What is the IQ of gpt-6-luna?

gpt-6-luna has an estimated IQ of 125, which ranks #27 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-luna best at?

Among the dimensions with published benchmark results, gpt-6-luna ranks highest in Mathematical Reasoning (IQ 138, #18 of 176) and Computer Use (IQ 129, #19 of 176). Its lowest-ranked measured dimension is Abstract Reasoning (IQ 99, #62 of 201).

What is the EQ of gpt-6-luna?

gpt-6-luna 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-luna. 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-luna been tested on?

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

How much does gpt-6-luna cost?

gpt-6-luna costs $0.10 per million input tokens and $0.50 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.7684 per million input-plus-output tokens.

Is gpt-6-luna open source?

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

Who developed gpt-6-luna?

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

When was gpt-6-luna released?

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

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

gpt-6-luna 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-luna?

In independent measurements, gpt-6-luna generates about 124 tokens per second, with a typical response time of about 106 seconds.

OpenAIReleased Sep 22, 2026

Proprietary

gpt-6-luna

Strongest in Mathematical Reasoning (#18 of 176) and Computer Use (#19 of 176); weakest in Abstract Reasoning (#62 of 201). All seven dimensions are measured.

Composite IQ ?

125

#27 of 176 ranked models · ahead of 85%

OpenAI's #8 model, behind gpt-6.1-sol (141)

Effective cost

$0.768/1M

$0.10 in · $0.50 out

Speed

124tok/s

106s 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

99measured

#62 / 201

5/5

-27.5

Mathematical ReasoningMath

138measured

#18 / 176

3/5

-9

Academic ReasoningAcademic

131measured

#31 / 203

4/6

-4.5

Programmatic ReasoningCoding

132measured

#38 / 177

3/6

-17.5

Computer UseComputer Use

129measured

#19 / 176

2/5

-14

ReliabilityReliability

119measured

#48 / 177

4/6

-15

Knowledge WorkKnowledge Work

126measured

#27 / 176

5/6

-5.5

gpt-6-luna95% 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-luna. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 99 · measuredBest: #32 of 76 on Chess Puzzles5/5

BenchmarkScorePercentileRankLeader · source

Chess Puzzles

Epoch AI vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 14

31.0%

#32 / 76

Leader gpt-6-astra · 72.0%
Epoch AI vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 14

ARC-AGI-2

Full source leaderboard reconciliation · Oct 23

59.3%

#34 / 68

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

ARC-AGI-1

Full source leaderboard reconciliation · Oct 23

86.7%

#36 / 68

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

ARC-AGI-3

Full source leaderboard reconciliation · Oct 23

0.2%

#20 / 24

Leader gpt-6-astra · 62.7%
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

7.0%

#51 / 55

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

Mathematical Reasoning IQ 138 · measuredBest: #17 of 84 on FrontierMath Tier 1-33/5

BenchmarkScorePercentileRankLeader · source

FrontierMath Tier 1-3

Full source leaderboard reconciliation · Oct 23

78.9%

#17 / 84

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

FrontierMath Tier 4

Full source leaderboard reconciliation · Oct 23

56.1%

#16 / 72

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

ProofBench 1.1

Full source leaderboard reconciliation v1.1 · Oct 27

64.0%

#20 / 48

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

Not yet reported

MathArenaAIME

Academic Reasoning IQ 131 · measuredBest: #28 of 159 on CritPt4/6

BenchmarkScorePercentileRankLeader · source

CritPt

Artificial Analysis v4.3.2 · Oct 27

19.4%

#28 / 159

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

SciCode

Artificial Analysis v4.3.2 · Oct 27

54.6%

#36 / 167

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

MMMU-Pro

Artificial Analysis v4.3.2 · Oct 27

79.7%

#30 / 89

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

Humanity's Last Exam

Artificial Analysis v4.3.2 · Oct 27

38.5%

#57 / 167

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

Not yet reported

GPQA DiamondMMLU-Pro

Programmatic Reasoning IQ 132 · measuredBest: #37 of 104 on Terminal-Bench 4.03/6

