What is the IQ of gemini-3-pro?

gemini-3-pro has an estimated IQ of 114, which ranks #61 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 gemini-3-pro best at?

Among the dimensions with published benchmark results, gemini-3-pro ranks highest in Reliability (IQ 121, #34 of 177) and Academic Reasoning (IQ 128, #54 of 203). Its lowest-ranked measured dimension is Abstract Reasoning (IQ 91, #95 of 201).

What is the EQ of gemini-3-pro?

gemini-3-pro has an estimated EQ of 116. EQ measures emotional reasoning — how well a model reads and responds to emotional context — and is scored separately from IQ.

Which benchmarks has gemini-3-pro been tested on?

gemini-3-pro has published results on 20 of the 39 benchmarks behind AI IQ's Composite IQ, including SimpleQA Verified, AIME, MMLU-Pro, LiveCodeBench and SciCode.

How much does gemini-3-pro cost?

gemini-3-pro costs $2.00 per million input tokens and $12.00 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $14.78 per million input-plus-output tokens.

Is gemini-3-pro open source?

No — gemini-3-pro is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.

Who developed gemini-3-pro?

gemini-3-pro was developed by Google, based in the United States.

When was gemini-3-pro released?

gemini-3-pro was publicly released on November 18, 2025.

How large is the context window of gemini-3-pro?

AI IQ hasn't verified an input context limit for gemini-3-pro from its developer's documentation, so none is listed rather than guessing.

How fast is gemini-3-pro?

In independent measurements, gemini-3-pro generates about 116 tokens per second, with a typical response time of about 34 seconds.

GoogleReleased Nov 18, 2025

Proprietary

gemini-3-pro

Strongest in Reliability (#34 of 177) and Academic Reasoning (#54 of 203); weakest in Abstract Reasoning (#95 of 201). Knowledge Work is estimated, because no results are published yet.

Composite IQ ?

114

#61 of 176 ranked models · ahead of 66%

Google's #8 model, behind Gemini 4 Argon (140)

Effective cost

$14.78/1M

$2 in · $12 out

Speed

116tok/s

34s typical response

Context

Unverified

Not in publisher docs

Evidence

6of 7 dims

20 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

91measured

#95 / 201

3/5

-35.5

Mathematical ReasoningMath

115measured

#73 / 176

4/5

-32

Academic ReasoningAcademic

128measured

#54 / 203

6/6

-7.5

Programmatic ReasoningCoding

114measured

#79 / 177

1/6

-35.5

Computer UseComputer Use

119measured

#56 / 176

1/5

-24

ReliabilityReliability

121measured

#34 / 177

5/6

-13

Knowledge WorkKnowledge Work

109estimated

#92 / 176

0/6

-22.5

gemini-3-pro95% range (model-based, uncalibrated)Top-10 median#1 in dimension100 = average human

Benchmark results

20 of 39 Composite IQ benchmarks have a published result for gemini-3-pro. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 91 · measuredBest: #31 of 76 on Chess Puzzles3/5

BenchmarkScorePercentileRankLeader · source

Chess Puzzles

Epoch AI vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 15

31.0%

#31 / 76

Leader gpt-6-astra · 72.0%
Epoch AI vEpoch 100-position leaderboard (task implementation versions recorded per run) · Oct 15

