What is the IQ of gpt-6-sol?

gpt-6-sol has an estimated IQ of 137, which ranks #7 out of 176 public models on the AI IQ leaderboard. The score combines seven equally weighted reasoning dimensions using measured benchmark results and conservative estimates for missing coverage.

What is gpt-6-sol best at?

Among the dimensions with published benchmark results, gpt-6-sol ranks highest in Mathematical Reasoning (IQ 148, #4 of 176) and Programmatic Reasoning (IQ 149, #6 of 177). Its lowest-ranked measured dimension is Knowledge Work (IQ 130, #13 of 176).

What is the EQ of gpt-6-sol?

gpt-6-sol doesn't have an EQ score yet. EQ (emotional reasoning) is calculated from EQ-Bench 4 and AttuneBench, and neither has published a result for gpt-6-sol. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.

Which benchmarks has gpt-6-sol been tested on?

gpt-6-sol has published results on 26 of the 39 benchmarks behind AI IQ's Composite IQ, including FACTS Grounding, CritPt, MathArena, AA Long Context Reasoning v1.1 and FrontierMath Tier 1-3.

How much does gpt-6-sol cost?

gpt-6-sol costs $2.00 per million input tokens and $10.00 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $9.84 per million input-plus-output tokens.

Is gpt-6-sol open source?

No — gpt-6-sol is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.

Who developed gpt-6-sol?

gpt-6-sol was developed by OpenAI, based in the United States.

When was gpt-6-sol released?

gpt-6-sol was publicly released on September 22, 2026.

How large is the context window of gpt-6-sol?

gpt-6-sol supports a context window of 1,050,000 tokens — the amount of text it can consider in a single request.

How fast is gpt-6-sol?

In independent measurements, gpt-6-sol generates about 122 tokens per second, with a typical response time of about 122 seconds.

OpenAIReleased Sep 22, 2026

Proprietary

gpt-6-sol

Strongest in Mathematical Reasoning (#4 of 176) and Programmatic Reasoning (#6 of 177); weakest in Knowledge Work (#13 of 176). All seven dimensions are measured.

Composite IQ ?

137

#7 of 176 ranked models · ahead of 97%

OpenAI's #3 model, behind gpt-6.1-sol (141)

Effective cost

$9.84/1M

$2 in · $10 out

Speed

122tok/s

122s typical response

Context

1Mtokens

1,050,000 tokens in

Evidence

7of 7 dims

26 of 39 benchmarks

Compare with gpt-6.1-solAPI pricing

IQ profile

Seven dimensions, averaged equally into Composite IQ

Compare shape with

Measured95% range

#1 in dimensionTop-10 median

IQ dimensions

Ranks are among models scored in each dimension. Ranges are model-based estimates, not calibrated confidence intervals.

DimensionIQPosition · 70–160RankEvidencevs Top 10

Abstract ReasoningAbstract

124measured

#10 / 201

4/5

-2.5

Mathematical ReasoningMath

148measured

#4 / 176

4/5

Academic ReasoningAcademic

135measured

#10 / 203

4/6

-0.5

Programmatic ReasoningCoding

149measured

#6 / 177

3/6

-0.5

Computer UseComputer Use

140measured

#9 / 176

2/5

-3

ReliabilityReliability

130measured

#9 / 177

5/6

-4

Knowledge WorkKnowledge Work

130measured

#13 / 176

4/6

-1.5

gpt-6-sol95% range (model-based, uncalibrated)Top-10 median#1 in dimension100 = average human

Benchmark results

26 of 39 Composite IQ benchmarks have a published result for gpt-6-sol. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 124 · measuredBest: #8 of 68 on ARC-AGI-24/5

BenchmarkScorePercentileRankLeader · source

ARC-AGI-2

Full source leaderboard reconciliation · Oct 23

89.6%

#8 / 68

Leader gpt-6-astra · 95.0%
Full source leaderboard reconciliation · Oct 23

Mystery Game Puzzles

Full source leaderboard reconciliation vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 23

56.0%

#9 / 55

Leader gpt-6-astra · 84.0%
Full source leaderboard reconciliation vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 23

