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GPT-5.5 vs Muse Spark 1.3

GPT-5.5 leads Muse Spark 1.3 on coding, 71.3 to 57.4 on the Vibe Coding Index, and Muse Spark 1.3 costs 7.1x less per output token ($4.25 vs $30.00 per million). Updated October 22, 2026; 86 benchmarks have a result for both.

Replace GPT-5.5 Replace Muse Spark 1.3
GPT-5.5OpenAI
Coding
71.3
Overall
69.2
Output $/M
$30.00
18
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
66
vs boards won of 86 shared, 2 tied

GPT-5.5 or Muse Spark 1.3: which to pick

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 57.4 for Muse Spark 1.3.

Pick Muse Spark 1.3 for output tokens 7.1x cheaper ($4.25 vs $30.00 per million) and work measured by LiveBench coding or LMArena WebDev, where it leads.

Model AGPT-5.5OpenAI71.3/1005 independent benchmarks$1.65 per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
86
GPT-5.5 only
48
Muse Spark 1.3 only
6
Like-for-like categories
8 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-5.5 71.3 from 5 benchmarks, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Agentic work, 12.3 points apart on average over 14 shared benchmarks.
Widest single gap
LiveBench browser: GPT-5.5 48.0% against Muse Spark 1.3 80.0%, 32.0 points apart on a 0 to 100 scale.
Output price
GPT-5.5 $30.00 against Muse Spark 1.3 $4.25 per million output tokens, 7.1x apart.
Context window
GPT-5.5 takes 1.05M tokens, Muse Spark 1.3 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-5.5BarsMuse Spark 1.3Ties
Coding3101 tie
Intelligence11
Agentic work212
Reasoning361 tie
Math33
Knowledge04
Web design09
General621
All shared boards18662 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index310
Coding benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
LiveBench coding85.1%90.2%Muse Spark 1.3
LMArena WebDev15131659Muse Spark 1.3
AA Coding Index74.975.8Muse Spark 1.3
LiveCodeBench (Vals AI)85.3%Not measuredOnly GPT-5.5 measured
SWE-bench Verified (Vals AI)82.6%Not measuredOnly GPT-5.5 measured
Terminal-Bench 4 (Vals AI)Not measured10.6%Only Muse Spark 1.3 measured
Vibe Code Bench (Vals AI)69.8%82.9%Muse Spark 1.3
Code migration (Vals AI)45.2%27.6%GPT-5.5
ProgramBench (Vals AI)0.5%0.5%Tie
IOI (Vals AI)Not measured43.9%Only Muse Spark 1.3 measured
Terminal-Bench 2.1 (Vals AI)76.4%72.3%GPT-5.5
SkillsBench (Vals AI)62.5%Not measuredOnly GPT-5.5 measured
CyberBench (Vals AI)Not measured69.4%Only Muse Spark 1.3 measured
SciCode56.1%59.7%Muse Spark 1.3
Terminal-Bench Hard (Artificial Analysis run)60.6%Not measuredOnly GPT-5.5 measured
Terminal-Bench84.7%Not measuredOnly GPT-5.5 measured
FrontierCode43.0%Not measuredOnly GPT-5.5 measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
GSO-Bench40.2%Not measuredOnly GPT-5.5 measured
WeirdML84.9%Not measuredOnly GPT-5.5 measured
MirrorCode10.0%Not measuredOnly GPT-5.5 measured
ALE-Bench1943.01688.3GPT-5.5
LMArena Text: coding14941510Muse Spark 1.3
LMArena Text: software and IT14931511Muse Spark 1.3
LMArena WebDev: React15061672Muse Spark 1.3
LMArena WebDev: HTML15431653Muse Spark 1.3
LMArena WebDev: from an image15321640Muse Spark 1.3
Neither model has a result on the other 12 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
AA Intelligence Index38.448.1Muse Spark 1.3
Epoch Capabilities Index159.7157.2GPT-5.5
Agentic workLike-for-likePublic boards, shown as published, kept out of the index212
Agentic work benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
AA Agentic Index36.455.5Muse Spark 1.3
Design Arena: agents building web apps11171297Muse Spark 1.3
Design Arena: agents building full-stack apps10891295Muse Spark 1.3
Design Arena: agents building mobile apps11421218Muse Spark 1.3
Design Arena: agents building Android apps1164Not measuredOnly GPT-5.5 measured
Design Arena: agents building Godot games11731241Muse Spark 1.3
Design Arena: agents building games1179Not measuredOnly GPT-5.5 measured
Design Arena: HTML slides1017Not measuredOnly GPT-5.5 measured
Design Arena: PowerPoint slides10841219Muse Spark 1.3
Design Arena: spreadsheetsNot measured1062Only Muse Spark 1.3 measured
LiveBench research61.6%68.6%Muse Spark 1.3
LiveBench browser48.0%80.0%Muse Spark 1.3
LiveBench long agentic44.6%40.4%GPT-5.5
SREBench (Vals AI)3.8%Not measuredOnly GPT-5.5 measured
Finance Agent (Vals AI)51.8%58.9%Muse Spark 1.3
Tax Agent Bench (Vals AI)21.8%36.0%Muse Spark 1.3
Legal Research Bench (Vals AI)40.4%40.9%Muse Spark 1.3
Excel Modeling Benchmark (Vals AI)64.5%62.7%GPT-5.5
Terminal-Bench-Science (Vals AI)Not measured4.3%Only Muse Spark 1.3 measured
Time Horizon Index (Vals AI)8.3%Not measuredOnly GPT-5.5 measured
τ²-Bench Telecom93.9%Not measuredOnly GPT-5.5 measured
APEX-Agents55.1%58.6%Muse Spark 1.3
Remote Labor Index6.3%Not measuredOnly GPT-5.5 measured
OSWorld 2.013.0%Not measuredOnly GPT-5.5 measured
DeepResearch Bench54.0%Not measuredOnly GPT-5.5 measured
PostTrainBench27.2%Not measuredOnly GPT-5.5 measured
Vending-Bench 2$7,524Not measuredOnly GPT-5.5 measured
Neither model has a result on the other 14 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index36
