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GPT-4.1 Nano vs Muse Spark 1.3

Muse Spark 1.3 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 48.1 to 7.8, and GPT-4.1 Nano costs 10.6x less per output token ($0.40 vs $4.25 per million). Updated October 23, 2026; 42 benchmarks have a result for both.

Replace GPT-4.1 Nano Replace Muse Spark 1.3
GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
42
vs boards won of 42 shared

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

Pick GPT-4.1 Nano for output tokens 10.6x cheaper ($0.40 vs $4.25 per million).

Model AGPT-4.1 NanoOpenAINot benchmarkedNo coding benchmarkNo cost per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
42
GPT-4.1 Nano only
29
Muse Spark 1.3 only
54
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 Nano not benchmarked, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Web design, 51.2 points apart on average over 6 shared benchmarks.
Widest single gap
OTIS Mock AIME: GPT-4.1 Nano 28.9% against Muse Spark 1.3 99.2%, 70.3 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Muse Spark 1.3 $4.25 per million output tokens, 10.6x apart.
Context window
GPT-4.1 Nano 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-4.1 NanoBarsMuse Spark 1.3Ties
Coding03
Intelligence02
Reasoning06
Math03
Knowledge04
Web design06
General018
All shared boards042
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDevNot measured1657Only Muse Spark 1.3 measured
AA Coding Index11.175.8Muse Spark 1.3
LiveCodeBench (Vals AI)42.7%Not measuredOnly GPT-4.1 Nano 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)32.6%Not measuredOnly GPT-4.1 Nano measured
SciCodeNot measured59.7%Only Muse Spark 1.3 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly GPT-4.1 Nano measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
WeirdML19.0%Not measuredOnly GPT-4.1 Nano measured
ALE-BenchNot measured1688.3Only Muse Spark 1.3 measured
LMArena Text: coding13051511Muse Spark 1.3
LMArena Text: software and IT13051511Muse Spark 1.3
LMArena WebDev: ReactNot measured1671Only 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 20 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
AA Intelligence Index7.848.1Muse Spark 1.3
Epoch Capabilities Index129.5157.2Muse Spark 1.3
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index18 boards, none shared
Agentic work benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse 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 measured1210Only 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 Telecom17.3%Not measuredOnly GPT-4.1 Nano measured
APEX-AgentsNot measured58.6%Only Muse Spark 1.3 measured
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index06
Reasoning benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
GPQA Diamond50.8%Not measuredOnly GPT-4.1 Nano measured
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
MMMU Pro (Vals AI)55.0%Not measuredOnly GPT-4.1 Nano measured
GPQA Diamond (Artificial Analysis run)51.2%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)3.8%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)48.9%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI0.0%Not measuredOnly GPT-4.1 Nano measured
ARC-AGI-20.0%Not measuredOnly GPT-4.1 Nano measured
Chess puzzles0.0%37.0%Muse Spark 1.3
Mystery game puzzlesNot measured25.0%Only Muse Spark 1.3 measured
LMArena Text: hard prompts12861504Muse Spark 1.3
LMArena Text: expert12721515Muse Spark 1.3
LMArena Text: hard prompts in English12921501Muse Spark 1.3
LMArena Vision: diagramsNot measured1330Only Muse Spark 1.3 measured
LMArena Vision: homeworkNot measured1296Only Muse Spark 1.3 measured
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Humanity's Last Exam (Scale run)Not measured25.4%Only Muse Spark 1.3 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
AIME26.5%Not measuredOnly GPT-4.1 Nano measured
MATH 500 (Vals AI)80.2%Not measuredOnly GPT-4.1 Nano measured
MGSM (Vals AI)69.3%Not measuredOnly GPT-4.1 Nano measured
AA Math Index24.0Not measuredOnly GPT-4.1 Nano measured
AIME 2025 (Artificial Analysis run)24.0%Not measuredOnly GPT-4.1 Nano measured
OTIS Mock AIME28.9%99.2%Muse Spark 1.3
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
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math12741502Muse Spark 1.3
LMArena Text: mathematical work12741493Muse Spark 1.3
