Answer the same prompt as a rival model; real users vote blind on which answer they prefer.
1,472
45% expected win rate against the board leader (1,507)
#28 of 92
board 2026-09-02
Source: ArenaAnthropicUnited States· released Feb 2026
Ranked #22, 36.1% behind the frontier on average.
Anthropic, United States. One of 12 models from this lab on the Index.

Available in Theo as Theo Balanced
Theo orchestrates it for the steps it does best and always shows which engine answered.
Snapshot September 8, 2026
OpenCharts Index
63.9
Ranked #22 (18 to 28) of 36 · 36.1% behind the frontier on average · 20 comparable tests · 3 counting categories
Drop any single test and the Index lands between 61.0 and 69.7, anywhere from #18 to #28. Neighbours inside that range are ties.
Needs more results (3 of 8 so far)
Averaging 72.2 on the 3 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
Strongest in agentic (65.6) and coding (63.8). It trails the frontier most in reasoning, 37.7% behind on average. No comparable result yet in long context. Between 35% and 40% behind the best published results, on average. Drop any single test and it would sit anywhere from #18 to #28.
Strongest category
Agentic
Long-horizon tasks with tools: terminals, desktops, browsers, whole jobs.
65.6
Mean of 5 of the category's 8 comparable tests. Counts toward the Index.
Best single result
Write a PhD-level research brief with web access, graded on coverage, insight and citations.
54.9%
99.3% of the best (55.3%) · #2 of 19.
A research agent lives or dies on whether its sources are real and its synthesis is right.
Where it trails
Solve an unpublished research-level physics problem to a numeric or symbolic answer checked by an official server.
3.1%
90.3% behind the best published result (32.3%) · #50 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 this category. 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.
Human preference · mean 90.0 across 1 comparable test · a single-test category, shown beside the Index and never averaged into it
Answer the same prompt as a rival model; real users vote blind on which answer they prefer.
1,472
45% expected win rate against the board leader (1,507)
#28 of 92
board 2026-09-02
Source: ArenaEvery 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.
Claude Sonnet 4.6
#22·Index 63.9C
0 : 12
wins · 0 ties · 12 shared
GPT-6 Astra
#1·Index 99.0A+
GPT-6 Astra comes out ahead on 12 of the 12 tests both have taken.
Category means
Reasoning
Knowledge
Coding
Math
Agentic
Multimodal
Human preference
Shared tests · 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 · 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 “beside”), which is shown next to the Index and never averaged into it.
87.4%
88.1% of the best (95.8%), above chance
43th percentile of 78 · n = 198
32k
Source: Epoch AI — AI Benchmarking Hub60.4%
63.6% of the best (95.0%)
54th percentile of 51 · n = 120
high
Source: Epoch AI — AI Benchmarking Hub86.5%
87.8% of the best (98.5%)
48th percentile of 51 · n = 100
high
Source: Epoch AI — AI Benchmarking Hub3.1%
9.7% of the best (32.3%)
32th percentile of 78
max
Source: Epoch AI — AI Benchmarking Hub35.5%
47.0% of the best (75.6%)
36th percentile of 57 · n = 1,000
high
Source: Epoch AI — AI Benchmarking Hub75.2%
90.1% of the best (83.5%)
52th percentile of 26 · n = 500
46.8%
75.4% of the best (62.0%)
46th percentile of 73 · n = 338
max
Source: Epoch AI — AI Benchmarking Hub66.1%
71.1% of the best (92.9%)
68th percentile of 69
medium
Source: Epoch AI — AI Benchmarking Hub24.3%
45.5% of the best (53.5%)
23th percentile of 27
harness: claude-code · reasoning effort: max
Source: Epoch AI — AI Benchmarking Hub49.0%
66.8% of the best (73.4%)
10th percentile of 21
max · reasoning level: Max
Source: Epoch AI — AI Benchmarking Hub1,521
17% expected win rate against the board leader (1,797)
69th percentile of 86
board 2026-09-05
Source: Arena (LMArena) — Leaderboard Dataset85.8%
85.8% of the best (100.0%)
29th percentile of 78 · n = 45
32k
Source: Epoch AI — AI Benchmarking Hub45.0%
45.0% of the best (100.0%)
65th percentile of 61
max · reasoning effort: max
Source: Epoch AI — AI Benchmarking Hub53.4%
63.0% of the best (84.7%)
64th percentile of 40
agent: Simplai Agent
Source: Epoch AI — AI Benchmarking Hub9.3%
29.6% of the best (31.4%)
38th percentile of 9 · n = 108
medium
Source: Epoch AI — AI Benchmarking Hub23.7%
50.0% of the best (47.4%)
48th percentile of 49
high
Source: Epoch AI — AI Benchmarking Hub$7,204
85.9% of the best ($11,182) on a log scale
83th percentile of 53
54.9%
99.3% of the best (55.3%)
94th percentile of 19 · n = 100
high
Source: Epoch AI — AI Benchmarking Hub1,275
45% expected win rate against the board leader (1,313)
66th percentile of 54
board 2026-08-27
Source: Arena (LMArena) — Leaderboard Dataset1,472
45% expected win rate against the board leader (1,507)
70th percentile of 92
board 2026-09-02
Source: Arena (LMArena) — Leaderboard DatasetNearby on 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.