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GPT-4.1 vs Muse Spark 1.3

Muse Spark 1.3 leads GPT-4.1 on the Artificial Analysis Intelligence Index, 48.1 to 12.7, and Muse Spark 1.3 costs 1.9x less per output token ($4.25 vs $8.00 per million). Updated October 22, 2026; 53 benchmarks have a result for both.

Replace GPT-4.1 Replace Muse Spark 1.3
GPT-4.1OpenAI
Coding
No data
Overall
36.5
Output $/M
$8.00
0
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
53
vs boards won of 53 shared

GPT-4.1 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-4.1 has none, so the two cannot be ranked on coding.

Compare them on price, context and the boards below.

Model AGPT-4.1OpenAINot benchmarkedNo coding benchmark$0.37 per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
53
GPT-4.1 only
39
Muse Spark 1.3 only
39
Like-for-like categories
7 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-4.1 not benchmarked, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Math, 43.1 points apart on average over 4 shared benchmarks.
Widest single gap
FrontierMath, tiers 1 to 3: GPT-4.1 6.0% against Muse Spark 1.3 74.4%, 68.4 points apart on a 0 to 100 scale.
Output price
GPT-4.1 $8.00 against Muse Spark 1.3 $4.25 per million output tokens, 1.9x apart.
Context window
GPT-4.1 takes 1.05M 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-4.1BarsMuse Spark 1.3Ties
Coding03
Intelligence02
Reasoning08
Math04
Knowledge04
Web design06
General026
All shared boards053
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
Aider polyglot52.4%Not measuredOnly GPT-4.1 measured
SWE-bench Verified39.6%Not measuredOnly GPT-4.1 measured
SWE-bench Multimodal31.1%Not measuredOnly GPT-4.1 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
LiveCodeBench (Vals AI)54.7%Not measuredOnly GPT-4.1 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)45.7%Not measuredOnly GPT-4.1 measured
SciCodeNot measured59.7%Only Muse Spark 1.3 measured
Terminal-Bench Hard (Artificial Analysis run)13.6%Not measuredOnly GPT-4.1 measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
WeirdML39.0%Not measuredOnly GPT-4.1 measured
ALE-Bench558.11688.3Muse Spark 1.3
LMArena Text: coding13901510Muse Spark 1.3
LMArena Text: software and IT13911511Muse 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
SciCode4.6%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
AA Intelligence Index12.748.1Muse Spark 1.3
Epoch Capabilities Index136.7157.2Muse Spark 1.3
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse 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 measured1218Only Muse Spark 1.3 measured
Design Arena: agents building Godot gamesNot measured1241Only Muse Spark 1.3 measured
Design Arena: PowerPoint slidesNot measured1219Only Muse Spark 1.3 measured
Design Arena: spreadsheetsNot measured1062Only 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 Telecom47.1%Not measuredOnly GPT-4.1 measured
APEX-AgentsNot measured58.6%Only Muse Spark 1.3 measured
Berkeley Function Calling Leaderboard (BFCL)54.0%Not measuredOnly GPT-4.1 measured
BrowseComp-Plus36.4%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
GPQA Diamond65.4%Not measuredOnly GPT-4.1 measured
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
MMMU Pro (Vals AI)72.4%Not measuredOnly GPT-4.1 measured
GPQA Diamond (Artificial Analysis run)66.6%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)4.2%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)66.9%Not measuredOnly GPT-4.1 measured
ARC-AGI5.5%Not measuredOnly GPT-4.1 measured
ARC-AGI-20.4%Not measuredOnly GPT-4.1 measured
SimpleBench27.0%Not measuredOnly GPT-4.1 measured
Chess puzzles3.0%37.0%Muse Spark 1.3
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
LMArena Text: hard prompts13841503Muse Spark 1.3
LMArena Text: expert13641519Muse Spark 1.3
LMArena Text: hard prompts in English13931500Muse Spark 1.3
LMArena Vision: diagrams12151330Muse Spark 1.3
LMArena Vision: homework12481296Muse Spark 1.3
Kagi LLM Benchmark52.3%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
AIME39.6%Not measuredOnly GPT-4.1 measured
MATH 500 (Vals AI)87.2%Not measuredOnly GPT-4.1 measured
MGSM (Vals AI)87.7%Not measuredOnly GPT-4.1 measured
AA Math Index34.7Not measuredOnly GPT-4.1 measured
AIME 2025 (Artificial Analysis run)34.7%Not measuredOnly GPT-4.1 measured
OTIS Mock AIME38.3%99.2%Muse Spark 1.3
FrontierMath, tiers 1 to 36.0%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 583.0%Not measuredOnly GPT-4.1 measured
