What is the IQ of muse-spark?

muse-spark has an estimated IQ of 114, which ranks #65 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 muse-spark best at?

Among the dimensions with published benchmark results, muse-spark ranks highest in Reliability (IQ 123, #31 of 177) and Computer Use (IQ 125, #33 of 176). Its lowest-ranked measured dimension is Knowledge Work (IQ 113, #77 of 176).

What is the EQ of muse-spark?

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

Which benchmarks has muse-spark been tested on?

muse-spark has published results on 15 of the 39 benchmarks behind AI IQ's Composite IQ, including AIME, SimpleQA Verified, IFBench, MMMU-Pro and Humanity's Last Exam.

How much does muse-spark cost?

muse-spark costs $0.00 per million input tokens and $0.00 per million output tokens. AI IQ does not yet have enough task-level token usage data to calculate its effective cost.

Is muse-spark open source?

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

Who developed muse-spark?

muse-spark was developed by Meta, based in the United States.

When was muse-spark released?

muse-spark was publicly released on April 8, 2026.

How large is the context window of muse-spark?

muse-spark supports a context window of 262,000 tokens — the amount of text it can consider in a single request.

How fast is muse-spark?

AI IQ doesn't have independent speed measurements for muse-spark yet. Speed comes from independent tests of a model's hosted API, which aren't available for every model — especially new, restricted-access, or self-hosted ones.

MetaReleased Apr 8, 2026

Proprietary

muse-spark

Strongest in Reliability (#31 of 177) and Computer Use (#33 of 176); weakest in Knowledge Work (#77 of 176). Abstract Reasoning and Programmatic Reasoning are estimated, because no results are published yet.

Composite IQ ?

114

#65 of 176 ranked models · ahead of 63%

Meta's #7 model, behind Muse Wonder Full (134)

Effective cost

Not priced

No standard API rate

Speed

Not measured

No speed data yet

Context

262Ktokens

262,000 tokens in

Evidence

5of 7 dims

15 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

88estimated

#114 / 201

0/5

-38.5

Mathematical ReasoningMath

118measured

#67 / 176

3/5

-29

Academic ReasoningAcademic

129measured

#51 / 203

5/6

-6.5

Programmatic ReasoningCoding

104estimated

#107 / 177

0/6

-45.5

Computer UseComputer Use

125measured

#33 / 176

1/5

-18

ReliabilityReliability

123measured

#31 / 177

4/6

-11

Knowledge WorkKnowledge Work

113measured

#77 / 176

2/6

-18.5

muse-spark95% range (model-based, uncalibrated)Top-10 median#1 in dimension100 = average human

Benchmark results

15 of 39 Composite IQ benchmarks have a published result for muse-spark. Benchmarks without a result stay listed so gaps are visible.

Abstract Reasoning IQ 88 · estimatedNo published results0/5

No published results yet for Abstract Reasoning. The 88 shown is estimated from muse-spark'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 118 · measuredBest: #3 of 56 on AIME3/5

BenchmarkScorePercentileRankLeader · source

AIME

96.9%

#3 / 56

Leader gemini-3.1-pro · 98.1%

FrontierMath Tier 1-3

Epoch AI FrontierMath Tiers 1-3 v2 · Sep 22

39.0%

#54 / 84

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

FrontierMath Tier 4

Epoch AI FrontierMath Tier 4 v2 · Sep 22

14.6%

#52 / 72

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

Not yet reported

ProofBench 1.1MathArena

Academic Reasoning IQ 129 · measuredBest: #23 of 89 on MMMU-Pro5/6

BenchmarkScorePercentileRankLeader · source

MMMU-Pro

Artificial Analysis v4.3.2 · Oct 27

80.5%

#23 / 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

40.7%

#46 / 167

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

SciCode

Artificial Analysis model leaderboard · Sep 10

52.0%

#52 / 167

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

CritPt

Artificial Analysis v4.3.2 · Oct 27

11.3%

#54 / 159

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

GPQA Diamond

Artificial Analysis v4.3.2 · Oct 27

88.4%

#59 / 147

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

Not yet reported

MMLU-Pro

Programmatic Reasoning IQ 104 · estimatedNo published results0/6

No published results yet for Programmatic Reasoning. The 104 shown is estimated from muse-spark's other dimensions and will be replaced as results come in. How estimates work