ARC-AGI-1

Full source leaderboard reconciliation · Oct 23

95.5%

#14 / 68

Leader fable-5 · 98.5%
Full source leaderboard reconciliation · Oct 23

ARC-AGI-3

Full source leaderboard reconciliation · Oct 23

4.6%

#8 / 24

Leader gpt-6-astra · 62.7%
Full source leaderboard reconciliation · Oct 23

Not yet reported

Chess Puzzles

Mathematical Reasoning IQ 148 · measuredBest: #3 of 64 on MathArena4/5

BenchmarkScorePercentileRankLeader · source

MathArena

Full source leaderboard reconciliation · Oct 26

79.9%

#3 / 64

Leader gpt-6.1-sol · 84.0%
Full source leaderboard reconciliation · Oct 26

FrontierMath Tier 1-3

Full source leaderboard reconciliation · Oct 23

89.8%

#6 / 84

Leader gpt-6-astra · 93.7%
Full source leaderboard reconciliation · Oct 23

FrontierMath Tier 4

Full source leaderboard reconciliation · Oct 23

90.0%

#6 / 72

Leader gpt-6.1-sol · 100%
Full source leaderboard reconciliation · Oct 23

ProofBench 1.1

Full source leaderboard reconciliation v1.1 · Oct 27

83.0%

#15 / 48

Leader fable-5.1 · 100%
Full source leaderboard reconciliation v1.1 · Oct 27

Not yet reported

AIME

Academic Reasoning IQ 135 · measuredBest: #7 of 159 on CritPt4/6

BenchmarkScorePercentileRankLeader · source

CritPt

Artificial Analysis v4.3.2 · Oct 27

30.9%

#7 / 159

Leader Muse Wonder Full · 32.9%
Artificial Analysis v4.3.2 · Oct 27

Humanity's Last Exam

Artificial Analysis v4.3.2 · Oct 27

47.9%

#18 / 167

Leader opus-5.5 · 61.4%
Artificial Analysis v4.3.2 · Oct 27

SciCode

Artificial Analysis v4.3.2 · Oct 27

57.6%

#19 / 167

Leader opus-5.5 · 66.9%
Artificial Analysis v4.3.2 · Oct 27

MMMU-Pro

Artificial Analysis v4.3.2 · Oct 27

82.9%

#15 / 89

Leader fable-5.1 · 90.6%
Artificial Analysis v4.3.2 · Oct 27

Not yet reported

GPQA DiamondMMLU-Pro

Programmatic Reasoning IQ 149 · measuredBest: #12 of 104 on Terminal-Bench 4.03/6

BenchmarkScorePercentileRankLeader · source

Terminal-Bench 4.0

Artificial Analysis v4.3.2 · Oct 27

43.9%

#12 / 104

Leader Kimi K3.1 Pro · 67.2%
Artificial Analysis v4.3.2 · Oct 27

ProgramBench

Full source leaderboard reconciliation · Oct 23

32.5%

#9 / 61

Leader opus-5.5 · 65.0%
Full source leaderboard reconciliation · Oct 23

IOI V2

Full source leaderboard reconciliation v2 · Oct 27

82.6%

#10 / 43

Leader Gemini 4 Argon · 100%
Full source leaderboard reconciliation v2 · Oct 27

Not yet reported

LiveCodeBenchSWE-rebenchMirrorCode

Computer Use IQ 140 · measuredBest: #3 of 29 on Agents' Last Exam2/5

BenchmarkScorePercentileRankLeader · source

Agents' Last Exam

Full source leaderboard reconciliation · Oct 23

32.2%

#3 / 29

Leader opus-5.5 · 38.2%
Full source leaderboard reconciliation · Oct 23

Arena.ai Agent Arena

Arena.ai Agent Arena · Oct 26

8.0

#12 / 70

Leader opus-5.5 · 20.9
Arena.ai Agent Arena · Oct 26

Not yet reported

BrowseCompOSWorld-VerifiedMCP Atlas

Reliability IQ 130 · measuredBest: #1 of 36 on FACTS Grounding5/6

BenchmarkScorePercentileRankLeader · source

FACTS Grounding

Full source leaderboard reconciliation · Oct 23

85.2%

#1 / 36

Leader on this benchmark
Full source leaderboard reconciliation · Oct 23

AA Long Context Reasoning v1.1

Artificial Analysis v4.3.2 · Oct 27

83.7%

#10 / 154

Leader kimi-k3 · 88.7%
Artificial Analysis v4.3.2 · Oct 27

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

27.1

#20 / 158

Leader opus-5.5 · 46.4
Artificial Analysis v4.3.2 · Oct 27

SimpleQA Verified

Full source leaderboard reconciliation · Oct 23

60.7%

#17 / 80

Leader Gemini 4 Argon · 76.0%
Full source leaderboard reconciliation · Oct 23

BullshitBench v2

Full source leaderboard reconciliation · Oct 23

54.0%

#31 / 83

Leader opus-4.8 · 94.0%
Full source leaderboard reconciliation · Oct 23

Not yet reported

IFBench

Knowledge Work IQ 130 · measuredBest: #12 of 106 on GDP.pdf4/6

BenchmarkScorePercentileRankLeader · source

GDP.pdf

Artificial Analysis v4.3.2 · Oct 27

25.2%

#12 / 106

Leader Muse Wonder Full · 32.6%
Artificial Analysis v4.3.2 · Oct 27

AutomationBench-AA

Artificial Analysis v4.3.2 · Oct 27

61.6%

#17 / 106

Leader Gemini 4 Argon · 77.5%
Artificial Analysis v4.3.2 · Oct 27

AA-Briefcase v1.1 Elo

Artificial Analysis v4.3.2 · Oct 27

1,477

#24 / 111

Leader sonnet-5.5 · 1,812
Artificial Analysis v4.3.2 · Oct 27

GDPval-AA v2.1 normalized score

Artificial Analysis v4.3.2 · Oct 20

50.4%

#29 / 124

Leader opus-5.5 · 68.3%
Artificial Analysis v4.3.2 · Oct 20

Not yet reported

AA-AnalystAgentEnterpriseOps-Gym-AA

Release & availability

Facts from the publisher's announcement and documentation.

