Enter opens the highlighted result. Esc closes.

GPT-4o (2024-08-06) vs Muse Spark 1.3

Muse Spark 1.3 leads GPT-4o (2024-08-06) on the Artificial Analysis Intelligence Index, 48.1 to 7.7, and Muse Spark 1.3 costs 2.4x less per output token ($4.25 vs $10.00 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

GPT-4o (2024-08-06)OpenAI
Coding
No data
Overall
26.3
Output $/M
$10.00
0
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
37
vs boards won of 37 shared

GPT-4o (2024-08-06) or Muse Spark 1.3: which to pick

Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
37
GPT-4o (2024-08-06) only
21
Muse Spark 1.3 only
59
Like-for-like categories
6 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
GPT-4o (2024-08-06) not benchmarked, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Math, 59.2 points apart on average over 4 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4o (2024-08-06) 6.4% against Muse Spark 1.3 99.2%, 92.8 points apart on a 0 to 100 scale.
Output price
GPT-4o (2024-08-06) $10.00 against Muse Spark 1.3 $4.25 per million output tokens, 2.4x apart.
Context window
GPT-4o (2024-08-06) takes 128K tokens, Muse Spark 1.3 1.05M.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGPT-4o (2024-08-06)BarsMuse Spark 1.3Ties
Coding02
Intelligence01
Reasoning06
Math04
Knowledge04
General020
All shared boards037
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
Aider polyglot23.1%Not measuredOnly GPT-4o (2024-08-06) measured
SWE-bench Lite21.7%Not measuredOnly GPT-4o (2024-08-06) measured
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDevNot measured1659Only Muse Spark 1.3 measured
AA Coding IndexNot measured75.8Only Muse Spark 1.3 measured
Terminal-Bench 4 (Vals AI)Not measured10.6%Only Muse Spark 1.3 measured
Vibe Code Bench (Vals AI)Not measured82.9%Only Muse Spark 1.3 measured
Code migration (Vals AI)Not measured27.6%Only Muse Spark 1.3 measured
ProgramBench (Vals AI)Not measured0.5%Only Muse Spark 1.3 measured
IOI (Vals AI)Not measured43.9%Only Muse Spark 1.3 measured
Terminal-Bench 2.1 (Vals AI)Not measured72.3%Only Muse Spark 1.3 measured
CyberBench (Vals AI)Not measured69.4%Only Muse Spark 1.3 measured
LiveCodeBench (Artificial Analysis run)31.7%Not measuredOnly GPT-4o (2024-08-06) measured
SciCodeNot measured59.7%Only Muse Spark 1.3 measured
Terminal-Bench Hard (Artificial Analysis run)8.3%Not measuredOnly GPT-4o (2024-08-06) measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
ALE-BenchNot measured1688.3Only Muse Spark 1.3 measured
LMArena Text: coding12831510Muse Spark 1.3
LMArena Text: software and IT12781511Muse Spark 1.3
LMArena WebDev: ReactNot measured1672Only Muse Spark 1.3 measured
LMArena WebDev: HTMLNot measured1653Only Muse Spark 1.3 measured
LMArena WebDev: from an imageNot measured1640Only Muse Spark 1.3 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
AA Intelligence Index7.748.1Muse Spark 1.3
Epoch Capabilities IndexNot measured157.2Only Muse Spark 1.3 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
Agentic work benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
AA Agentic IndexNot measured55.5Only Muse Spark 1.3 measured
Design Arena: agents building web appsNot measured1297Only Muse Spark 1.3 measured
Design Arena: agents building full-stack appsNot measured1295Only Muse Spark 1.3 measured
Design Arena: agents building mobile appsNot measured1217Only Muse Spark 1.3 measured
Design Arena: agents building Godot gamesNot measured1241Only Muse Spark 1.3 measured
Design Arena: PowerPoint slidesNot measured1217Only Muse Spark 1.3 measured
Design Arena: spreadsheetsNot measured1075Only Muse Spark 1.3 measured
LiveBench researchNot measured68.6%Only Muse Spark 1.3 measured
LiveBench browserNot measured80.0%Only Muse Spark 1.3 measured
LiveBench long agenticNot measured40.4%Only Muse Spark 1.3 measured
Finance Agent (Vals AI)Not measured58.9%Only Muse Spark 1.3 measured
Tax Agent Bench (Vals AI)Not measured36.0%Only Muse Spark 1.3 measured
Legal Research Bench (Vals AI)Not measured40.9%Only Muse Spark 1.3 measured
Excel Modeling Benchmark (Vals AI)Not measured62.7%Only Muse Spark 1.3 measured
Terminal-Bench-Science (Vals AI)Not measured4.3%Only Muse Spark 1.3 measured
τ²-Bench Telecom28.9%Not measuredOnly GPT-4o (2024-08-06) measured
APEX-AgentsNot measured58.6%Only Muse Spark 1.3 measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
MMMU Pro (Vals AI)64.0%Not measuredOnly GPT-4o (2024-08-06) measured
GPQA Diamond (Artificial Analysis run)52.1%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)2.3%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)49.2%Not measuredOnly GPT-4o (2024-08-06) measured
