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GPT-4.1 vs Muse Spark 1.2

Updated October 21, 2026. 52 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GPT-4.1 Replace Muse Spark 1.2
GPT-4.1OpenAI
Coding
46.5
Overall
12.7
Output $/M
$8.00
1
Muse Spark 1.2Meta
Coding
65.1
Overall
39.6
Output $/M
$4.25
51
vs boards won of 52 shared

Decision reading

Pick Muse Spark 1.2 for coding: it scores 65.1 on the Vibe Coding Index against 46.5 for GPT-4.1.

Pick GPT-4.1 when a solved task costs $0.37 against $0.64, or when the benchmark that matters is MortgageTax (Vals AI), where it leads.

Model AGPT-4.1OpenAI46.5/1002 independent benchmarks$0.37 per solved taskModel BMuse Spark 1.2Meta65.1/1002 independent benchmarks$0.64 per solved task
Shared results
52
GPT-4.1 only
35
Muse Spark 1.2 only
45
Like-for-like categories
7 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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 46.5 from 2 benchmarks, Muse Spark 1.2 65.1 from 2 benchmarks.
Widest category
Web design, 36.8 points apart on average over 6 shared benchmarks.
Widest single gap
Design Arena: 3D: GPT-4.1 850 against Muse Spark 1.2 1301, 56.4 points apart on a 0 to 100 scale.
Output price
GPT-4.1 $8.00 against Muse Spark 1.2 $4.25 per million output tokens, 1.9x apart.
Context window
GPT-4.1 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-4.1BarsMuse Spark 1.2Ties
Coding03
Intelligence02
Reasoning09
Math02
Knowledge19
Web design06
General020
All shared boards151
CodingLike-for-likeFour of these boards feed the Vibe Coding Index03
Coding benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
Aider polyglot52.4%Not measuredOnly GPT-4.1 measured
SWE-bench Verified39.6%Not measuredOnly GPT-4.1 measured
SWE-bench Multimodal31.1%Not measuredOnly GPT-4.1 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)54.7%Not measuredOnly GPT-4.1 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)45.7%Not measuredOnly GPT-4.1 measured
SciCodeNot measured57.4%Only Muse Spark 1.2 measured
Terminal-Bench Hard (Artificial Analysis run)13.6%Not measuredOnly GPT-4.1 measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdML39.0%60.3%Muse Spark 1.2
ALE-Bench558.1Not measuredOnly GPT-4.1 measured
LMArena Text: coding13901505Muse Spark 1.2
LMArena Text: software and IT13911505Muse 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 12 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
AA Intelligence Index12.739.6Muse Spark 1.2
Epoch Capabilities Index136.7155.1Muse Spark 1.2
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index19 boards, none shared
Agentic work benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
AA Agentic IndexNot measured43.2Only Muse Spark 1.2 measured
Design Arena: agents building web appsNot measured1222Only Muse Spark 1.2 measured
Design Arena: agents building full-stack appsNot measured1210Only Muse Spark 1.2 measured
Design Arena: agents building mobile appsNot measured1182Only Muse Spark 1.2 measured
Design Arena: agents building Android appsNot measured1228Only Muse Spark 1.2 measured
Design Arena: agents building gamesNot measured1179Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1135Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1198Only 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 Telecom47.1%Not measuredOnly GPT-4.1 measured
APEX-AgentsNot measured45.4%Only Muse Spark 1.2 measured
Neither model has a result on the other 20 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index09
Reasoning benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
GPQA Diamond65.4%Not measuredOnly GPT-4.1 measured
LiveBench reasoningNot measured90.0%Only Muse Spark 1.2 measured
MMMU Pro (Vals AI)72.4%86.1%Muse Spark 1.2
GPQA Diamond (Artificial Analysis run)66.6%90.4%Muse Spark 1.2
Humanity's Last Exam (Artificial Analysis run)4.2%45.5%Muse Spark 1.2
GPQA Diamond (Epoch AI run)66.9%Not measuredOnly GPT-4.1 measured
ARC-AGI5.5%Not measuredOnly GPT-4.1 measured
ARC-AGI-20.4%Not measuredOnly GPT-4.1 measured
SimpleBench27.0%74.5%Muse Spark 1.2
Chess puzzles3.0%27.0%Muse Spark 1.2
LMArena Text: hard prompts13841489Muse Spark 1.2
LMArena Text: expert13641475Muse Spark 1.2
LMArena Text: hard prompts in English13931487Muse Spark 1.2
LMArena Vision: diagrams12151317Muse Spark 1.2
LMArena Vision: homework1248Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
AIME39.6%Not measuredOnly GPT-4.1 measured
MATH 500 (Vals AI)87.2%Not measuredOnly GPT-4.1 measured
MGSM (Vals AI)87.7%Not measuredOnly GPT-4.1 measured
AA Math Index34.7Not measuredOnly GPT-4.1 measured
AIME 2025 (Artificial Analysis run)34.7%Not measuredOnly GPT-4.1 measured
OTIS Mock AIME38.3%Not measuredOnly GPT-4.1 measured
FrontierMath, tiers 1 to 36.0%Not measuredOnly GPT-4.1 measured
ProofBenchNot measured43.0%Only Muse Spark 1.2 measured
MATH level 583.0%Not measuredOnly GPT-4.1 measured
LMArena Text: math13691484Muse Spark 1.2
LMArena Text: mathematical work13601480Muse Spark 1.2
Neither model has a result on the other 2 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index19
Knowledge benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
MMLU Pro80.5%88.3%Muse Spark 1.2
LegalBench (Vals AI)83.1%85.3%Muse Spark 1.2
CaseLaw (Vals AI)69.9%Not measuredOnly GPT-4.1 measured
CorpFin (Vals AI)63.0%70.9%Muse Spark 1.2
TaxEval (Vals AI)75.1%80.4%Muse Spark 1.2
MortgageTax (Vals AI)65.9%65.4%GPT-4.1
MedQA (Vals AI)91.2%Not measuredOnly GPT-4.1 measured
MedCode (Vals AI)Not measured49.4%Only Muse Spark 1.2 measured
MMLU Pro (Artificial Analysis run)80.6%Not measuredOnly GPT-4.1 measured
SimpleQA Verified31.1%60.3%Muse Spark 1.2
GeoBench72.0%Not measuredOnly GPT-4.1 measured
LMArena Text: science13821500Muse Spark 1.2
LMArena Text: medicine and healthcare13791496Muse Spark 1.2
LMArena Text: legal and government13991517Muse Spark 1.2
LMArena Text: business and finance13691484Muse Spark 1.2
Neither model has a result on the other 2 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index06
Web design benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse Spark 1.2Leader
Design Arena: websites10391313Muse Spark 1.2
Design Arena: UI components10001300Muse Spark 1.2
Design Arena: game dev10801302Muse Spark 1.2
Design Arena: data viz11041334Muse Spark 1.2
Design Arena: 3D8501301Muse Spark 1.2
Design Arena: all code categories10261313Muse Spark 1.2
Design Arena: SVGNot measured1285Only 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 index020
General benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse 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
IFBench43.0%Not measuredOnly GPT-4.1 measured
Long context reasoning (AA-LCR)68.3%79.0%Muse Spark 1.2
DTBench68.3%94.7%Muse Spark 1.2
LMCA25.6%48.4%Muse Spark 1.2
Fiction.LiveBench63.9%Not measuredOnly GPT-4.1 measured
LMArena Text13831482Muse Spark 1.2
LMArena Text: instruction following13671462Muse Spark 1.2
LMArena Text: creative writing13631436Muse Spark 1.2
LMArena Vision12101304Muse Spark 1.2
LMArena Text: English13921483Muse Spark 1.2
LMArena Text: non-English13701476Muse Spark 1.2
LMArena Text: Chinese13821509Muse Spark 1.2
LMArena Text: German1381Not measuredOnly GPT-4.1 measured
LMArena Text: Japanese1319Not measuredOnly GPT-4.1 measured
LMArena Text: Korean13381462Muse Spark 1.2
LMArena Text: French13821495Muse Spark 1.2
LMArena Text: Spanish13761484Muse Spark 1.2
LMArena Text: Russian13771483Muse Spark 1.2
LMArena Text: Polish1389Not measuredOnly GPT-4.1 measured
LMArena Text: multi-turn13971502Muse Spark 1.2
LMArena Text: longer queries13851473Muse Spark 1.2
LMArena Text: writing and language13711453Muse Spark 1.2
LMArena Text: entertainment and media13651443Muse Spark 1.2
LMArena Vision: English12091291Muse Spark 1.2
LMArena Vision: Chinese1226Not measuredOnly GPT-4.1 measured
LMArena Vision: reading text12181313Muse Spark 1.2
LMArena Vision: humor1196Not measuredOnly GPT-4.1 measured
LMArena Vision: captioning1207Not measuredOnly GPT-4.1 measured
LMArena Vision: recognizing things1208Not measuredOnly GPT-4.1 measured
LMArena Vision: creative writing1210Not measuredOnly GPT-4.1 measured
Neither model has a result on the other 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-4.1 and Muse Spark 1.2
BenchmarkGPT-4.1Muse 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$0.0060Fits in one request
Muse Spark 1.2$0.0034Fits in one request

