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GPT-4.1 Nano vs Muse Spark 1.2

Muse Spark 1.2 leads GPT-4.1 Nano on the Artificial Analysis Intelligence Index, 39.6 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; 47 benchmarks have a result for both.

GPT-4.1 NanoOpenAI
Coding
No data
Overall
24.7
Output $/M
$0.40
0
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
47
vs boards won of 47 shared

GPT-4.1 Nano or Muse Spark 1.2: which to pick

Only Muse Spark 1.2 has a coding score, 55.7 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
47
GPT-4.1 Nano only
24
Muse Spark 1.2 only
50
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 1.2 55.7 from 5 benchmarks.
Widest category
Web design, 46.3 points apart on average over 6 shared benchmarks.
Widest single gap
AA Coding Index: GPT-4.1 Nano 11.1 against Muse Spark 1.2 72.2, 61.1 points apart on a 0 to 100 scale.
Output price
GPT-4.1 Nano $0.40 against Muse Spark 1.2 $4.25 per million output tokens, 10.6x apart.
Context window
GPT-4.1 Nano takes 1.05M tokens, Muse Spark 1.2 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 1.2Ties
Coding04
Intelligence02
Reasoning07
Math02
Knowledge010
Web design06
General016
All shared boards047
CodingLike-for-likeSix of these boards feed the Vibe Coding Index04
Coding benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
Aider polyglot8.9%Not measuredOnly GPT-4.1 Nano measured
LiveBench codingNot measured78.2%Only Muse Spark 1.2 measured
LMArena WebDevNot measured1534Only Muse Spark 1.2 measured
AA Coding Index11.172.2Muse Spark 1.2
LiveCodeBench (Vals AI)42.7%Not measuredOnly GPT-4.1 Nano measured
SWE-bench Verified (Vals AI)Not measured86.6%Only Muse Spark 1.2 measured
Terminal-Bench 4 (Vals AI)Not measured6.1%Only Muse Spark 1.2 measured
Vibe Code Bench (Vals AI)Not measured79.1%Only Muse Spark 1.2 measured
Code migration (Vals AI)Not measured29.9%Only Muse Spark 1.2 measured
ProgramBench (Vals AI)Not measured0.5%Only Muse Spark 1.2 measured
IOI (Vals AI)Not measured21.8%Only Muse Spark 1.2 measured
Terminal-Bench 2.1 (Vals AI)Not measured69.7%Only Muse Spark 1.2 measured
SkillsBench (Vals AI)Not measured53.0%Only Muse Spark 1.2 measured
CyberBench (Vals AI)Not measured69.5%Only Muse Spark 1.2 measured
LiveCodeBench (Artificial Analysis run)32.6%Not measuredOnly GPT-4.1 Nano measured
SciCodeNot measured57.4%Only Muse Spark 1.2 measured
Terminal-Bench Hard (Artificial Analysis run)3.8%Not measuredOnly GPT-4.1 Nano measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdML19.0%60.3%Muse Spark 1.2
LMArena Text: coding13061505Muse Spark 1.2
LMArena Text: software and IT13051505Muse Spark 1.2
LMArena WebDev: ReactNot measured1526Only Muse Spark 1.2 measured
LMArena WebDev: HTMLNot measured1543Only Muse Spark 1.2 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 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
AA Intelligence Index7.839.6Muse Spark 1.2
Epoch Capabilities Index129.5155.1Muse Spark 1.2
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
Agentic work benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
AA Agentic IndexNot measured43.2Only Muse Spark 1.2 measured
Design Arena: agents building web appsNot measured1221Only Muse Spark 1.2 measured
Design Arena: agents building full-stack appsNot measured1210Only Muse Spark 1.2 measured
Design Arena: agents building mobile appsNot measured1181Only Muse Spark 1.2 measured
Design Arena: agents building Android appsNot measured1222Only Muse Spark 1.2 measured
Design Arena: agents building gamesNot measured1178Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1074Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1170Only Muse Spark 1.2 measured
LiveBench researchNot measured67.7%Only Muse Spark 1.2 measured
LiveBench browserNot measured36.0%Only Muse Spark 1.2 measured
LiveBench long agenticNot measured21.3%Only Muse Spark 1.2 measured
SREBench (Vals AI)Not measured0.0%Only Muse Spark 1.2 measured
Finance Agent (Vals AI)Not measured60.6%Only Muse Spark 1.2 measured
Tax Agent Bench (Vals AI)Not measured32.8%Only Muse Spark 1.2 measured
Legal Research Bench (Vals AI)Not measured43.8%Only Muse Spark 1.2 measured
Excel Modeling Benchmark (Vals AI)Not measured57.0%Only Muse Spark 1.2 measured
BioMysteryBench (Vals AI)Not measured64.8%Only Muse Spark 1.2 measured
τ²-Bench Telecom17.3%Not measuredOnly GPT-4.1 Nano measured
APEX-AgentsNot measured45.4%Only Muse Spark 1.2 measured
Berkeley Function Calling Leaderboard (BFCL)33.1%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
GPQA Diamond50.8%Not measuredOnly GPT-4.1 Nano measured
LiveBench reasoningNot measured90.0%Only Muse Spark 1.2 measured
MMMU Pro (Vals AI)55.0%86.1%Muse Spark 1.2
GPQA Diamond (Artificial Analysis run)51.2%90.4%Muse Spark 1.2
Humanity's Last Exam (Artificial Analysis run)3.8%45.5%Muse Spark 1.2
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
SimpleBenchNot measured74.5%Only Muse Spark 1.2 measured
Chess puzzles0.0%27.0%Muse Spark 1.2