Reasoning benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
GPQA Diamond93.2%Not measuredOnly GPT-5.5 measured
LiveBench reasoning89.7%89.7%Tie
MMMU Pro (Vals AI)88.3%Not measuredOnly GPT-5.5 measured
GPQA Diamond (Artificial Analysis run)93.5%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)45.8%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)90.7%Not measuredOnly GPT-5.5 measured
ARC-AGI95.0%Not measuredOnly GPT-5.5 measured
ARC-AGI-285.0%Not measuredOnly GPT-5.5 measured
SimpleBench69.0%Not measuredOnly GPT-5.5 measured
Chess puzzles63.0%37.0%GPT-5.5
Mystery game puzzles56.0%25.0%GPT-5.5
EBR-bench34.3%Not measuredOnly GPT-5.5 measured
LMArena Text: hard prompts14891503Muse Spark 1.3
LMArena Text: expert15071519Muse Spark 1.3
LMArena Text: hard prompts in English14831500Muse Spark 1.3
LMArena Vision: diagrams13251330Muse Spark 1.3
LMArena Vision: homework13321296GPT-5.5
Kagi LLM Benchmark88.8%Not measuredOnly GPT-5.5 measured
Neither model has a result on the other 4 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index33
Math benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
OTIS Mock AIME84.4%99.2%Muse Spark 1.3
FrontierMath, tiers 1 to 385.3%74.4%GPT-5.5
FrontierMath, tier 472.5%46.3%GPT-5.5
ProofBench50.0%58.0%Muse Spark 1.3
LMArena Text: math14871497Muse Spark 1.3
LMArena Text: mathematical work14961491GPT-5.5
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
MMLU Pro88.1%Not measuredOnly GPT-5.5 measured
LegalBench (Vals AI)86.5%Not measuredOnly GPT-5.5 measured
CaseLaw (Vals AI)66.2%Not measuredOnly GPT-5.5 measured
CorpFin (Vals AI)68.4%Not measuredOnly GPT-5.5 measured
TaxEval (Vals AI)75.0%Not measuredOnly GPT-5.5 measured
MortgageTax (Vals AI)68.8%Not measuredOnly GPT-5.5 measured
MedCode (Vals AI)49.1%Not measuredOnly GPT-5.5 measured
SimpleQA Verified63.0%Not measuredOnly GPT-5.5 measured
LMArena Text: science14851507Muse Spark 1.3
LMArena Text: medicine and healthcare14651493Muse Spark 1.3
LMArena Text: legal and government14911499Muse Spark 1.3
LMArena Text: business and finance14781490Muse Spark 1.3
FACTS Benchmark Suite66.7%Not measuredOnly GPT-5.5 measured
Neither model has a result on the other 5 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index09
Web design benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
Design Arena: websites12561356Muse Spark 1.3
Design Arena: UI components12571349Muse Spark 1.3
Design Arena: game dev12931328Muse Spark 1.3
Design Arena: data viz12641343Muse Spark 1.3
Design Arena: 3D11971358Muse Spark 1.3
Design Arena: all code categories12601352Muse Spark 1.3
Design Arena: SVG12341301Muse Spark 1.3
Design Arena: ASCII art12551278Muse Spark 1.3
LiveBench design70.3%74.8%Muse Spark 1.3
GeneralLike-for-likePublic boards, shown as published, kept out of the index621
General benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
LiveBench data analysis81.6%79.6%GPT-5.5
Public Benefits Bench (Vals AI)60.9%Not measuredOnly GPT-5.5 measured
SAGE (Vals AI)51.5%Not measuredOnly GPT-5.5 measured
MedScribe (Vals AI)86.9%Not measuredOnly GPT-5.5 measured
Vals Multimodal Index68.1%Not measuredOnly GPT-5.5 measured
IFBench75.9%Not measuredOnly GPT-5.5 measured
Long context reasoning (AA-LCR)84.3%83.0%GPT-5.5
DTBench96.0%96.5%Muse Spark 1.3
LMCA54.3%53.9%GPT-5.5
Surface Evolver Bench88.1%Not measuredOnly GPT-5.5 measured
Furniture assembly44.2%Not measuredOnly GPT-5.5 measured
ExploitBench47.4%Not measuredOnly GPT-5.5 measured
CL-bench Life22.2%Not measuredOnly GPT-5.5 measured
LMArena Text14711490Muse Spark 1.3
LMArena Text: instruction following14781479Muse Spark 1.3
LMArena Text: creative writing14551462Muse Spark 1.3
LMArena Vision12971308Muse Spark 1.3
LMArena Text: English14701495Muse Spark 1.3
LMArena Text: non-English14671481Muse Spark 1.3
LMArena Text: Chinese15341532GPT-5.5
LMArena Text: German14801513Muse Spark 1.3
LMArena Text: Japanese14991470GPT-5.5
LMArena Text: Korean14601490Muse Spark 1.3
LMArena Text: French14851511Muse Spark 1.3
LMArena Text: Spanish14681496Muse Spark 1.3
LMArena Text: Russian14731491Muse Spark 1.3
LMArena Text: Polish14651490Muse Spark 1.3
LMArena Text: multi-turn14761487Muse Spark 1.3
LMArena Text: longer queries14841488Muse Spark 1.3
LMArena Text: writing and language14661470Muse Spark 1.3
LMArena Text: entertainment and media14491457Muse Spark 1.3
LMArena Vision: English12921298Muse Spark 1.3
LMArena Vision: Chinese13601384Muse Spark 1.3
LMArena Vision: reading text13061319Muse Spark 1.3
LMArena Vision: humor12931293Muse Spark 1.3
LMArena Vision: recognizing things1231Not measuredOnly GPT-5.5 measured
LMArena Vision: creative writing13011296GPT-5.5
LMArena Document1486Not measuredOnly GPT-5.5 measured
Neither model has a result on the other 8 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GPT-5.5 and Muse Spark 1.3
BenchmarkGPT-5.5Muse Spark 1.3Leader
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-5.5$0.020Fits in one request
Muse Spark 1.3$0.0034Fits in one request