LMArena Text: math13691497Muse Spark 1.3
LMArena Text: mathematical work13601491Muse Spark 1.3
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
MMLU Pro80.5%Not measuredOnly GPT-4.1 measured
LegalBench (Vals AI)83.1%Not measuredOnly GPT-4.1 measured
CaseLaw (Vals AI)69.9%Not measuredOnly GPT-4.1 measured
CorpFin (Vals AI)63.0%Not measuredOnly GPT-4.1 measured
TaxEval (Vals AI)75.1%Not measuredOnly GPT-4.1 measured
MortgageTax (Vals AI)65.9%Not measuredOnly GPT-4.1 measured
MedQA (Vals AI)91.2%Not measuredOnly GPT-4.1 measured
MMLU Pro (Artificial Analysis run)80.6%Not measuredOnly GPT-4.1 measured
SimpleQA Verified31.1%Not measuredOnly GPT-4.1 measured
GeoBench72.0%Not measuredOnly GPT-4.1 measured
LMArena Text: science13821507Muse Spark 1.3
LMArena Text: medicine and healthcare13791493Muse Spark 1.3
LMArena Text: legal and government13991499Muse Spark 1.3
LMArena Text: business and finance13691490Muse Spark 1.3
FACTS Benchmark Suite45.8%Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
Design Arena: websites10381356Muse Spark 1.3
Design Arena: UI components9971349Muse Spark 1.3
Design Arena: game dev10791328Muse Spark 1.3
Design Arena: data viz11041343Muse Spark 1.3
Design Arena: 3D8491358Muse Spark 1.3
Design Arena: all code categories10251352Muse Spark 1.3
Design Arena: SVGNot measured1301Only Muse Spark 1.3 measured
Design Arena: ASCII artNot measured1278Only 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 index026
General benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
IFBench43.0%Not measuredOnly GPT-4.1 measured
Long context reasoning (AA-LCR)68.3%83.0%Muse Spark 1.3
DTBench68.3%96.5%Muse Spark 1.3
LMCA25.6%53.9%Muse Spark 1.3
Fiction.LiveBench63.9%Not measuredOnly GPT-4.1 measured
LMArena Text13831490Muse Spark 1.3
LMArena Text: instruction following13671479Muse Spark 1.3
LMArena Text: creative writing13631462Muse Spark 1.3
LMArena Vision12101308Muse Spark 1.3
LMArena Text: English13921495Muse Spark 1.3
LMArena Text: non-English13701481Muse Spark 1.3
LMArena Text: Chinese13821532Muse Spark 1.3
LMArena Text: German13811513Muse Spark 1.3
LMArena Text: Japanese13191470Muse Spark 1.3
LMArena Text: Korean13381490Muse Spark 1.3
LMArena Text: French13821511Muse Spark 1.3
LMArena Text: Spanish13761496Muse Spark 1.3
LMArena Text: Russian13771491Muse Spark 1.3
LMArena Text: Polish13891490Muse Spark 1.3
LMArena Text: multi-turn13971487Muse Spark 1.3
LMArena Text: longer queries13851488Muse Spark 1.3
LMArena Text: writing and language13711470Muse Spark 1.3
LMArena Text: entertainment and media13651457Muse Spark 1.3
LMArena Vision: English12091298Muse Spark 1.3
LMArena Vision: Chinese12261384Muse Spark 1.3
LMArena Vision: reading text12181319Muse Spark 1.3
LMArena Vision: humor11961293Muse Spark 1.3
LMArena Vision: captioning1207Not measuredOnly GPT-4.1 measured
LMArena Vision: recognizing things1208Not measuredOnly GPT-4.1 measured
LMArena Vision: creative writing12101296Muse Spark 1.3
Neither model has a result on the other 15 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 and Muse Spark 1.3
BenchmarkGPT-4.1Muse 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-4.1$0.0060Fits 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$0.124Fits 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-4.1$0.480Fits in one request
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-4.1 and Muse Spark 1.3
SpecificationOpenAI GPT-4.1Meta Muse Spark 1.3
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025September 2, 2026
Context window1.05M1.05M
Input $/Mtok$2.00$1.25
Output $/Mtok$8.00$4.25
Coding indexNot benchmarked57.4
Independent measurements behind it04
Cost per solved task$0.37Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 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-4.1 has none, so the two cannot be ranked on coding. Compare them on price, context and the boards below.

Which is cheaper, GPT-4.1 or Muse Spark 1.3?

GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for GPT-4.1 only.

Which has the bigger context window, GPT-4.1 or Muse Spark 1.3?

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

How many benchmarks is the GPT-4.1 vs Muse Spark 1.3 comparison based on?

53 benchmarks have a result for both models as of October 22, 2026. GPT-4.1'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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