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GPT-4 vs Muse Spark 1.3

Muse Spark 1.3 leads GPT-4 on the Artificial Analysis Intelligence Index, 48.1 to 6.7, and Muse Spark 1.3 costs 14.1x less per output token ($4.25 vs $60.00 per million). Updated October 21, 2026; 34 benchmarks have a result for both.

Replace GPT-4 Replace Muse Spark 1.3
GPT-4OpenAI
Coding
No data
Overall
No data
Output $/M
$60.00
0
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
34
vs boards won of 34 shared

GPT-4 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-4 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGPT-4OpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
34
GPT-4 only
11
Muse Spark 1.3 only
58
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 1.3 57.4 from 4 benchmarks.
Widest category
Knowledge, 55.4 points apart on average over 4 shared benchmarks.
Widest single gap
LMArena Text: Korean: GPT-4 1087 against Muse Spark 1.3 1490, 67.2 points apart on a 0 to 100 scale.
Output price
GPT-4 $60.00 against Muse Spark 1.3 $4.25 per million output tokens, 14.1x apart.
Context window
GPT-4 takes 8K 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-4BarsMuse Spark 1.3Ties
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 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
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
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDevNot measured1659Only Muse Spark 1.3 measured
AA Coding Index13.175.8Muse Spark 1.3
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
SciCodeNot measured59.7%Only Muse Spark 1.3 measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
ALE-BenchNot measured1688.3Only Muse Spark 1.3 measured
LMArena Text: coding12091510Muse Spark 1.3
LMArena Text: software and IT11951511Muse 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 18 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
AA Intelligence Index6.748.1Muse Spark 1.3
Epoch Capabilities Index125.7157.2Muse Spark 1.3
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index16 boards, none shared
Agentic work benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse 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 measured1243Only Muse Spark 1.3 measured
Design Arena: spreadsheetsNot measured1043Only 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
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 index04
Reasoning benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
GPQA Diamond (Artificial Analysis run)34.9%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)Not measured48.7%Only Muse Spark 1.3 measured
Chess puzzlesNot measured37.0%Only Muse Spark 1.3 measured
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
BIG-Bench Hard75.1%Not measuredOnly GPT-4 measured
LMArena Text: hard prompts12001503Muse Spark 1.3
LMArena Text: expert11491519Muse Spark 1.3
LMArena Text: hard prompts in English12091500Muse Spark 1.3
LMArena Vision: diagramsNot measured1330Only Muse Spark 1.3 measured
LMArena Vision: homeworkNot measured1296Only Muse Spark 1.3 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 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
OTIS Mock AIMENot measured99.2%Only Muse Spark 1.3 measured
FrontierMath, tiers 1 to 3Not measured74.4%Only Muse Spark 1.3 measured
FrontierMath, tier 4Not measured46.3%Only Muse Spark 1.3 measured
ProofBenchNot measured58.0%Only Muse Spark 1.3 measured
GSM8K92.0%Not measuredOnly GPT-4 measured
LMArena Text: math12301497Muse Spark 1.3
LMArena Text: mathematical work12281491Muse Spark 1.3
Neither model has a result on the other 6 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
MMLU Pro (Artificial Analysis run)56.2%Not measuredOnly GPT-4 measured
MMLU86.4%Not measuredOnly GPT-4 measured
AI2 Reasoning Challenge96.3%Not measuredOnly GPT-4 measured
LMArena Text: science11771507Muse Spark 1.3
LMArena Text: medicine and healthcare11451493Muse Spark 1.3
LMArena Text: legal and government11911499Muse Spark 1.3
LMArena Text: business and finance11451490Muse Spark 1.3
Neither model has a result on the other 11 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index9 boards, none shared
Web design benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
Design Arena: websitesNot measured1356Only Muse Spark 1.3 measured
Design Arena: UI componentsNot measured1351Only Muse Spark 1.3 measured
Design Arena: game devNot measured1329Only Muse Spark 1.3 measured
Design Arena: data vizNot measured1343Only Muse Spark 1.3 measured
Design Arena: 3DNot measured1359Only Muse Spark 1.3 measured
Design Arena: all code categoriesNot measured1353Only Muse Spark 1.3 measured
Design Arena: SVGNot measured1301Only Muse Spark 1.3 measured
Design Arena: ASCII artNot measured1280Only 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 index019
General benchmarks for GPT-4 and Muse Spark 1.3
BenchmarkGPT-4Muse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
IFBench33.2%Not measuredOnly GPT-4 measured
Long context reasoning (AA-LCR)Not measured83.0%Only Muse Spark 1.3 measured
DTBench62.7%96.5%Muse Spark 1.3
LMCA17.1%53.9%Muse Spark 1.3
HellaSwag95.3%Not measuredOnly GPT-4 measured
WinoGrande87.5%Not measuredOnly GPT-4 measured
LMArena Text12061490Muse Spark 1.3
LMArena Text: instruction following12011479Muse Spark 1.3
LMArena Text: creative writing11911462Muse Spark 1.3
LMArena VisionNot measured1308Only Muse Spark 1.3 measured
LMArena Text: English12201495Muse Spark 1.3
LMArena Text: non-English11941481Muse Spark 1.3
LMArena Text: Chinese11841532Muse Spark 1.3
LMArena Text: German11981513Muse Spark 1.3
LMArena Text: Japanese11371470Muse Spark 1.3
LMArena Text: Korean10871490Muse Spark 1.3
LMArena Text: French12201511Muse Spark 1.3
LMArena Text: Spanish11971496Muse Spark 1.3
LMArena Text: Russian11951491Muse Spark 1.3
LMArena Text: Polish12651490Muse Spark 1.3
LMArena Text: multi-turn12061487Muse Spark 1.3
LMArena Text: longer queries11901488Muse Spark 1.3
LMArena Text: writing and language12191470Muse Spark 1.3
LMArena Text: entertainment and media11841457Muse Spark 1.3
LMArena Vision: EnglishNot measured1298Only Muse Spark 1.3 measured
LMArena Vision: ChineseNot measured1384Only Muse Spark 1.3 measured
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 16 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 1.3
BenchmarkGPT-4Muse 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-4$0.060Fits 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-4$1.68Exceeds the context window
Muse Spark 1.3$0.075Fits in one request

Muse Spark 1.3 costs less

Agent loop

200K input + 10K output tokens

GPT-4$6.60Exceeds 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-4 and Muse Spark 1.3
SpecificationOpenAI GPT-4Meta Muse Spark 1.3
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedMay 28, 2023September 2, 2026
Context window8K1.05M
Input $/Mtok$30.00$1.25
Output $/Mtok$60.00$4.25
Coding indexNot benchmarked57.4
Independent measurements behind it04
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4 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-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 1.3?

GPT-4 costs $30.00 per million input tokens and $60.00 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-4 or Muse Spark 1.3?

Muse Spark 1.3, with 1.05M tokens against 8K.

How many benchmarks is the GPT-4 vs Muse Spark 1.3 comparison based on?

34 benchmarks have a result for both models as of October 21, 2026. GPT-4'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.

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