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GPT-4.1 Nano vs Muse Spark 1.1

Muse Spark 1.1 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 33.7 to 7.8, and GPT-4.1 Nano costs 10.6x less per output token ($0.40 vs $4.25 per million). Updated October 22, 2026; 50 benchmarks have a result for both.

GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
50
vs boards won of 50 shared

GPT-4.1 Nano 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-4.1 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).

Shared results
50
GPT-4.1 Nano only
21
Muse Spark 1.1 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 1.1 70.3 from 3 benchmarks.
Widest category
Coding, 41.9 points apart on average over 4 shared benchmarks.
Widest single gap
AA Coding Index: GPT-4.1 Nano 11.1 against Muse Spark 1.1 71.3, 60.2 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Muse Spark 1.1 $4.25 per million output tokens, 10.6x apart.
Context window
GPT-4.1 Nano takes 1.05M 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-4.1 NanoBarsMuse Spark 1.1Ties
Coding04
Intelligence02
Reasoning08
Math02
Knowledge010
Web design06
General018
All shared boards050
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
LMArena WebDevNot measured1542Only Muse Spark 1.1 measured
AA Coding Index11.171.3Muse Spark 1.1
LiveCodeBench (Vals AI)42.7%85.9%Muse Spark 1.1
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
LiveCodeBench (Artificial Analysis run)32.6%Not measuredOnly GPT-4.1 Nano measured
SciCodeNot measured58.8%Only Muse Spark 1.1 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly GPT-4.1 Nano measured
WeirdML19.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: coding13061498Muse Spark 1.1
LMArena Text: software and IT13051498Muse 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
SWE Atlas: Codebase QnANot measured42.2%Only Muse Spark 1.1 measured
SWE Atlas: Test WritingNot measured41.5%Only Muse Spark 1.1 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
AA Intelligence Index7.833.7Muse Spark 1.1
Epoch Capabilities Index129.5154.1Muse Spark 1.1
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse 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 measured1145Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1134Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured1021Only 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
τ²-Bench Telecom17.3%Not measuredOnly GPT-4.1 Nano measured
APEX-AgentsNot measured31.8%Only Muse Spark 1.1 measured
Vending-Bench 2Not measured$6,520Only Muse Spark 1.1 measured
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
MCP AtlasNot measured88.1%Only Muse Spark 1.1 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
GPQA Diamond50.8%91.2%Muse Spark 1.1
MMMU Pro (Vals AI)55.0%86.6%Muse Spark 1.1
GPQA Diamond (Artificial Analysis run)51.2%89.8%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)3.8%46.2%Muse Spark 1.1
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%34.0%Muse Spark 1.1
LMArena Text: hard prompts12861485Muse Spark 1.1
LMArena Text: expert12711478Muse Spark 1.1
LMArena Text: hard prompts in English12931480Muse Spark 1.1
LMArena Vision: diagramsNot measured1305Only Muse Spark 1.1 measured
LMArena Vision: homeworkNot measured1287Only Muse Spark 1.1 measured
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
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%Not measuredOnly GPT-4.1 Nano measured
ProofBenchNot measured39.0%Only Muse Spark 1.1 measured
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math12741482Muse Spark 1.1
LMArena Text: mathematical work12741487Muse Spark 1.1
MathArenaNot measured42.5%Only Muse Spark 1.1 measured
Neither model has a result on the other 3 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
Knowledge benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
MMLU Pro63.5%88.7%Muse Spark 1.1
LegalBench (Vals AI)61.1%85.0%Muse Spark 1.1
CorpFin (Vals AI)42.1%71.3%Muse Spark 1.1
TaxEval (Vals AI)60.8%79.7%Muse Spark 1.1
MortgageTax (Vals AI)52.8%66.1%Muse Spark 1.1
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%57.8%Muse Spark 1.1
LMArena Text: science12971484Muse Spark 1.1
LMArena Text: medicine and healthcare12761479Muse Spark 1.1
LMArena Text: legal and government13001481Muse Spark 1.1
LMArena Text: business and finance12671470Muse Spark 1.1
PRBench FinanceNot measured55.0%Only Muse Spark 1.1 measured
PRBench LegalNot measured57.0%Only Muse Spark 1.1 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 1.1
BenchmarkGPT-4.1 NanoMuse Spark 1.1Leader
Design Arena: websites9731270Muse Spark 1.1
Design Arena: UI components9131287Muse Spark 1.1
Design Arena: game dev9701269Muse Spark 1.1
Design Arena: data viz8911267Muse Spark 1.1
Design Arena: 3D9241259Muse Spark 1.1
Design Arena: all code categories9621276Muse Spark 1.1
Design Arena: SVGNot measured1234Only Muse Spark 1.1 measured
Design Arena: ASCII artNot measured1269Only 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 index018
General benchmarks for GPT-4.1 Nano and Muse Spark 1.1
BenchmarkGPT-4.1 NanoMuse 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
IFBench32.0%Not measuredOnly GPT-4.1 Nano measured
Long context reasoning (AA-LCR)20.3%77.7%Muse Spark 1.1
DTBench52.5%94.4%Muse Spark 1.1
LMCA5.5%49.9%Muse Spark 1.1
Fiction.LiveBench25.0%Not measuredOnly GPT-4.1 Nano measured
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
LMArena Text12851478Muse Spark 1.1
LMArena Text: instruction following12661457Muse Spark 1.1
LMArena Text: creative writing12601435Muse Spark 1.1
LMArena Vision10631293Muse Spark 1.1
LMArena Text: English13031478Muse Spark 1.1
LMArena Text: non-English12601471Muse Spark 1.1
LMArena Text: Chinese12701515Muse Spark 1.1
LMArena Text: German12881469Muse Spark 1.1
LMArena Text: Japanese11981450Muse Spark 1.1
LMArena Text: KoreanNot measured1459Only Muse Spark 1.1 measured
LMArena Text: FrenchNot measured1492Only Muse Spark 1.1 measured
LMArena Text: SpanishNot measured1464Only Muse Spark 1.1 measured
LMArena Text: Russian12611482Muse Spark 1.1
LMArena Text: PolishNot measured1499Only Muse Spark 1.1 measured
LMArena Text: multi-turn12771484Muse Spark 1.1
LMArena Text: longer queries12831462Muse Spark 1.1
LMArena Text: writing and language12611448Muse Spark 1.1
LMArena Text: entertainment and media12431438Muse Spark 1.1
LMArena Vision: English11011292Muse Spark 1.1
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
MultiChallengeNot measured75.3%Only Muse Spark 1.1 measured
EQ-Bench 4Not measured1260Only Muse Spark 1.1 measured
Neither model has a result on the other 12 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 1.1
BenchmarkGPT-4.1 NanoMuse 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-4.1 Nano$0.0003Fits in one request
Muse Spark 1.1$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 1.1$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 1.1$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 1.1
SpecificationOpenAI GPT-4.1 NanoMeta Muse Spark 1.1
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025July 16, 2026
Context window1.05M1.05M
Input $/Mtok$0.10$1.25
Output $/Mtok$0.40$4.25
Coding indexNot benchmarked70.3
Independent measurements behind it03
Cost per solved taskNot computable$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano 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-4.1 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 1.1?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 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-4.1 Nano or Muse Spark 1.1?

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

How many benchmarks is the GPT-4.1 Nano vs Muse Spark 1.1 comparison based on?

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