LMArena Text: hard prompts12861489Muse Spark 1.2
LMArena Text: expert12711475Muse Spark 1.2
LMArena Text: hard prompts in English12931487Muse Spark 1.2
LMArena Vision: diagramsNot measured1317Only Muse Spark 1.2 measured
Kagi LLM Benchmark33.3%Not measuredOnly GPT-4.1 Nano measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
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 measured43.0%Only Muse Spark 1.2 measured
MATH level 570.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text: math12741484Muse Spark 1.2
LMArena Text: mathematical work12741480Muse Spark 1.2
Neither model has a result on the other 4 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
Knowledge benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
MMLU Pro63.5%88.3%Muse Spark 1.2
LegalBench (Vals AI)61.1%85.3%Muse Spark 1.2
CorpFin (Vals AI)42.1%70.9%Muse Spark 1.2
TaxEval (Vals AI)60.8%80.4%Muse Spark 1.2
MortgageTax (Vals AI)52.8%65.4%Muse Spark 1.2
MedQA (Vals AI)68.2%Not measuredOnly GPT-4.1 Nano measured
MedCode (Vals AI)Not measured49.4%Only Muse Spark 1.2 measured
MMLU Pro (Artificial Analysis run)65.7%Not measuredOnly GPT-4.1 Nano measured
SimpleQA Verified6.0%60.3%Muse Spark 1.2
LMArena Text: science12971500Muse Spark 1.2
LMArena Text: medicine and healthcare12761496Muse Spark 1.2
LMArena Text: legal and government13001517Muse Spark 1.2
LMArena Text: business and finance12671484Muse Spark 1.2
Neither model has a result on the other 7 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 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
Design Arena: websites9731312Muse Spark 1.2
Design Arena: UI components9131299Muse Spark 1.2
Design Arena: game dev9701300Muse Spark 1.2
Design Arena: data viz8911334Muse Spark 1.2
Design Arena: 3D9241300Muse Spark 1.2
Design Arena: all code categories9621312Muse Spark 1.2
Design Arena: SVGNot measured1283Only Muse Spark 1.2 measured
Design Arena: ASCII artNot measured1284Only Muse Spark 1.2 measured
LiveBench designNot measured67.1%Only Muse Spark 1.2 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index016
General benchmarks for GPT-4.1 Nano and Muse Spark 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
LiveBench data analysisNot measured76.5%Only Muse Spark 1.2 measured
Public Benefits Bench (Vals AI)Not measured68.5%Only Muse Spark 1.2 measured
SAGE (Vals AI)Not measured47.7%Only Muse Spark 1.2 measured
MedScribe (Vals AI)Not measured90.1%Only Muse Spark 1.2 measured
Vals Multimodal IndexNot measured69.8%Only Muse Spark 1.2 measured
IFBench32.0%Not measuredOnly GPT-4.1 Nano measured
Long context reasoning (AA-LCR)20.3%79.0%Muse Spark 1.2
DTBench52.5%94.7%Muse Spark 1.2
LMCA5.5%48.4%Muse Spark 1.2
Fiction.LiveBench25.0%Not measuredOnly GPT-4.1 Nano measured
LMArena Text12851482Muse Spark 1.2
LMArena Text: instruction following12661462Muse Spark 1.2
LMArena Text: creative writing12601436Muse Spark 1.2
LMArena Vision10631304Muse Spark 1.2
LMArena Text: English13031483Muse Spark 1.2
LMArena Text: non-English12601476Muse Spark 1.2
LMArena Text: Chinese12701509Muse Spark 1.2
LMArena Text: German1288Not measuredOnly GPT-4.1 Nano measured
LMArena Text: Japanese1198Not measuredOnly GPT-4.1 Nano measured
LMArena Text: KoreanNot measured1462Only Muse Spark 1.2 measured
LMArena Text: FrenchNot measured1495Only Muse Spark 1.2 measured
LMArena Text: SpanishNot measured1484Only Muse Spark 1.2 measured
LMArena Text: Russian12611483Muse Spark 1.2
LMArena Text: multi-turn12771502Muse Spark 1.2
LMArena Text: longer queries12831473Muse Spark 1.2
LMArena Text: writing and language12611453Muse Spark 1.2
LMArena Text: entertainment and media12431443Muse Spark 1.2
LMArena Vision: English11011291Muse Spark 1.2
LMArena Vision: reading textNot measured1313Only Muse Spark 1.2 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 1.2
BenchmarkGPT-4.1 NanoMuse Spark 1.2Leader
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 1.2$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 1.2$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 1.2$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 1.2
SpecificationOpenAI GPT-4.1 NanoMeta Muse Spark 1.2
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025August 5, 2026
Context window1.05M1.05M
Input $/Mtok$0.10$1.25
Output $/Mtok$0.40$4.25
Coding indexNot benchmarked55.7
Independent measurements behind it05
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-4.1 Nano better than Muse Spark 1.2 for coding?

Only Muse Spark 1.2 has a coding score, 55.7 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 1.2?

GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.2 only.

Which has the bigger context window, GPT-4.1 Nano or Muse Spark 1.2?

Muse Spark 1.2, with 1.05M tokens against 1.05M.

How many benchmarks is the GPT-4.1 Nano vs Muse Spark 1.2 comparison based on?

47 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 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.

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