Solve competition mathematics problems that have a single exact integer answer.
91.1%
91.1% of the best (100.0%)
#37 of 78 Β· n = 45
45 problems: one problem is 2.2 points, so gaps of a few points are within noise.
Source: Epoch AI (internal runs)AlibabaChinaΒ· released Apr 2026Β· open weights
Provisional: 5 comparable tests so far. Ranked once it reaches 6 across 3 counting categories.
Alibaba, China. One of 19 models from this lab on the Index.
Snapshot September 8, 2026
OpenCharts Index
56.3
Provisional: not enough comparable tests or counting categories to rank yet Β· 5 comparable tests Β· 0 counting categories
Drop any single test and the Index lands between 42.4 and 70.1.
Needs more results (1 of 8 so far)
Averaging 37.5 on the 1 it has; the score opens at 4 of 8.
Distance to today's frontier on the hardest tests. Not a measure of intelligence.
What it's known for
Its widest gap is on CritPt, 97.3% behind the best published result. No comparable results yet in knowledge, agentic, multimodal, human preference and long context. Between 40% and 50% behind the best published results, on average.
Strongest category
No category counts yet: a category counts once it has more than one comparable test and the model has taken at least half of them. The scores it has are below.
Best single result
Solve competition mathematics problems that have a single exact integer answer.
91.1%
91.1% of the best (100.0%) Β· #37 of 78.
Olympiad-style problems need long, careful chains of reasoning, and there is no partial credit.
Where it trails
Solve an unpublished research-level physics problem to a numeric or symbolic answer checked by an official server.
0.9%
97.3% behind the best published result (32.3%) Β· #66 of 78.
Research physics is far past textbook recall. Only a few models produce anything a physicist would accept.
Not measured yet
No comparable result yet in these 5 categories. A blank is a blank, never a zero, and it does not lower the Index.
Covered, but not averaged into the Index:
See it at work
Every test it has taken, by category, with the kind of task it faced, who produced the number and where the result landed against the best published one. The examples are original and illustrative, never items from the datasets themselves.
Math Β· mean 64.3 across 2 comparable tests Β· not counted toward the Index yet (fewer than half the category's tests)
Solve competition mathematics problems that have a single exact integer answer.
91.1%
91.1% of the best (100.0%)
#37 of 78 Β· n = 45
45 problems: one problem is 2.2 points, so gaps of a few points are within noise.
Source: Epoch AI (internal runs)Solve unpublished research-level mathematics problems written by professional mathematicians (tiers 1 to 3).
35.1%
37.5% of the best (93.7%)
#45 of 61 Β· n = 290
Commissioned by OpenAI, which has access to much of the problem set; Epoch discloses this and keeps a holdout it does not share.
Source: Epoch AI (internal runs)Every result is read against the best published one on its test: percent scores as a share of the best above chance, Arena ratings as the expected win rate against the board leader, open-ended values on a log scale. Sitting a harder exam never lowers a model. Every number links to the publisher that produced it.
Head to head
Choose a rival. Every counted test both have taken appears side by side as a share of the best published result on that test, with the category means above. A win is a higher share; a gap under 2 points is a tie, because one item on a 45-problem exam is 2.2 points and publishers' own standard errors are of that order.
Qwen3.6 27B
provisionalΒ·Index 56.3C-
0 : 5
wins Β· 0 ties Β· 5 shared
GPT-6 Astra
#1Β·Index 99.0A+
GPT-6 Astra comes out ahead on 5 of the 5 tests both have taken.
Category means
Reasoning
Knowledge
Coding
Math
Agentic
Shared tests Β· biggest gaps first
Bars are distances to the best published result on each test (percent scores above chance, Arena ratings as win rate against the leader, open-ended values on a log scale). Raw values as the publishers report them.
Open GPT-6 AstraScores
The best published run per benchmark, the raw value as the publisher reports it, who produced the number, how close it comes to the best published result on that test, and where the model sits among every model scored on it. Percent scores are read above chance, Arena ratings as a win rate against the board leader, open-ended values on a log scale. A test with too few models to compare against is shown but not counted.
Category means
Mean Β· tests taken of the category's comparable tests. A faded category either rests on fewer than half of them or is a single-test category (marked βbesideβ), which is shown next to the Index and never averaged into it.
85.9%
86.0% of the best (95.8%), above chance
34th percentile of 78 Β· n = 198
0.9%
2.7% of the best (32.3%)
14th percentile of 78
none
Source: Epoch AI β AI Benchmarking Hub37.3%
60.1% of the best (62.0%)
10th percentile of 73 Β· n = 338
none
Source: Epoch AI β AI Benchmarking Hub91.1%
91.1% of the best (100.0%)
51th percentile of 78 Β· n = 45
35.1%
37.5% of the best (93.7%)
27th percentile of 61 Β· n = 290
Top of the leaderboard

28 of the models on this page run inside Theo today. Theo picks the right one for each step and always shows which engine answered.