SimpleBench17.8%Not measuredOnly GPT-4o (2024-08-06) measured
Chess puzzles6.0%37.0%Muse Spark 1.3
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
LMArena Text: hard prompts12641503Muse Spark 1.3
LMArena Text: expert12411519Muse Spark 1.3
LMArena Text: hard prompts in English12771500Muse Spark 1.3
LMArena Vision: diagramsNot measured1330Only Muse Spark 1.3 measured
LMArena Vision: homeworkNot measured1296Only Muse Spark 1.3 measured
Humanity's Last Exam (Scale run)Not measured25.4%Only Muse Spark 1.3 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
AIME14.0%Not measuredOnly GPT-4o (2024-08-06) measured
MATH 500 (Vals AI)75.2%Not measuredOnly GPT-4o (2024-08-06) measured
MGSM (Vals AI)90.7%Not measuredOnly GPT-4o (2024-08-06) measured
OTIS Mock AIME6.4%99.2%Muse Spark 1.3
FrontierMath, tiers 1 to 30.4%74.4%Muse Spark 1.3
FrontierMath, tier 4Not measured46.3%Only Muse Spark 1.3 measured
ProofBenchNot measured58.0%Only Muse Spark 1.3 measured
MATH level 553.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: math12851497Muse Spark 1.3
LMArena Text: mathematical work12831491Muse Spark 1.3
MathArenaNot measured43.0%Only Muse Spark 1.3 measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
MMLU Pro74.1%Not measuredOnly GPT-4o (2024-08-06) measured
LegalBench (Vals AI)80.1%Not measuredOnly GPT-4o (2024-08-06) measured
CorpFin (Vals AI)39.4%Not measuredOnly GPT-4o (2024-08-06) measured
TaxEval (Vals AI)71.1%Not measuredOnly GPT-4o (2024-08-06) measured
MortgageTax (Vals AI)61.0%Not measuredOnly GPT-4o (2024-08-06) measured
MedQA (Vals AI)88.2%Not measuredOnly GPT-4o (2024-08-06) measured
SimpleQA Verified26.0%Not measuredOnly GPT-4o (2024-08-06) measured
MMLU84.3%Not measuredOnly GPT-4o (2024-08-06) measured
LMArena Text: science12741507Muse Spark 1.3
LMArena Text: medicine and healthcare12521493Muse Spark 1.3
LMArena Text: legal and government12751499Muse Spark 1.3
LMArena Text: business and finance12321490Muse Spark 1.3
PRBench FinanceNot measured59.5%Only Muse Spark 1.3 measured
PRBench LegalNot measured61.6%Only Muse Spark 1.3 measured
Neither model has a result on the other 6 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
Design Arena: websitesNot measured1356Only Muse Spark 1.3 measured
Design Arena: UI componentsNot measured1350Only Muse Spark 1.3 measured
Design Arena: game devNot measured1328Only Muse Spark 1.3 measured
Design Arena: data vizNot measured1344Only Muse Spark 1.3 measured
Design Arena: 3DNot measured1358Only Muse Spark 1.3 measured
Design Arena: all code categoriesNot measured1352Only Muse Spark 1.3 measured
Design Arena: SVGNot measured1301Only Muse Spark 1.3 measured
Design Arena: ASCII artNot measured1283Only Muse Spark 1.3 measured
LiveBench designNot measured74.8%Only Muse Spark 1.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index020
General benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
IFBench36.0%Not measuredOnly GPT-4o (2024-08-06) measured
Long context reasoning (AA-LCR)41.0%83.0%Muse Spark 1.3
DTBenchNot measured96.5%Only Muse Spark 1.3 measured
LMCANot measured53.9%Only Muse Spark 1.3 measured
LMArena Text12831490Muse Spark 1.3
LMArena Text: instruction following12671479Muse Spark 1.3
LMArena Text: creative writing12741462Muse Spark 1.3
LMArena Vision10651308Muse Spark 1.3
LMArena Text: English12971495Muse Spark 1.3
LMArena Text: non-English12621481Muse Spark 1.3
LMArena Text: Chinese12541532Muse Spark 1.3
LMArena Text: German12571513Muse Spark 1.3
LMArena Text: Japanese12341470Muse Spark 1.3
LMArena Text: Korean12181490Muse Spark 1.3
LMArena Text: French12631511Muse Spark 1.3
LMArena Text: Spanish12691496Muse Spark 1.3
LMArena Text: Russian12721491Muse Spark 1.3
LMArena Text: PolishNot measured1490Only Muse Spark 1.3 measured
LMArena Text: multi-turn12791487Muse Spark 1.3
LMArena Text: longer queries12831488Muse Spark 1.3
LMArena Text: writing and language12901470Muse Spark 1.3
LMArena Text: entertainment and media12671457Muse Spark 1.3
LMArena Vision: English10721298Muse Spark 1.3
LMArena Vision: Chinese10091384Muse Spark 1.3
LMArena Vision: reading textNot measured1319Only Muse Spark 1.3 measured
LMArena Vision: humorNot measured1293Only Muse Spark 1.3 measured
LMArena Vision: creative writingNot measured1296Only Muse Spark 1.3 measured
Neither model has a result on the other 20 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4o (2024-08-06) and Muse Spark 1.3
BenchmarkGPT-4o (2024-08-06)Muse Spark 1.3Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