MathArenaNot measured43.0%Only Muse Spark 1.3 measured
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 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
MMLU Pro63.5%Not measuredOnly GPT-4.1 Nano measured
LegalBench (Vals AI)61.1%Not measuredOnly GPT-4.1 Nano measured
CorpFin (Vals AI)42.1%Not measuredOnly GPT-4.1 Nano measured
TaxEval (Vals AI)60.8%Not measuredOnly GPT-4.1 Nano measured
MortgageTax (Vals AI)52.8%Not measuredOnly GPT-4.1 Nano measured
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MMLU Pro (Artificial Analysis run)65.7%Not measuredOnly GPT-4.1 Nano measured
SimpleQA Verified6.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: science12971506Muse Spark 1.3
LMArena Text: medicine and healthcare12761493Muse Spark 1.3
LMArena Text: legal and government13001499Muse Spark 1.3
LMArena Text: business and finance12661489Muse 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 designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
Design Arena: websites9731356Muse Spark 1.3
Design Arena: UI components9131350Muse Spark 1.3
Design Arena: game dev9701328Muse Spark 1.3
Design Arena: data viz8911343Muse Spark 1.3
Design Arena: 3D9261364Muse Spark 1.3
Design Arena: all code categories9621351Muse Spark 1.3
Design Arena: SVGNot measured1301Only Muse Spark 1.3 measured
Design Arena: ASCII artNot measured1279Only 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 index018
General benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
IFBench32.0%Not measuredOnly GPT-4.1 Nano measured
Long context reasoning (AA-LCR)20.3%83.0%Muse Spark 1.3
DTBench52.5%96.5%Muse Spark 1.3
LMCA5.5%53.9%Muse Spark 1.3
Fiction.LiveBench25.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text12851491Muse Spark 1.3
LMArena Text: instruction following12661479Muse Spark 1.3
LMArena Text: creative writing12601462Muse Spark 1.3
LMArena Vision10631308Muse Spark 1.3
LMArena Text: English13031496Muse Spark 1.3
LMArena Text: non-English12601482Muse Spark 1.3
LMArena Text: Chinese12701529Muse Spark 1.3
LMArena Text: German12881513Muse Spark 1.3
LMArena Text: Japanese11981465Muse Spark 1.3
LMArena Text: KoreanNot measured1494Only Muse Spark 1.3 measured
LMArena Text: FrenchNot measured1516Only Muse Spark 1.3 measured
LMArena Text: SpanishNot measured1493Only Muse Spark 1.3 measured
LMArena Text: Russian12611494Muse Spark 1.3
LMArena Text: PolishNot measured1487Only Muse Spark 1.3 measured
LMArena Text: multi-turn12771489Muse Spark 1.3
LMArena Text: longer queries12821489Muse Spark 1.3
LMArena Text: writing and language12611470Muse Spark 1.3
LMArena Text: entertainment and media12431458Muse Spark 1.3
LMArena Vision: English11011298Muse Spark 1.3
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 19 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 Nano and Muse Spark 1.3
BenchmarkGPT-4.1 NanoMuse 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 Nano$0.0003Fits in one request
Muse Spark 1.3$0.0034Fits in one request

GPT-4.1 Nano costs less

Repository review

50K input + 3K output tokens

GPT-4.1 Nano$0.0062Fits in one request
Muse Spark 1.3$0.075Fits in one request

GPT-4.1 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-4.1 Nano$0.024Fits in one request
Muse Spark 1.3$0.292Fits in one request

GPT-4.1 Nano 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 Nano and Muse Spark 1.3
SpecificationOpenAI GPT-4.1 NanoMeta Muse Spark 1.3
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025September 2, 2026
Context window1.05M1.05M
Input $/Mtok$0.10$1.25
Output $/Mtok$0.40$4.25
Coding indexNot benchmarked57.4
Independent measurements behind it04
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano 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 Nano has none, so the two cannot be ranked on coding. Pick GPT-4.1 Nano for output tokens 10.6x cheaper ($0.40 vs $4.25 per million).

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

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 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-4.1 Nano or Muse Spark 1.3?

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

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

42 benchmarks have a result for both models as of October 23, 2026. GPT-4.1 Nano'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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