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GPT-5 Nano vs Muse Spark 1.1

Muse Spark 1.1 leads GPT-5 Nano on the Artificial Analysis Intelligence Index, 33.7 to 13.0, and GPT-5 Nano costs 10.6x less per output token ($0.40 vs $4.25 per million). Updated October 22, 2026; 60 benchmarks have a result for both.

GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
0
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
60
vs boards won of 60 shared

GPT-5 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-5 Nano has none, so the two cannot be ranked on coding.

Pick GPT-5 Nano for output tokens 10.6x cheaper ($0.40 vs $4.25 per million) and a lower cost per solved task ($0.109 against $0.43).

Shared results
60
GPT-5 Nano only
28
Muse Spark 1.1 only
44
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-5 Nano not benchmarked, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category
Math, 27.7 points apart on average over 4 shared benchmarks.
Widest single gap
SimpleQA Verified: GPT-5 Nano 11.7% against Muse Spark 1.1 57.8%, 46.1 points apart on a 0 to 100 scale.
Output price
GPT-5 Nano $0.40 against Muse Spark 1.1 $4.25 per million output tokens, 10.6x apart.
Context window
GPT-5 Nano takes 400K 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-5 NanoBarsMuse Spark 1.1Ties
Coding03
Intelligence02
Reasoning010
Math04
Knowledge09
Web design06
General026
All shared boards060
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
SWE-bench Verified34.8%Not measuredOnly GPT-5 Nano measured
LMArena WebDevNot measured1542Only Muse Spark 1.1 measured
AA Coding IndexNot measured71.3Only Muse Spark 1.1 measured
LiveCodeBench (Vals AI)70.2%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)78.9%Not measuredOnly GPT-5 Nano measured
SciCodeNot measured58.8%Only Muse Spark 1.1 measured
Terminal-Bench Hard (Artificial Analysis run)17.4%Not measuredOnly GPT-5 Nano measured
Terminal-Bench21.8%Not measuredOnly GPT-5 Nano measured
WeirdML38.1%Not measuredOnly GPT-5 Nano measured
LMArena Text: coding13511498Muse Spark 1.1
LMArena Text: software and IT13451498Muse 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 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
AA Intelligence Index13.033.7Muse Spark 1.1
Epoch Capabilities Index139.2154.1Muse Spark 1.1
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 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 Telecom36.5%Not measuredOnly GPT-5 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)51.4%Not measuredOnly GPT-5 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 index010
Reasoning benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
GPQA Diamond63.4%91.2%Muse Spark 1.1
MMMU Pro (Vals AI)70.9%86.6%Muse Spark 1.1
GPQA Diamond (Artificial Analysis run)67.6%89.8%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)9.5%46.2%Muse Spark 1.1
GPQA Diamond (Epoch AI run)69.4%Not measuredOnly GPT-5 Nano measured
ARC-AGI20.7%Not measuredOnly GPT-5 Nano measured
ARC-AGI-22.6%Not measuredOnly GPT-5 Nano measured
Chess puzzles22.0%34.0%Muse Spark 1.1
Mystery game puzzles9.0%Not measuredOnly GPT-5 Nano measured
VPCT37.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: hard prompts13281485Muse Spark 1.1
LMArena Text: expert13211478Muse Spark 1.1
LMArena Text: hard prompts in English13381480Muse Spark 1.1
LMArena Vision: diagrams11411305Muse Spark 1.1
LMArena Vision: homework11571287Muse Spark 1.1
Kagi LLM Benchmark62.2%Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 7 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index04
Math benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
AIME81.2%Not measuredOnly GPT-5 Nano measured
MATH 500 (Vals AI)93.8%Not measuredOnly GPT-5 Nano measured
MGSM (Vals AI)89.3%Not measuredOnly GPT-5 Nano measured
AA Math Index83.7Not measuredOnly GPT-5 Nano measured
AIME 2025 (Artificial Analysis run)83.7%Not measuredOnly GPT-5 Nano measured
OTIS Mock AIME81.1%Not measuredOnly GPT-5 Nano measured
FrontierMath, tiers 1 to 320.0%Not measuredOnly GPT-5 Nano measured
FrontierMath, tier 42.4%Not measuredOnly GPT-5 Nano measured
ProofBench12.0%39.0%Muse Spark 1.1
MATH level 595.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: math13171482Muse Spark 1.1
LMArena Text: mathematical work13261487Muse Spark 1.1
MathArena12.8%42.5%Muse Spark 1.1
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index09
Knowledge benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
MMLU Pro76.1%88.7%Muse Spark 1.1
LegalBench (Vals AI)50.1%85.0%Muse Spark 1.1
CaseLaw (Vals AI)52.6%Not measuredOnly GPT-5 Nano measured
CorpFin (Vals AI)Not measured71.3%Only Muse Spark 1.1 measured
TaxEval (Vals AI)67.4%79.7%Muse Spark 1.1
MortgageTax (Vals AI)53.6%66.1%Muse Spark 1.1
MedQA (Vals AI)93.3%Not measuredOnly GPT-5 Nano measured
MedCode (Vals AI)30.4%Not measuredOnly GPT-5 Nano measured
MMLU Pro (Artificial Analysis run)78.0%Not measuredOnly GPT-5 Nano measured
SimpleQA Verified11.7%57.8%Muse Spark 1.1
LMArena Text: science13181484Muse Spark 1.1
LMArena Text: medicine and healthcare13351479Muse Spark 1.1
LMArena Text: legal and government12981481Muse Spark 1.1
LMArena Text: business and finance13111470Muse 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 4 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
Design Arena: websites11011270Muse Spark 1.1
Design Arena: UI components10641287Muse Spark 1.1
Design Arena: game dev10441269Muse Spark 1.1
Design Arena: data viz10561267Muse Spark 1.1
Design Arena: 3D9651259Muse Spark 1.1
Design Arena: all code categories10841276Muse 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 index026
General benchmarks for GPT-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 NanoMuse Spark 1.1Leader
Public Benefits Bench (Vals AI)Not measured61.3%Only Muse Spark 1.1 measured
SAGE (Vals AI)30.4%45.6%Muse Spark 1.1
MedScribe (Vals AI)72.9%88.9%Muse Spark 1.1
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
IFBench67.6%Not measuredOnly GPT-5 Nano measured
Long context reasoning (AA-LCR)45.0%77.7%Muse Spark 1.1
DTBench62.7%94.4%Muse Spark 1.1
LMCA7.9%49.9%Muse Spark 1.1
Fiction.LiveBench44.4%Not measuredOnly GPT-5 Nano measured
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
LMArena Text13201478Muse Spark 1.1
LMArena Text: instruction following13061457Muse Spark 1.1
LMArena Text: creative writing12491435Muse Spark 1.1
LMArena Vision11591293Muse Spark 1.1
LMArena Text: English13211478Muse Spark 1.1
LMArena Text: non-English13131471Muse Spark 1.1
LMArena Text: Chinese13561515Muse Spark 1.1
LMArena Text: German13271469Muse Spark 1.1
LMArena Text: Japanese12271450Muse Spark 1.1
LMArena Text: Korean12691459Muse Spark 1.1
LMArena Text: FrenchNot measured1492Only Muse Spark 1.1 measured
LMArena Text: Spanish13601464Muse Spark 1.1
LMArena Text: Russian12961482Muse Spark 1.1
LMArena Text: Polish13141499Muse Spark 1.1
LMArena Text: multi-turn13111484Muse Spark 1.1
LMArena Text: longer queries13121462Muse Spark 1.1
LMArena Text: writing and language12831448Muse Spark 1.1
LMArena Text: entertainment and media12681438Muse Spark 1.1
LMArena Vision: English11701292Muse Spark 1.1
LMArena Vision: Chinese11761348Muse Spark 1.1
LMArena Vision: reading text11521301Muse Spark 1.1
LMArena Vision: humor11101288Muse Spark 1.1
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-5 Nano and Muse Spark 1.1
BenchmarkGPT-5 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-5 Nano$0.0003Fits in one request
Muse Spark 1.1$0.0034Fits in one request