GPT-4o (2024-08-06)$0.0075Fits in one request
Muse Spark 1.3$0.0034Fits in one request

Muse Spark 1.3 costs less

Repository review

50K input + 3K output tokens

GPT-4o (2024-08-06)$0.155Fits in one request
Muse Spark 1.3$0.075Fits in one request

Muse Spark 1.3 costs less

Agent loop

200K input + 10K output tokens

GPT-4o (2024-08-06)$0.600Exceeds the context window
Muse Spark 1.3$0.292Fits in one request

Muse Spark 1.3 costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of GPT-4o (2024-08-06) and Muse Spark 1.3
SpecificationOpenAI GPT-4o (2024-08-06)Meta Muse Spark 1.3
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedAugust 6, 2024September 2, 2026
Context window128K1.05M
Input $/Mtok$2.50$1.25
Output $/Mtok$10.00$4.25
Coding indexNot benchmarked57.4
Independent measurements behind it04
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4o (2024-08-06) better than Muse Spark 1.3 for coding?

Only Muse Spark 1.3 has a coding score, 57.4 on the Vibe Coding Index; GPT-4o (2024-08-06) has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4o (2024-08-06) or Muse Spark 1.3?

GPT-4o (2024-08-06) costs $2.50 per million input tokens and $10.00 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for neither of them.

Which has the bigger context window, GPT-4o (2024-08-06) or Muse Spark 1.3?

Muse Spark 1.3, with 1.05M tokens against 128K.

How many benchmarks is the GPT-4o (2024-08-06) vs Muse Spark 1.3 comparison based on?

37 benchmarks have a result for both models as of October 22, 2026. GPT-4o (2024-08-06)'s coding index rests on 0 independent benchmarks and Muse Spark 1.3's on 4. Where only one model has a result, the page says so instead of naming a winner.

Compare next