Muse Spark 1.2 costs less

Repository review

50K input + 3K output tokens

GPT-4.1$0.124Fits in one request
Muse Spark 1.2$0.075Fits in one request

Muse Spark 1.2 costs less

Agent loop

200K input + 10K output tokens

GPT-4.1$0.480Fits in one request
Muse Spark 1.2$0.292Fits in one request

Muse Spark 1.2 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 and Muse Spark 1.2
SpecificationOpenAI GPT-4.1Meta Muse Spark 1.2
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 14, 2025August 5, 2026
Context window1.05M1.05M
Input $/Mtok$2.00$1.25
Output $/Mtok$8.00$4.25
Coding index46.565.1
Independent measurements behind it22
Cost per solved task$0.37$0.64
SourceOpenRouter listingOpenRouter listing

Questions

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

Pick Muse Spark 1.2 for coding: it scores 65.1 on the Vibe Coding Index against 46.5 for GPT-4.1. Pick GPT-4.1 when a solved task costs $0.37 against $0.64, or when the benchmark that matters is MortgageTax (Vals AI), where it leads.

Which is cheaper, GPT-4.1 or Muse Spark 1.2?

GPT-4.1 costs $2.00 per million input tokens and $8.00 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GPT-4.1 costs $0.37 and Muse Spark 1.2 $0.64.

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

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

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

52 benchmarks have a result for both models as of October 21, 2026. GPT-4.1's coding index rests on 2 independent benchmarks and Muse Spark 1.2's on 2. Where only one model has a result, the page says so instead of naming a winner.

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<iframe src="https://llmbenchmark.ai/embed/compare/gpt-4-1-vs-meta-muse-spark-1-2" title="GPT-4.1 vs Muse Spark 1.2, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gpt-4-1-vs-meta-muse-spark-1-2">LLMBenchmark.ai, GPT-4.1 vs Muse Spark 1.2</a></p>