BenchmarkScorePercentileRankLeader · source

Terminal-Bench 4.0

Artificial Analysis v4.3.2 · Oct 27

12.6%

#37 / 104

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

IOI V2

Full source leaderboard reconciliation v2 · Oct 27

55.6%

#21 / 43

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

ProgramBench

Full source leaderboard reconciliation · Oct 23

8.0%

#33 / 61

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

Not yet reported

LiveCodeBenchSWE-rebenchMirrorCode

Computer Use IQ 129 · measuredBest: #26 of 70 on Arena.ai Agent Arena2/5

BenchmarkScorePercentileRankLeader · source

Arena.ai Agent Arena

Arena.ai Agent Arena · Oct 26

2.2

#26 / 70

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

Agents' Last Exam

Full source leaderboard reconciliation · Oct 23

25.0%

#14 / 29

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

Not yet reported

BrowseCompOSWorld-VerifiedMCP Atlas

Reliability IQ 119 · measuredBest: #13 of 154 on AA Long Context Reasoning v1.14/6

BenchmarkScorePercentileRankLeader · source

AA Long Context Reasoning v1.1

Artificial Analysis v4.3.2 · Oct 27

83.3%

#13 / 154

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

BullshitBench v2

Full source leaderboard reconciliation · Oct 23

58.0%

#22 / 83

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

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

0.7

#70 / 158

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

SimpleQA Verified

Full source leaderboard reconciliation · Oct 23

41.4%

#46 / 80

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

Not yet reported

IFBenchFACTS Grounding

Knowledge Work IQ 126 · measuredBest: #16 of 106 on GDP.pdf5/6

BenchmarkScorePercentileRankLeader · source

GDP.pdf

Artificial Analysis v4.3.2 · Oct 27

22.8%

#16 / 106

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

GDPval-AA v2.1 normalized score

Artificial Analysis v4.3.2 · Oct 23

46.6%

#39 / 124

Leader opus-5.5 · 68.3%
Artificial Analysis v4.3.2 · Oct 23

AA-Briefcase v1.1 Elo

Artificial Analysis v4.3.2 · Oct 27

1,336

#37 / 111

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

AutomationBench-AA

Artificial Analysis v4.3.2 · Oct 27

53.2%

#36 / 106

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

AA-AnalystAgent

Full source leaderboard reconciliation vpass^5-2026-09-29 · Oct 27

43.8%

#19 / 35

Leader gemini-3.7-flash · 60.0%
Full source leaderboard reconciliation vpass^5-2026-09-29 · Oct 27

Not yet reported

EnterpriseOps-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-luna, ChatGPT Work, and Codex.
Weights: ProprietaryHosted access only
Inputs: textimage
Context: 1,050,000 tokens
API price: $0.10 in · $0.50 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-luna

About this score

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

26/ 39benchmark results

7/ 7dimensions measured

0estimated

5/5Abstract

3/5Math

4/6Academic

3/6Coding

2/5Computer Use

4/6Reliability

5/6Knowledge 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 Luna; 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-luna

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

#1 overall

gpt-6.1-sol

IQ141 16 higherEffective cost$6.30 8.2× pricier

Predecessor

gpt-5.6-luna

IQ124 1 lowerEffective cost$1.63 2.1× pricier

Closest IQ

mimo-v2.6-pro

IQ125 same IQEffective cost$1.52 2.0× pricier

Most similar profile

kimi-k3

IQ127 2 higherEffective cost$20.20 26.3× pricier

Similar price

Agnes 2.5 Pro Beta

IQ110 15 lowerEffective cost$0.82 about the same

#2 overall

opus-5.5

IQ141 16 higherEffective cost$35.73 46.5× pricier

gpt-6-lunaComparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about gpt-6-luna, 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-luna?: gpt-6-luna has an estimated IQ of 125, which ranks #27 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-luna best at?: Among the dimensions with published benchmark results, gpt-6-luna ranks highest in Mathematical Reasoning (IQ 138, #18 of 176) and Computer Use (IQ 129, #19 of 176). Its lowest-ranked measured dimension is Abstract Reasoning (IQ 99, #62 of 201).
What is the EQ of gpt-6-luna?: gpt-6-luna 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-luna. 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-luna been tested on?: gpt-6-luna has published results on 26 of the 39 benchmarks behind AI IQ's Composite IQ, including AA Long Context Reasoning v1.1, GDP.pdf, CritPt, FrontierMath Tier 1-3 and SciCode.
How much does gpt-6-luna cost?: gpt-6-luna costs $0.10 per million input tokens and $0.50 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.7684 per million input-plus-output tokens.
Is gpt-6-luna open source?: No — gpt-6-luna is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed gpt-6-luna?: gpt-6-luna was developed by OpenAI, based in the United States.
When was gpt-6-luna released?: gpt-6-luna was publicly released on September 22, 2026.
How large is the context window of gpt-6-luna?: gpt-6-luna 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-luna?: In independent measurements, gpt-6-luna generates about 124 tokens per second, with a typical response time of about 106 seconds.