What is the IQ of mercury-2?

mercury-2 has an estimated IQ of 93, which ranks #156 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 mercury-2 best at?

Among the dimensions with published benchmark results, mercury-2 ranks highest in Academic Reasoning (IQ 111, #135 of 203) and Knowledge Work (IQ 98, #123 of 176). Its lowest-ranked measured dimension is Reliability (IQ 102, #139 of 177).

What is the EQ of mercury-2?

mercury-2 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 mercury-2. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.

Which benchmarks has mercury-2 been tested on?

mercury-2 has published results on 12 of the 39 benchmarks behind AI IQ's Composite IQ, including IFBench, Humanity's Last Exam, CritPt, GPQA Diamond and SciCode.

How much does mercury-2 cost?

mercury-2 costs $0.25 per million input tokens and $0.75 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.631 per million input-plus-output tokens.

Is mercury-2 open source?

No — mercury-2 is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.

Who developed mercury-2?

mercury-2 was developed by Inception, based in the United States.

When was mercury-2 released?

mercury-2 was publicly released on February 24, 2026.

How large is the context window of mercury-2?

mercury-2 supports a context window of 128,000 tokens — the amount of text it can consider in a single request.

How fast is mercury-2?

In independent measurements, mercury-2 generates about 508 tokens per second, with a typical response time of about 8.1 seconds.

InceptionReleased Feb 24, 2026

Proprietary

mercury-2

Its best results are in Academic Reasoning (#135 of 203) and Knowledge Work (#123 of 176); weakest in Reliability (#139 of 177). Three of seven dimensions are estimated, because no results are published yet.

Composite IQ ?

#156 of 176 ranked models · ahead of 11%

US (Other)'s #17 model, behind Beam (114)

Effective cost

$0.631/1M

$0.25 in · $0.75 out

Speed

508tok/s

8s typical response

Context

128Ktokens

128,000 tokens in

Evidence

4of 7 dims

12 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

77estimated

#177 / 201

0/5

-49.5

Mathematical ReasoningMath

87estimated

#160 / 176

0/5

-60

Academic ReasoningAcademic

111measured

#135 / 203

4/6

-24.5

Programmatic ReasoningCoding

99measured

#138 / 177

1/6

-50.5

Computer UseComputer Use

75estimated

#156 / 176

0/5

-68

ReliabilityReliability

102measured

#139 / 177

3/6

-32

Knowledge WorkKnowledge Work

98measured

#123 / 176

4/6

-33.5

mercury-295% range (model-based, uncalibrated)Top-10 median#1 in dimension100 = average human

Benchmark results

12 of 39 Composite IQ benchmarks have a published result for mercury-2. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 77 · estimatedNo published results0/5

No published results yet for Abstract Reasoning. The 77 shown is estimated from mercury-2's other dimensions and will be replaced as results come in. How estimates work

ARC-AGI-3ARC-AGI-2ARC-AGI-1Chess PuzzlesMystery Game Puzzles

Mathematical Reasoning IQ 87 · estimatedNo published results0/5

No published results yet for Mathematical Reasoning. The 87 shown is estimated from mercury-2's other dimensions and will be replaced as results come in. How estimates work

FrontierMath Tier 4FrontierMath Tier 1-3ProofBench 1.1MathArenaAIME

Academic Reasoning IQ 111 · measuredBest: #125 of 167 on Humanity's Last Exam4/6

BenchmarkScorePercentileRankLeader · source

Humanity's Last Exam

Artificial Analysis v4.3.2 · Oct 27

17.1%

#125 / 167

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

CritPt

Artificial Analysis v4.3.2 · Oct 27

0.8%

#121 / 159

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

GPQA Diamond

Artificial Analysis v4.3.2 · Oct 27

77.0%

#112 / 147

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

SciCode

Artificial Analysis v4.3.2 · Oct 27

37.7%

#135 / 167

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

Not yet reported

MMLU-ProMMMU-Pro

Programmatic Reasoning IQ 99 · measuredBest: #89 of 104 on Terminal-Bench 4.01/6

BenchmarkScorePercentileRankLeader · source

Terminal-Bench 4.0

Artificial Analysis v4.3.2 · Oct 27

0.0%

#89 / 104

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

Not yet reported

LiveCodeBenchIOI V2ProgramBenchSWE-rebenchMirrorCode

Computer Use IQ 75 · estimatedNo published results0/5

No published results yet for Computer Use. The 75 shown is estimated from mercury-2's other dimensions and will be replaced as results come in. How estimates work

BrowseCompOSWorld-VerifiedMCP AtlasArena.ai Agent ArenaAgents' Last Exam

Reliability IQ 102 · measuredBest: #48 of 96 on IFBench3/6

BenchmarkScorePercentileRankLeader · source

IFBench

Artificial Analysis v4.3.2 · Oct 27

69.8%

#48 / 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

43.7%

#142 / 154

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

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

-50.7

#148 / 158

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

Not yet reported

SimpleQA VerifiedBullshitBench v2FACTS Grounding

Knowledge Work IQ 98 · measuredBest: #88 of 106 on GDP.pdf4/6

BenchmarkScorePercentileRankLeader · source

GDP.pdf

Artificial Analysis v4.3.2 · Oct 27

3.8%

#88 / 106

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

AutomationBench-AA

Artificial Analysis v4.3.2 · Oct 27

1.7%

#92 / 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

265.1

#100 / 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

0.0%

#116 / 124

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

Not yet reported

AA-AnalystAgentEnterpriseOps-Gym-AA

Release & availability

Release details on record for this model.

Released: Feb 24, 2026
Developer: Inception
Weights: ProprietaryHosted access only
Context: 128,000 tokens
API price: $0.25 in · $0.75 outper 1M tokens · full pricing

About this score

How much of mercury-2's IQ is measured, and how the rest is estimated.

12/ 39benchmark results

4/ 7dimensions measured

3estimated

0/5Abstract

0/5Math

4/6Academic

1/6Coding

0/5Computer Use

3/6Reliability

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.

Estimates fill the gaps

Abstract Reasoning, Mathematical Reasoning and Computer Use have no published results yet, so their IQ is estimated from mercury-2'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 mercury-2

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mercury-2Comparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about mercury-2, 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 mercury-2?: mercury-2 has an estimated IQ of 93, which ranks #156 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 mercury-2 best at?: Among the dimensions with published benchmark results, mercury-2 ranks highest in Academic Reasoning (IQ 111, #135 of 203) and Knowledge Work (IQ 98, #123 of 176). Its lowest-ranked measured dimension is Reliability (IQ 102, #139 of 177).
What is the EQ of mercury-2?: mercury-2 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 mercury-2. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.
Which benchmarks has mercury-2 been tested on?: mercury-2 has published results on 12 of the 39 benchmarks behind AI IQ's Composite IQ, including IFBench, Humanity's Last Exam, CritPt, GPQA Diamond and SciCode.
How much does mercury-2 cost?: mercury-2 costs $0.25 per million input tokens and $0.75 per million output tokens. Adjusted for how many tokens it actually consumes on real tasks, its effective cost works out to $0.631 per million input-plus-output tokens.
Is mercury-2 open source?: No — mercury-2 is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed mercury-2?: mercury-2 was developed by Inception, based in the United States.
When was mercury-2 released?: mercury-2 was publicly released on February 24, 2026.
How large is the context window of mercury-2?: mercury-2 supports a context window of 128,000 tokens — the amount of text it can consider in a single request.
How fast is mercury-2?: In independent measurements, mercury-2 generates about 508 tokens per second, with a typical response time of about 8.1 seconds.