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GPT-4 vs Muse Spark 1.1

Muse Spark 1.1 leads GPT-4 on the Artificial Analysis Intelligence Index, 33.7 to 6.7, and Muse Spark 1.1 costs 14.1x less per output token ($4.25 vs $60.00 per million). Updated October 22, 2026; 34 benchmarks have a result for both.

GPT-4OpenAI
Coding
No data
Overall
No data
Output $/M
$60.00
0
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
34
vs boards won of 34 shared

GPT-4 or Muse Spark 1.1: which to pick

Only Muse Spark 1.1 has a coding score, 70.3 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Shared results
34
GPT-4 only
11
Muse Spark 1.1 only
62
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-4 not benchmarked, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category
Knowledge, 52.3 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: Korean: GPT-4 1087 against Muse Spark 1.1 1459, 62.0 points apart on a 0 to 100 scale.
Output price
GPT-4 $60.00 against Muse Spark 1.1 $4.25 per million output tokens, 14.1x apart.
Context window
GPT-4 takes 8K tokens, Muse Spark 1.1 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-4BarsMuse Spark 1.1Ties
Coding03
Intelligence02
Reasoning04
Math02
Knowledge04
General019
All shared boards034
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
SWE-bench Verified22.4%Not measuredOnly GPT-4 measured
SWE-bench Lite39.7%Not measuredOnly GPT-4 measured
SWE-bench (full test set)12.5%Not measuredOnly GPT-4 measured
LMArena WebDevNot measured1542Only Muse Spark 1.1 measured
AA Coding Index13.171.3Muse Spark 1.1
LiveCodeBench (Vals AI)Not measured85.9%Only Muse Spark 1.1 measured
SWE-bench Verified (Vals AI)Not measured82.0%Only Muse Spark 1.1 measured
Vibe Code Bench (Vals AI)Not measured72.2%Only Muse Spark 1.1 measured
Code migration (Vals AI)Not measured31.1%Only Muse Spark 1.1 measured
ProgramBench (Vals AI)Not measured0.0%Only Muse Spark 1.1 measured
Terminal-Bench 2.1 (Vals AI)Not measured69.3%Only Muse Spark 1.1 measured
SkillsBench (Vals AI)Not measured59.2%Only Muse Spark 1.1 measured
SciCodeNot measured58.8%Only Muse Spark 1.1 measured
LMArena Text: coding12091498Muse Spark 1.1
LMArena Text: software and IT11951498Muse Spark 1.1
LMArena WebDev: ReactNot measured1532Only Muse Spark 1.1 measured
LMArena WebDev: HTMLNot measured1540Only Muse Spark 1.1 measured
LMArena WebDev: from an imageNot measured1540Only Muse Spark 1.1 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
AA Intelligence Index6.733.7Muse Spark 1.1
Epoch Capabilities Index125.7154.1Muse Spark 1.1
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
Agentic work benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
AA Agentic IndexNot measured25.8Only Muse Spark 1.1 measured
Design Arena: agents building web appsNot measured1207Only Muse Spark 1.1 measured
Design Arena: agents building full-stack appsNot measured1199Only Muse Spark 1.1 measured
Design Arena: agents building mobile appsNot measured1175Only Muse Spark 1.1 measured
Design Arena: agents building Android appsNot measured1178Only Muse Spark 1.1 measured
Design Arena: agents building Godot gamesNot measured1103Only Muse Spark 1.1 measured
Design Arena: agents building gamesNot measured1183Only Muse Spark 1.1 measured
Design Arena: HTML slidesNot measured1195Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1155Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured1042Only Muse Spark 1.1 measured
Finance Agent (Vals AI)Not measured57.2%Only Muse Spark 1.1 measured
Legal Research Bench (Vals AI)Not measured38.0%Only Muse Spark 1.1 measured
Excel Modeling Benchmark (Vals AI)Not measured56.4%Only Muse Spark 1.1 measured
Time Horizon Index (Vals AI)Not measured1.7%Only Muse Spark 1.1 measured
APEX-AgentsNot measured31.8%Only Muse Spark 1.1 measured
Vending-Bench 2Not measured$6,520Only Muse Spark 1.1 measured
Neither model has a result on the other 25 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index04
Reasoning benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
GPQA DiamondNot measured91.2%Only Muse Spark 1.1 measured
MMMU Pro (Vals AI)Not measured86.6%Only Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)34.9%89.8%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)Not measured46.2%Only Muse Spark 1.1 measured
Chess puzzlesNot measured34.0%Only Muse Spark 1.1 measured
BIG-Bench Hard75.1%Not measuredOnly GPT-4 measured
LMArena Text: hard prompts12001485Muse Spark 1.1
LMArena Text: expert11491478Muse Spark 1.1
LMArena Text: hard prompts in English12091480Muse Spark 1.1
LMArena Vision: diagramsNot measured1305Only Muse Spark 1.1 measured
LMArena Vision: homeworkNot measured1287Only Muse Spark 1.1 measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
ProofBenchNot measured39.0%Only Muse Spark 1.1 measured
GSM8K92.0%Not measuredOnly GPT-4 measured
LMArena Text: math12301482Muse Spark 1.1
LMArena Text: mathematical work12281487Muse Spark 1.1
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
MMLU ProNot measured88.7%Only Muse Spark 1.1 measured
LegalBench (Vals AI)Not measured85.0%Only Muse Spark 1.1 measured
CorpFin (Vals AI)Not measured71.3%Only Muse Spark 1.1 measured
TaxEval (Vals AI)Not measured79.7%Only Muse Spark 1.1 measured
MortgageTax (Vals AI)Not measured66.1%Only Muse Spark 1.1 measured
MMLU Pro (Artificial Analysis run)56.2%Not measuredOnly GPT-4 measured
SimpleQA VerifiedNot measured57.8%Only Muse Spark 1.1 measured
MMLU86.4%Not measuredOnly GPT-4 measured
AI2 Reasoning Challenge96.3%Not measuredOnly GPT-4 measured
LMArena Text: science11771484Muse Spark 1.1
LMArena Text: medicine and healthcare11451479Muse Spark 1.1
LMArena Text: legal and government11911481Muse Spark 1.1
LMArena Text: business and finance11451470Muse Spark 1.1
Neither model has a result on the other 5 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
Design Arena: websitesNot measured1270Only Muse Spark 1.1 measured
Design Arena: UI componentsNot measured1289Only Muse Spark 1.1 measured
Design Arena: game devNot measured1269Only Muse Spark 1.1 measured
Design Arena: data vizNot measured1268Only Muse Spark 1.1 measured
Design Arena: 3DNot measured1260Only Muse Spark 1.1 measured
Design Arena: all code categoriesNot measured1276Only Muse Spark 1.1 measured
Design Arena: SVGNot measured1235Only Muse Spark 1.1 measured
Design Arena: ASCII artNot measured1271Only Muse Spark 1.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
Public Benefits Bench (Vals AI)Not measured61.3%Only Muse Spark 1.1 measured
SAGE (Vals AI)Not measured45.6%Only Muse Spark 1.1 measured
MedScribe (Vals AI)Not measured88.9%Only Muse Spark 1.1 measured
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
IFBench33.2%Not measuredOnly GPT-4 measured
Long context reasoning (AA-LCR)Not measured77.7%Only Muse Spark 1.1 measured
DTBench62.7%94.4%Muse Spark 1.1
LMCA17.1%49.9%Muse Spark 1.1
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
HellaSwag95.3%Not measuredOnly GPT-4 measured
WinoGrande87.5%Not measuredOnly GPT-4 measured
LMArena Text12061478Muse Spark 1.1
LMArena Text: instruction following12011457Muse Spark 1.1
LMArena Text: creative writing11911435Muse Spark 1.1
LMArena VisionNot measured1293Only Muse Spark 1.1 measured
LMArena Text: English12201478Muse Spark 1.1
LMArena Text: non-English11941471Muse Spark 1.1
LMArena Text: Chinese11841515Muse Spark 1.1
LMArena Text: German11981469Muse Spark 1.1
LMArena Text: Japanese11371450Muse Spark 1.1
LMArena Text: Korean10871459Muse Spark 1.1
LMArena Text: French12201492Muse Spark 1.1
LMArena Text: Spanish11971464Muse Spark 1.1
LMArena Text: Russian11951482Muse Spark 1.1
LMArena Text: Polish12651499Muse Spark 1.1
LMArena Text: multi-turn12061484Muse Spark 1.1
LMArena Text: longer queries11901462Muse Spark 1.1
LMArena Text: writing and language12191448Muse Spark 1.1
LMArena Text: entertainment and media11841438Muse Spark 1.1
LMArena Vision: EnglishNot measured1292Only Muse Spark 1.1 measured
LMArena Vision: ChineseNot measured1348Only Muse Spark 1.1 measured
LMArena Vision: reading textNot measured1301Only Muse Spark 1.1 measured
LMArena Vision: humorNot measured1288Only Muse Spark 1.1 measured
LMArena Vision: creative writingNot measured1253Only Muse Spark 1.1 measured
LMArena DocumentNot measured1465Only Muse Spark 1.1 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4 and Muse Spark 1.1
BenchmarkGPT-4Muse Spark 1.1Leader
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-4$0.060Fits in one request
Muse Spark 1.1$0.0034Fits in one request