GPT-5 Nano costs less

Repository review

50K input + 3K output tokens

GPT-5 Nano$0.0037Fits in one request
Muse Spark 1.1$0.075Fits in one request

GPT-5 Nano costs less

Agent loop

200K input + 10K output tokens

GPT-5 Nano$0.014Fits in one request
Muse Spark 1.1$0.292Fits in one request

GPT-5 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-5 Nano and Muse Spark 1.1
SpecificationOpenAI GPT-5 NanoMeta Muse Spark 1.1
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedAugust 7, 2025July 16, 2026
Context window400K1.05M
Input $/Mtok$0.05$1.25
Output $/Mtok$0.40$4.25
Coding indexNot benchmarked70.3
Independent measurements behind it03
Cost per solved task$0.109$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 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-5 Nano has none, so the two cannot be ranked on coding. Pick GPT-5 Nano for output tokens 10.6x cheaper ($0.40 vs $4.25 per million) and a lower cost per solved task ($0.109 against $0.43).

Which is cheaper, GPT-5 Nano or Muse Spark 1.1?

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GPT-5 Nano costs $0.109 and Muse Spark 1.1 $0.43.

Which has the bigger context window, GPT-5 Nano or Muse Spark 1.1?

Muse Spark 1.1, with 1.05M tokens against 400K.

How many benchmarks is the GPT-5 Nano vs Muse Spark 1.1 comparison based on?

60 benchmarks have a result for both models as of October 22, 2026. GPT-5 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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