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GPT-5 Nano vs Muse Spark 1.2

Muse Spark 1.2 leads GPT-5 Nano on the Artificial Analysis Intelligence Index, 39.6 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; 53 benchmarks have a result for both.

GPT-5 NanoOpenAI
Coding
No data
Overall
35.6
Output $/M
$0.40
0
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
53
vs boards won of 53 shared

GPT-5 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-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 $0.64).

Shared results
53
GPT-5 Nano only
34
Muse Spark 1.2 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 1.2 55.7 from 5 benchmarks.
Widest category
Web design, 32.2 points apart on average over 6 shared benchmarks.
Widest single gap
SimpleQA Verified: GPT-5 Nano 11.7% against Muse Spark 1.2 60.3%, 48.6 points apart on a 0 to 100 scale.
Output price
GPT-5 Nano $0.40 against Muse Spark 1.2 $4.25 per million output tokens, 10.6x apart.
Context window
GPT-5 Nano takes 400K 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-5 NanoBarsMuse Spark 1.2Ties
Coding03
Intelligence02
Reasoning08
Math03
Knowledge010
Web design06
General021
All shared boards053
CodingLike-for-likeSix of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
SWE-bench Verified34.8%Not measuredOnly GPT-5 Nano measured
LiveBench codingNot measured78.2%Only Muse Spark 1.2 measured
LMArena WebDevNot measured1534Only Muse Spark 1.2 measured
AA Coding IndexNot measured72.2Only Muse Spark 1.2 measured
LiveCodeBench (Vals AI)70.2%Not measuredOnly GPT-5 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)78.9%Not measuredOnly GPT-5 Nano measured
SciCodeNot measured57.4%Only Muse Spark 1.2 measured
Terminal-Bench Hard (Artificial Analysis run)17.4%Not measuredOnly GPT-5 Nano measured
Terminal-Bench21.8%Not measuredOnly GPT-5 Nano measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdML38.1%60.3%Muse Spark 1.2
LMArena Text: coding13511505Muse Spark 1.2
LMArena Text: software and IT13451505Muse 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 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
AA Intelligence Index13.039.6Muse Spark 1.2
Epoch Capabilities Index139.2155.1Muse Spark 1.2
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index20 boards, none shared
Agentic work benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 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 measured1179Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1085Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1172Only 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 Telecom36.5%Not measuredOnly GPT-5 Nano measured
APEX-AgentsNot measured45.4%Only Muse Spark 1.2 measured
Berkeley Function Calling Leaderboard (BFCL)51.4%Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index08
Reasoning benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
GPQA Diamond63.4%Not measuredOnly GPT-5 Nano measured
LiveBench reasoningNot measured90.0%Only Muse Spark 1.2 measured
MMMU Pro (Vals AI)70.9%86.1%Muse Spark 1.2
GPQA Diamond (Artificial Analysis run)67.6%90.4%Muse Spark 1.2
Humanity's Last Exam (Artificial Analysis run)9.5%45.5%Muse Spark 1.2
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
SimpleBenchNot measured74.5%Only Muse Spark 1.2 measured
Chess puzzles22.0%27.0%Muse Spark 1.2
Mystery game puzzles9.0%Not measuredOnly GPT-5 Nano measured
VPCT37.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: hard prompts13281489Muse Spark 1.2
LMArena Text: expert13211475Muse Spark 1.2
LMArena Text: hard prompts in English13381487Muse Spark 1.2
LMArena Vision: diagrams11411317Muse Spark 1.2
LMArena Vision: homework1157Not measuredOnly GPT-5 Nano measured
Kagi LLM Benchmark62.2%Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
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%43.0%Muse Spark 1.2
MATH level 595.2%Not measuredOnly GPT-5 Nano measured
LMArena Text: math13171484Muse Spark 1.2
LMArena Text: mathematical work13261480Muse Spark 1.2
Neither model has a result on the other 1 board here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index010
Knowledge benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
MMLU Pro76.1%88.3%Muse Spark 1.2