Released: Sep 22, 2026
Developer: OpenAI
Access: Available through the OpenAI API as gpt-6-sol, ChatGPT Work, and Codex.
Weights: ProprietaryHosted access only
Inputs: textimage
Context: 1,050,000 tokens
API price: $2 in · $10 outper 1M tokens · full pricing

What OpenAI says

Designed for coding, computer use, and professional agent workflows.
Supports configurable reasoning effort from none through max and a 1,050,000-token context window.
Lower standard API token prices than its GPT-5.6 predecessor.

Limitations

Audio and video input are not supported.
Prompts above 272K input tokens incur higher rates.

Publisher statements, not AI IQ measurements.

Sourcesopenai.com/index/introducing-gpt-6-sol-and-luna developers.openai.com/api/docs/models/gpt-6-sol

About this score

How much of gpt-6-sol's IQ is measured, and how the rest is estimated.

26/ 39benchmark results

7/ 7dimensions measured

0estimated

4/5Abstract

4/5Math

4/6Academic

3/6Coding

2/5Computer Use

5/6Reliability

4/6Knowledge Work

Bar height = share of benchmarks with resultsEstimatedNo score

Measured results are shown as published

Every score in the benchmark tables comes from its source unchanged. Composite IQ averages all seven dimensions equally.

How gaps are handled

Every dimension has at least one published result. Missing benchmarks can also draw on its predecessor, GPT 5.6 Sol; a predecessor is an estimation input, not evidence that this model has the predecessor's measured results.

A missing result is not a zero

Benchmark versions and evaluation harnesses can differ between sources, so small gaps between models may not be meaningful.

Read the scoring methodology →

Compare gpt-6-sol

Side-by-side pages for the models it is most often weighed against.

#1 overall

gpt-6.1-sol

IQ141 4 higherEffective cost$6.30 1.6× cheaper

Predecessor

gpt-5.6-sol

IQ133 4 lowerEffective cost$27.47 2.8× pricier

Closest IQ

sonnet-5.5

IQ137 same IQEffective cost$21.04 2.1× pricier

Most similar profile

fable-5.1

IQ137 same IQEffective cost$91.05 9.3× pricier

Similar price

grok-4.6

IQ126 11 lowerEffective cost$8.88 1.1× cheaper

#2 overall

opus-5.5

IQ141 4 higherEffective cost$35.73 3.6× pricier

gpt-6-solComparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about gpt-6-sol, drawn from the same data as the rest of this page.

How AI IQ scores models →Get this data from the API →

What is the IQ of gpt-6-sol?: gpt-6-sol has an estimated IQ of 137, which ranks #7 out of 176 public models on the AI IQ leaderboard. The score combines seven equally weighted reasoning dimensions using measured benchmark results and conservative estimates for missing coverage.
What is gpt-6-sol best at?: Among the dimensions with published benchmark results, gpt-6-sol ranks highest in Mathematical Reasoning (IQ 148, #4 of 176) and Programmatic Reasoning (IQ 149, #6 of 177). Its lowest-ranked measured dimension is Knowledge Work (IQ 130, #13 of 176).
What is the EQ of gpt-6-sol?: gpt-6-sol doesn't have an EQ score yet. EQ (emotional reasoning) is calculated from EQ-Bench 4 and AttuneBench, and neither has published a result for gpt-6-sol. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.
Which benchmarks has gpt-6-sol been tested on?: gpt-6-sol has published results on 26 of the 39 benchmarks behind AI IQ's Composite IQ, including FACTS Grounding, CritPt, MathArena, AA Long Context Reasoning v1.1 and FrontierMath Tier 1-3.
How much does gpt-6-sol cost?: gpt-6-sol costs $2.00 per million input tokens and $10.00 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $9.84 per million input-plus-output tokens.
Is gpt-6-sol open source?: No — gpt-6-sol is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed gpt-6-sol?: gpt-6-sol was developed by OpenAI, based in the United States.
When was gpt-6-sol released?: gpt-6-sol was publicly released on September 22, 2026.
How large is the context window of gpt-6-sol?: gpt-6-sol supports a context window of 1,050,000 tokens — the amount of text it can consider in a single request.
How fast is gpt-6-sol?: In independent measurements, gpt-6-sol generates about 122 tokens per second, with a typical response time of about 122 seconds.