent arXiv papers and filtered to be self-contained. | Research frontier | Checked automatically | 92.8% | In use |
| FrontierMath Erdős Models try to prove or disprove 68 open Erdős problems in Lean 4. A result counts only if the Lean checker accepts the full proof. | Research frontier | Checked automatically | 4.41% | Not in cards |
| HorizonMath Models attack 113 mostly unsolved problems in eight areas of mathematics and the mathematical sciences. A program checks each proposed closed form, construction or bound. | Research frontier | Checked automatically | 11.5% | In use |
| IMProofBench Agents with web search and SageMath write proofs for private PhD-level problems written by mathematicians. Experts grade the proofs, and final-answer subquestions are graded automatically. | Research frontier | Graded by people | 49.3% | Not in cards |
| BrokenArXiv Models are asked to prove statements from recent arXiv papers that were changed to be plausible but false. Full credit goes to models that say the statement is false. | Research frontier | Graded by a model | 83.1% | In use |
| First Proof Third Batch The editors run five AI systems once each on ten unpublished research problems with proofs of up to 12 pages. About 30 referees score correctness, exposition and attribution. The score is average correctness, from negative 1 to 1. | Research frontier | Graded by people | 0.65 | Not in cards |
| Hy-Euler pro Models with tools solve Tencent in-house STEM problems. Task and scoring details are not published. | Expert | Checked automatically | | In use |
| First Proof AI systems attempt ten unpublished research problems that arose in the authors' own work. Mathematicians judge whether each proof is correct. | Research frontier | Graded by people | Not in cards | |
| First Proof Second Batch The editors run AI harnesses once each, with 24 hours, on ten unpublished research problems with human proofs of up to eight pages. Referees grade each answer blind. | Research frontier | Graded by people | Not in cards | |
| FrontierMath: Open Problems Models attack unsolved research math problems proposed by working mathematicians. Each problem has a program that checks a proposed solution. Epoch tracks which problems AI has solved. | Research frontier | Checked automatically | Not in cards | |
| Soohak Models solve 439 new research-level and graduate math problems written by mathematicians. A 340-item Challenge subset tests solving and a 99-item Refusal subset tests spotting ill-posed problems. | Research frontier | Checked automatically | Not in cards | |
| TCS-Bench Models write proofs of target results from STOC, FOCS and SODA papers, given the needed context. A verification agent, checked against expert judgments, grades each proof. | Research frontier | Graded by a model | Not in cards |