ARC-AGI-2

Full source leaderboard reconciliation · Oct 23

31.1%

#43 / 68

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

ARC-AGI-1

Full source leaderboard reconciliation · Oct 23

75.0%

#44 / 68

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

Not yet reported

ARC-AGI-3Mystery Game Puzzles

Mathematical Reasoning IQ 115 · measuredBest: #4 of 56 on AIME4/5

BenchmarkScorePercentileRankLeader · source

AIME

96.7%

#4 / 56

Leader gemini-3.1-pro · 98.1%

MathArena

Full source leaderboard reconciliation · Oct 28

20.1%

#38 / 64

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

FrontierMath Tier 4

Epoch AI FrontierMath Tier 4 v2 · Sep 22

18.8%

#45 / 72

Leader gpt-6.1-sol · 100%
Epoch AI FrontierMath Tier 4 v2 · Sep 22

FrontierMath Tier 1-3

Epoch AI FrontierMath Tiers 1-3 v2 · Sep 22

37.6%

#56 / 84

Leader gpt-6-astra · 93.7%
Epoch AI FrontierMath Tiers 1-3 v2 · Sep 22

Not yet reported

ProofBench 1.1

Academic Reasoning IQ 128 · measuredBest: #4 of 45 on MMLU-Pro6/6

BenchmarkScorePercentileRankLeader · source

MMLU-Pro

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

89.8%

#4 / 45

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

SciCode

Artificial Analysis model leaderboard · Sep 10

56.0%

#28 / 167

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

GPQA Diamond

Artificial Analysis v4.3.2 · Oct 27

90.8%

#41 / 147

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

MMMU-Pro

Artificial Analysis v4.3.2 · Oct 27

80.2%

#26 / 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

39.7%

#50 / 167

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

CritPt

Artificial Analysis v4.3.2 · Oct 27

9.1%

#66 / 159

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

Programmatic Reasoning IQ 114 · measuredBest: #10 of 61 on LiveCodeBench1/6

BenchmarkScorePercentileRankLeader · source

LiveCodeBench

Vals.ai · Aug 4

86.4%

#10 / 61

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

Not yet reported

IOI V2Terminal-Bench 4.0ProgramBenchSWE-rebenchMirrorCode

Computer Use IQ 119 · measuredBest: #21 of 32 on MCP Atlas1/5

BenchmarkScorePercentileRankLeader · source

MCP Atlas

Full source leaderboard reconciliation · Oct 23

70.3%

#21 / 32

Leader muse-spark-1.1 · 88.1%
Full source leaderboard reconciliation · Oct 23

Not yet reported

BrowseCompOSWorld-VerifiedArena.ai Agent ArenaAgents' Last Exam

Reliability IQ 121 · measuredBest: #5 of 80 on SimpleQA Verified5/6

BenchmarkScorePercentileRankLeader · source

SimpleQA Verified

Epoch AI SimpleQA Verified · Sep 22

72.9%

#5 / 80

Leader Gemini 4 Argon · 76.0%
Epoch AI SimpleQA Verified · Sep 22

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

15.3

#34 / 158

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

IFBench

Artificial Analysis v4.3.2 · Oct 27

70.4%

#44 / 96

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

AA Long Context Reasoning v1.1

Artificial Analysis v4.3.2 · Oct 27

76.0%

#82 / 154

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

BullshitBench v2

Full source leaderboard reconciliation · Oct 23

36.0%

#45 / 83

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

Not yet reported

FACTS Grounding

Knowledge Work IQ 109 · estimatedNo published results0/6

No published results yet for Knowledge Work. The 109 shown is estimated from gemini-3-pro'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: Nov 18, 2025
Developer: Google
Weights: ProprietaryHosted access only
API price: $2 in · $12 outper 1M tokens · full pricing

About this score

How much of gemini-3-pro's IQ is measured, and how the rest is estimated.

20/ 39benchmark results

6/ 7dimensions measured

1estimated

3/5Abstract

4/5Math

6/6Academic

1/6Coding

1/5Computer Use

5/6Reliability

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

Knowledge Work has no published results yet, so its IQ is estimated from gemini-3-pro's other dimensions. Missing benchmarks can also draw on its predecessor, Gemini 2.5 Pro; 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 gemini-3-pro

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

#1 overall

gpt-6.1-sol

IQ141 27 higherEffective cost$6.30 2.3× cheaper

Predecessor

gemini-2.5-pro

IQ99 15 lowerEffective cost$5.25 2.8× cheaper

IQ114 same IQEffective cost$4.70 3.1× cheaper

Similar price

gpt-5

IQ111 3 lowerEffective cost$14.22 about the same

gemini-3-proComparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about gemini-3-pro, 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 gemini-3-pro?: gemini-3-pro has an estimated IQ of 114, which ranks #61 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 gemini-3-pro best at?: Among the dimensions with published benchmark results, gemini-3-pro ranks highest in Reliability (IQ 121, #34 of 177) and Academic Reasoning (IQ 128, #54 of 203). Its lowest-ranked measured dimension is Abstract Reasoning (IQ 91, #95 of 201).
What is the EQ of gemini-3-pro?: gemini-3-pro has an estimated EQ of 116. EQ measures emotional reasoning — how well a model reads and responds to emotional context — and is scored separately from IQ.
Which benchmarks has gemini-3-pro been tested on?: gemini-3-pro has published results on 20 of the 39 benchmarks behind AI IQ's Composite IQ, including SimpleQA Verified, AIME, MMLU-Pro, LiveCodeBench and SciCode.
How much does gemini-3-pro cost?: gemini-3-pro costs $2.00 per million input tokens and $12.00 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $14.78 per million input-plus-output tokens.
Is gemini-3-pro open source?: No — gemini-3-pro is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed gemini-3-pro?: gemini-3-pro was developed by Google, based in the United States.
When was gemini-3-pro released?: gemini-3-pro was publicly released on November 18, 2025.
How large is the context window of gemini-3-pro?: AI IQ hasn't verified an input context limit for gemini-3-pro from its developer's documentation, so none is listed rather than guessing.
How fast is gemini-3-pro?: In independent measurements, gemini-3-pro generates about 116 tokens per second, with a typical response time of about 34 seconds.