LiveCodeBenchIOI V2Terminal-Bench 4.0ProgramBenchSWE-rebenchMirrorCode

Computer Use IQ 125 · measuredBest: #9 of 32 on MCP Atlas1/5

BenchmarkScorePercentileRankLeader · source

MCP Atlas

Full source leaderboard reconciliation · Oct 23

82.2%

#9 / 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 123 · measuredBest: #13 of 80 on SimpleQA Verified4/6

BenchmarkScorePercentileRankLeader · source

SimpleQA Verified

Epoch AI SimpleQA Verified · Sep 22

66.3%

#13 / 80

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

IFBench

Artificial Analysis v4.3.2 · Oct 27

75.9%

#20 / 96

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

AA Omniscience

Artificial Analysis v4.3.2 · Oct 27

7.2

#49 / 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

78.0%

#71 / 154

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

Not yet reported

BullshitBench v2FACTS Grounding

Knowledge Work IQ 113 · measuredBest: #71 of 124 on GDPval-AA v2.1 normalized score2/6

BenchmarkScorePercentileRankLeader · source

GDPval-AA v2.1 normalized score

Artificial Analysis v4.3.2 · Oct 20

24.9%

#71 / 124

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

AA-Briefcase v1.1 Elo

Artificial Analysis v4.3.2 · Oct 27

645

#83 / 111

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

Not yet reported

AutomationBench-AAGDP.pdfAA-AnalystAgentEnterpriseOps-Gym-AA

Release & availability

Release details on record for this model.

Released: Apr 8, 2026
Developer: Meta
Weights: ProprietaryHosted access only
Context: 262,000 tokens
API price: $0 in · $0 outper 1M tokens · full pricing

About this score

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

15/ 39benchmark results

5/ 7dimensions measured

2estimated

0/5Abstract

3/5Math

5/6Academic

0/6Coding

1/5Computer Use

4/6Reliability

2/6Knowledge 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 and Programmatic Reasoning have no published results yet, so their IQ is estimated from muse-spark'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 muse-spark

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

IQ114 same IQEffective cost$14.78

#2 overall

opus-5.5

IQ141 27 higherEffective cost$35.73

#3 overall

Gemini 4 Argon

IQ140 26 higher

muse-sparkComparison model

Compare with any modelBrowse all comparisons →

Frequently asked questions

Quick answers about muse-spark, 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 muse-spark?: muse-spark has an estimated IQ of 114, which ranks #65 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 muse-spark best at?: Among the dimensions with published benchmark results, muse-spark ranks highest in Reliability (IQ 123, #31 of 177) and Computer Use (IQ 125, #33 of 176). Its lowest-ranked measured dimension is Knowledge Work (IQ 113, #77 of 176).
What is the EQ of muse-spark?: muse-spark 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 muse-spark. AI IQ doesn't estimate EQ from other benchmarks, so the score appears once one of those results is published.
Which benchmarks has muse-spark been tested on?: muse-spark has published results on 15 of the 39 benchmarks behind AI IQ's Composite IQ, including AIME, SimpleQA Verified, IFBench, MMMU-Pro and Humanity's Last Exam.
How much does muse-spark cost?: muse-spark costs $0.00 per million input tokens and $0.00 per million output tokens. AI IQ does not yet have enough task-level token usage data to calculate its effective cost.
Is muse-spark open source?: No — muse-spark is a proprietary model. Its weights are not publicly available, so it is used through hosted APIs and products.
Who developed muse-spark?: muse-spark was developed by Meta, based in the United States.
When was muse-spark released?: muse-spark was publicly released on April 8, 2026.
How large is the context window of muse-spark?: muse-spark supports a context window of 262,000 tokens — the amount of text it can consider in a single request.
How fast is muse-spark?: AI IQ doesn't have independent speed measurements for muse-spark yet. Speed comes from independent tests of a model's hosted API, which aren't available for every model — especially new, restricted-access, or self-hosted ones.