OpenAIUnited States· released Nov 2025
Provisional: 5 comparable tests so far. Ranked once it reaches 6 across 3 counting categories.
OpenAI, United States. One of 26 models from this lab on the Index.
Snapshot September 8, 2026
OpenCharts Index
28.8
Provisional: not enough comparable tests or counting categories to rank yet · 5 comparable tests · 0 counting categories
Drop any single test and the Index lands between 26.5 and 38.7.
Needs more results (2 of 8 so far)
Averaging 74.6 on the 2 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 ProofBench, 91.0% behind the best published result. No comparable results yet in reasoning, knowledge, multimodal, human preference and long context. Below 40% of 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
Complete software tasks of increasing length; the score is the task length a model finishes with 50% reliability.
3.7 h
77.8% of the best (17.4 h) on a log scale · #8 of 14.
The horizon a model can work through unsupervised is the clearest measure of how much you can delegate.
Where it trails
Write a complete, rigorous proof, graded for rigor rather than for a final answer.
9.0%
91.0% behind the best published result (100.0%) · #50 of 61.
A proof shows the reasoning itself. A right answer with a wrong argument scores nothing.
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.
Agentic · mean 64.3 across 3 comparable tests · not counted toward the Index yet (fewer than half the category's tests)
Complete software tasks of increasing length; the score is the task length a model finishes with 50% reliability.
3.7 h
77.8% of the best (17.4 h) on a log scale
#8 of 14
max
METR publishes wide confidence intervals around each horizon; the point estimate is used here.
Source: METRComplete a real task inside a terminal, such as setting up a service, fixing a build or wrangling data, verified by tests.
60.4%
71.3% of the best (84.7%)
#13 of 40
max · agent: Codex CLI
Harnesses differ by model, so this compares model-plus-harness systems, not models alone.
Source: Terminal-BenchComplete professional-services work in consulting, law and finance as an agent, graded against expert rubrics.
20.7%
43.7% of the best (47.4%)
#27 of 49
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.
GPT-5.1 Codex
provisional·Index 28.8F
0 : 3
wins · 0 ties · 3 shared
GPT-6 Astra
#1·Index 99.0A+
GPT-6 Astra comes out ahead on 3 of the 3 tests both have taken.
Category means
Reasoning
Knowledge
Coding
Math
Agentic
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.
1,336
7% expected win rate against the board leader (1,797)
15th percentile of 86
board 2026-09-05
Source: Arena (LMArena) — Leaderboard Dataset9.0%
9.0% of the best (100.0%)
15th percentile of 61
max · reasoning effort: high
Source: Epoch AI — AI Benchmarking Hub60.4%
71.3% of the best (84.7%)
69th percentile of 40
max · agent: Codex CLI
Source: Epoch AI — AI Benchmarking Hub3.7 h
77.8% of the best (17.4 h) on a log scale
46th percentile of 14
max
Source: Epoch AI — AI Benchmarking Hub20.7%
43.7% of the best (47.4%)
44th percentile of 49
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.