LegalBench (Vals AI)50.1%85.3%Muse Spark 1.2
CaseLaw (Vals AI)52.6%Not measuredOnly GPT-5 Nano measured
CorpFin (Vals AI)Not measured70.9%Only Muse Spark 1.2 measured
TaxEval (Vals AI)67.4%80.4%Muse Spark 1.2
MortgageTax (Vals AI)53.6%65.4%Muse Spark 1.2
MedQA (Vals AI)93.3%Not measuredOnly GPT-5 Nano measured
MedCode (Vals AI)30.4%49.4%Muse Spark 1.2
MMLU Pro (Artificial Analysis run)78.0%Not measuredOnly GPT-5 Nano measured
SimpleQA Verified11.7%60.3%Muse Spark 1.2
LMArena Text: science13181500Muse Spark 1.2
LMArena Text: medicine and healthcare13351496Muse Spark 1.2
LMArena Text: legal and government12981517Muse Spark 1.2
LMArena Text: business and finance13111484Muse Spark 1.2
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 1.2
BenchmarkGPT-5 NanoMuse Spark 1.2Leader
Design Arena: websites11011312Muse Spark 1.2
Design Arena: UI components10641298Muse Spark 1.2
Design Arena: game dev10441301Muse Spark 1.2
Design Arena: data viz10561334Muse Spark 1.2
Design Arena: 3D9651301Muse Spark 1.2
Design Arena: all code categories10841312Muse Spark 1.2
Design Arena: SVGNot measured1284Only 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 index021
General benchmarks for GPT-5 Nano and Muse Spark 1.2
BenchmarkGPT-5 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)30.4%47.7%Muse Spark 1.2
MedScribe (Vals AI)72.9%90.1%Muse Spark 1.2
Vals Multimodal IndexNot measured69.8%Only Muse Spark 1.2 measured
IFBench67.6%Not measuredOnly GPT-5 Nano measured
Long context reasoning (AA-LCR)45.0%79.0%Muse Spark 1.2
DTBench62.7%94.7%Muse Spark 1.2
LMCA7.9%48.4%Muse Spark 1.2
Fiction.LiveBench44.4%Not measuredOnly GPT-5 Nano measured
LMArena Text13201482Muse Spark 1.2
LMArena Text: instruction following13061462Muse Spark 1.2
LMArena Text: creative writing12491436Muse Spark 1.2
LMArena Vision11591304Muse Spark 1.2
LMArena Text: English13211483Muse Spark 1.2
LMArena Text: non-English13131476Muse Spark 1.2
LMArena Text: Chinese13561509Muse Spark 1.2
LMArena Text: German1327Not measuredOnly GPT-5 Nano measured
LMArena Text: Japanese1227Not measuredOnly GPT-5 Nano measured
LMArena Text: Korean12691462Muse Spark 1.2
LMArena Text: FrenchNot measured1495Only Muse Spark 1.2 measured
LMArena Text: Spanish13601484Muse Spark 1.2
LMArena Text: Russian12961483Muse Spark 1.2
LMArena Text: Polish1314Not measuredOnly GPT-5 Nano measured
LMArena Text: multi-turn13111502Muse Spark 1.2
LMArena Text: longer queries13121473Muse Spark 1.2
LMArena Text: writing and language12831453Muse Spark 1.2
LMArena Text: entertainment and media12681443Muse Spark 1.2
LMArena Vision: English11701291Muse Spark 1.2
LMArena Vision: Chinese1176Not measuredOnly GPT-5 Nano measured
LMArena Vision: reading text11521313Muse Spark 1.2
LMArena Vision: humor1110Not measuredOnly GPT-5 Nano measured
Neither model has a result on the other 14 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 1.2
BenchmarkGPT-5 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-5 Nano$0.0003Fits in one request
Muse Spark 1.2$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 1.2$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 1.2$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 1.2
SpecificationOpenAI GPT-5 NanoMeta Muse Spark 1.2
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedAugust 7, 2025August 5, 2026
Context window400K1.05M
Input $/Mtok$0.05$1.25
Output $/Mtok$0.40$4.25
Coding indexNot benchmarked55.7
Independent measurements behind it05
Cost per solved task$0.109$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5 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-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 $0.64).

Which is cheaper, GPT-5 Nano or Muse Spark 1.2?

GPT-5 Nano costs $0.05 per million input tokens and $0.40 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GPT-5 Nano costs $0.109 and Muse Spark 1.2 $0.64.

Which has the bigger context window, GPT-5 Nano or Muse Spark 1.2?

Muse Spark 1.2, with 1.05M tokens against 400K.

How many benchmarks is the GPT-5 Nano vs Muse Spark 1.2 comparison based on?

53 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 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.

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