What is the IQ of gpt-5-nano?

gpt-5-nano has an estimated IQ of 95, which ranks #146 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-5-nano best at?

Among the dimensions with published benchmark results, gpt-5-nano ranks highest in Programmatic Reasoning (IQ 109, #98 of 177) and Mathematical Reasoning (IQ 103, #111 of 176). Its lowest-ranked measured dimension is Reliability (IQ 98, #153 of 177).

What is the EQ of gpt-5-nano?

gpt-5-nano 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-5-nano. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.

Which benchmarks has gpt-5-nano been tested on?

gpt-5-nano has published results on 19 of the 39 benchmarks behind AI IQ's Composite IQ, including Chess Puzzles, IFBench, AIME, AA Omniscience and LiveCodeBench.

How much does gpt-5-nano cost?

gpt-5-nano costs $0.05 per million input tokens and $0.40 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.2725 per million input-plus-output tokens.

Is gpt-5-nano open source?

No — gpt-5-nano is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.

Who developed gpt-5-nano?

gpt-5-nano was developed by OpenAI, based in the United States.

When was gpt-5-nano released?

gpt-5-nano was publicly released on August 7, 2025.

How large is the context window of gpt-5-nano?

AI IQ hasn't verified an input context limit for gpt-5-nano from its developer's documentation, so none is listed rather than guessing.

How fast is gpt-5-nano?

In independent measurements, gpt-5-nano generates about 160 tokens per second, with a typical response time of about 79 seconds.

OpenAIReleased Aug 7, 2025

Proprietary

gpt-5-nano

Its best results are in Programmatic Reasoning (#98 of 177) and Mathematical Reasoning (#111 of 176); weakest in Reliability (#153 of 177). Computer Use and Knowledge Work are estimated, because no results are published yet.

Composite IQ ?

#146 of 176 ranked models · ahead of 17%

OpenAI's #19 model, behind gpt-6.1-sol (141)

Effective cost

$0.273/1M

$0.05 in · $0.40 out

Speed

160tok/s

79s typical response

Context

Unverified

Not in publisher docs

Evidence

5of 7 dims

19 of 39 benchmarks

Compare with gpt-6.1-solAPI pricing

IQ profile

Seven dimensions, averaged equally into Composite IQ

Compare shape with

MeasuredEstimated95% 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

83measured

#146 / 201

4/5

-43.5

Mathematical ReasoningMath

103measured

#111 / 176

4/5

-44

Academic ReasoningAcademic

106measured

#150 / 203

6/6

-29.5

Programmatic ReasoningCoding

109measured

#98 / 177

1/6

-40.5

Computer UseComputer Use

75estimated

#149 / 176

0/5

-68

ReliabilityReliability

98measured

#153 / 177

4/6

-36

Knowledge WorkKnowledge Work

90estimated

#158 / 176

0/6

-41.5

gpt-5-nano95% range (model-based, uncalibrated)Top-10 median#1 in dimension100 = average human

Benchmark results

19 of 39 Composite IQ benchmarks have a published result for gpt-5-nano. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 83 · measuredBest: #37 of 76 on Chess Puzzles4/5

BenchmarkScorePercentileRankLeader · source

Chess Puzzles

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

27.0%

#37 / 76

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

Mystery Game Puzzles

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

9.0%

#48 / 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-2

Full source leaderboard reconciliation · Oct 23

2.6%

#60 / 68

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

ARC-AGI-1

Full source leaderboard reconciliation · Oct 23

20.7%

#62 / 68

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

Not yet reported

ARC-AGI-3

Mathematical Reasoning IQ 103 · measuredBest: #40 of 56 on AIME4/5

BenchmarkScorePercentileRankLeader · source

AIME

81.2%

#40 / 56

Leader gemini-3.1-pro · 98.1%

FrontierMath Tier 4

Full source leaderboard reconciliation · Oct 23

2.4%

#62 / 72

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

FrontierMath Tier 1-3

Full source leaderboard reconciliation · Oct 23

20.0%

#73 / 84

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

MathArena

Full source leaderboard reconciliation · Oct 28

12.4%

#56 / 64

Leader gpt-6.1-sol · 84.0%
Full source leaderboard reconciliation · Oct 28

Not yet reported

ProofBench 1.1

Academic Reasoning IQ 106 · measuredBest: #36 of 45 on MMLU-Pro6/6

BenchmarkScorePercentileRankLeader · source

MMLU-Pro

TIGER-Lab MMLU-Pro leaderboard (missing rows only) · Sep 22

78.0%

#36 / 45

Leader fable-5.1 · 92.4%
TIGER-Lab MMLU-Pro leaderboard (missing rows only) · Sep 22