Muse Spark 1.1 costs less

Repository review

50K input + 3K output tokens

GPT-4$1.68Exceeds the context window
Muse Spark 1.1$0.075Fits in one request

Muse Spark 1.1 costs less

Agent loop

200K input + 10K output tokens

GPT-4$6.60Exceeds the context window
Muse Spark 1.1$0.292Fits in one request

Muse Spark 1.1 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-4 and Muse Spark 1.1
SpecificationOpenAI GPT-4Meta Muse Spark 1.1
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedMay 28, 2023July 16, 2026
Context window8K1.05M
Input $/Mtok$30.00$1.25
Output $/Mtok$60.00$4.25
Coding indexNot benchmarked70.3
Independent measurements behind it03
Cost per solved taskNot computable$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 better than Muse Spark 1.1 for coding?

Only Muse Spark 1.1 has a coding score, 70.3 on the Vibe Coding Index; GPT-4 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4 or Muse Spark 1.1?

GPT-4 costs $30.00 per million input tokens and $60.00 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.1 only.

Which has the bigger context window, GPT-4 or Muse Spark 1.1?

Muse Spark 1.1, with 1.05M tokens against 8K.

How many benchmarks is the GPT-4 vs Muse Spark 1.1 comparison based on?

34 benchmarks have a result for both models as of October 22, 2026. GPT-4's coding index rests on 0 independent benchmarks and Muse Spark 1.1's on 3. Where only one model has a result, the page says so instead of naming a winner.

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