OpenAIUnited States· released Jul 2026

GPT-5.6 Sol Pro

Name: GPT-5.6 Sol Pro
Author: OpenAI

Provisional: 4 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.

Third-party publishedLow confidence (thin coverage)

Snapshot September 8, 2026

OpenCharts Index

87.7

Provisional: not enough comparable tests or counting categories to rank yet · 4 comparable tests · 0 counting categories

Drop any single test and the Index lands between 84.8 and 89.4.

Needs more results (1 of 8 so far)

Averaging 82.5 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

GPT-5.6 Sol Pro, in 4 results.

Its widest gap is on FrontierMath Tier 4, 17.5% behind the best published result. No comparable results yet in knowledge, multimodal, human preference and long context. Between 10% and 15% 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

WeirdML

Solve an unusual machine-learning task end to end: write the training code, run it, and hit an accuracy target.

89.4%

96.3% of the best (92.9%) · #5 of 69.

Real machine-learning work is messy and unfamiliar. This rewards models that can experiment rather than recite a tutorial.

Where it trails

FrontierMath Tier 4

Solve the hardest FrontierMath tier: problems that take expert mathematicians days.

80.5%

17.5% behind the best published result (97.6%) · #5 of 51.

The deepest end of the set. Progress here signals genuinely new capability.

Not measured yet

No comparable result yet in these 4 categories. A blank is a blank, never a zero, and it does not lower the Index.

Knowledge
Multimodal
Human preference
Long context

Covered, but not averaged into the Index:

Reasoning1 of 6 tests · needs 3 · mean 87.5
Coding1 of 7 tests · needs 4 · mean 96.3
Math1 of 5 tests · needs 3 · mean 82.5
Agentic1 of 8 tests · needs 4 · mean 84.4

Every score, with its source

See it at work

What GPT-5.6 Sol Pro was asked to do, and how it did.

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.

Coding · mean 96.3 across 1 comparable test · not counted toward the Index yet (fewer than half the category's tests)

WeirdMLLeaderboard

Solve an unusual machine-learning task end to end: write the training code, run it, and hit an accuracy target.

89.4%

96.3% of the best (92.9%)
#5 of 69

promax

Source: Håvard Ihle

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

GPT-5.6 Sol Pro against whoever you pick.

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-5.6 Sol Pro

provisional·Index 87.7A-

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
87.5
99.6
Knowledge
—
100.0
Coding
96.3
97.7
Math
82.5
99.8
Agentic
84.4
98.5

Shared tests · biggest gaps first

FrontierMath Tier 4Math
80.5%
97.6%
−17.5
APEX-AgentsAgentic
40.0%
46.7%
−14.1
WeirdMLCoding
89.4%
92.9%
−3.7

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 Astra

Scores

Every test, every source

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

Reasoning87.5 · 1/6
Knowledge—
Coding96.3 · 1/7
Math82.5 · 1/5
Agentic84.4 · 1/8
Multimodal—
Human preference—
Long context—

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.

SimpleBenchLeaderboardReasoning

71.7%

87.5% of the best (81.9%)
80th percentile of 46

proxhigh

Source: Epoch AI — AI Benchmarking Hub

WeirdMLLeaderboardCoding

89.4%

96.3% of the best (92.9%)
94th percentile of 69

promax

Source: Epoch AI — AI Benchmarking Hub

FrontierMath Tier 4Epoch-runMath

80.5%