SciCode

Artificial Analysis model leaderboard · Sep 10

37.0%

#136 / 167

Leader opus-5.5 · 66.9%
Artificial Analysis model leaderboard · Sep 10

Humanity's Last Exam

Artificial Analysis v4.3.2 · Oct 27

9.5%

#147 / 167

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

GPQA Diamond

Artificial Analysis v4.3.2 · Oct 27

67.6%

#130 / 147

Leader gpt-6-astra · 96.1%
Artificial Analysis v4.3.2 · Oct 27

CritPt

Artificial Analysis v4.3.2 · Oct 27

0.0%

#142 / 159

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

MMMU-Pro

Artificial Analysis v4.3.2 · Oct 27

61.0%

#81 / 89

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

Programmatic Reasoning IQ 109 · measuredBest: #48 of 61 on LiveCodeBench1/6

BenchmarkScorePercentileRankLeader · source

LiveCodeBench

Vals.ai · Aug 4

70.2%

#48 / 61

Leader Fugu Ultra v1.0 · 93.2%
Vals.ai · Aug 4

Not yet reported

IOI V2Terminal-Bench 4.0ProgramBenchSWE-rebenchMirrorCode

Computer Use IQ 75 · estimatedNo published results0/5

No published results yet for Computer Use. The 75 shown is estimated from gpt-5-nano's other dimensions and will be replaced as results come in. How estimates work

BrowseCompOSWorld-VerifiedMCP AtlasArena.ai Agent ArenaAgents' Last Exam

Reliability IQ 98 · measuredBest: #54 of 96 on IFBench4/6

BenchmarkScorePercentileRankLeader · source

IFBench

Artificial Analysis v4.3.2 · Oct 27

67.6%

#54 / 96

Leader minimax-m3 · 82.9%
Artificial Analysis v4.3.2 · Oct 27

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

-28.7

#122 / 158

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

AA Long Context Reasoning v1.1

Artificial Analysis v4.3.2 · Oct 27

45.0%

#140 / 154

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

SimpleQA Verified

Full source leaderboard reconciliation · Oct 23

11.7%

#78 / 80

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

Not yet reported

BullshitBench v2FACTS Grounding

Knowledge Work IQ 90 · estimatedNo published results0/6

No published results yet for Knowledge Work. The 90 shown is estimated from gpt-5-nano's other dimensions and will be replaced as results come in. How estimates work

AA-Briefcase v1.1GDPval-AA v2.1AutomationBench-AAGDP.pdfAA-AnalystAgentEnterpriseOps-Gym-AA

Release & availability

Release details on record for this model.

Released: Aug 7, 2025
Developer: OpenAI
Weights: ProprietaryHosted access only
API price: $0.05 in · $0.40 outper 1M tokens · full pricing

About this score

How much of gpt-5-nano's IQ is measured, and how the rest is estimated.

19/ 39benchmark results

5/ 7dimensions measured

2estimated

4/5Abstract

4/5Math

6/6Academic

1/6Coding

0/5Computer Use

4/6Reliability

0/6Knowledge 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.

Estimates fill the gaps

Computer Use and Knowledge Work have no published results yet, so their IQ is estimated from gpt-5-nano's other dimensions.

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-5-nano

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Gemini 4 Argon

IQ140 45 higher

gpt-5-nanoComparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about gpt-5-nano, 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-5-nano?: gpt-5-nano has an estimated IQ of 95, which ranks #146 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-5-nano best at?: Among the dimensions with published benchmark results, gpt-5-nano ranks highest in Programmatic Reasoning (IQ 109, #98 of 177) and Mathematical Reasoning (IQ 103, #111 of 176). Its lowest-ranked measured dimension is Reliability (IQ 98, #153 of 177).
What is the EQ of gpt-5-nano?: gpt-5-nano 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-5-nano. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.
Which benchmarks has gpt-5-nano been tested on?: gpt-5-nano has published results on 19 of the 39 benchmarks behind AI IQ's Composite IQ, including Chess Puzzles, IFBench, AIME, AA Omniscience and LiveCodeBench.
How much does gpt-5-nano cost?: gpt-5-nano costs $0.05 per million input tokens and $0.40 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.2725 per million input-plus-output tokens.
Is gpt-5-nano open source?: No — gpt-5-nano is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed gpt-5-nano?: gpt-5-nano was developed by OpenAI, based in the United States.
When was gpt-5-nano released?: gpt-5-nano was publicly released on August 7, 2025.
How large is the context window of gpt-5-nano?: AI IQ hasn't verified an input context limit for gpt-5-nano from its developer's documentation, so none is listed rather than guessing.
How fast is gpt-5-nano?: In independent measurements, gpt-5-nano generates about 160 tokens per second, with a typical response time of about 79 seconds.