Muse Spark 1.3 costs less

Repository review

50K input + 3K output tokens

GPT-5.5$0.340Fits in one request
Muse Spark 1.3$0.075Fits in one request

Muse Spark 1.3 costs less

Agent loop

200K input + 10K output tokens

GPT-5.5$1.30Fits in one request
Muse Spark 1.3$0.292Fits in one request

Muse Spark 1.3 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-5.5 and Muse Spark 1.3
SpecificationOpenAI GPT-5.5Meta Muse Spark 1.3
MakerOpenAIMeta
WeightsNo public weights listedNo public weights listed
ReleasedApril 24, 2026September 2, 2026
Context window1.05M1.05M
Input $/Mtok$5.00$1.25
Output $/Mtok$30.00$4.25
Coding index71.357.4
Independent measurements behind it54
Cost per solved task$1.65Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GPT-5.5 better than Muse Spark 1.3 for coding?

Pick GPT-5.5 for coding: it scores 71.3 on the Vibe Coding Index against 57.4 for Muse Spark 1.3. Pick Muse Spark 1.3 for output tokens 7.1x cheaper ($4.25 vs $30.00 per million) and work measured by LiveBench coding or LMArena WebDev, where it leads.

Which is cheaper, GPT-5.5 or Muse Spark 1.3?

GPT-5.5 costs $5.00 per million input tokens and $30.00 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for GPT-5.5 only.

Which has the bigger context window, GPT-5.5 or Muse Spark 1.3?

GPT-5.5, with 1.05M tokens against 1.05M.

How many benchmarks is the GPT-5.5 vs Muse Spark 1.3 comparison based on?

86 benchmarks have a result for both models as of October 22, 2026. GPT-5.5's coding index rests on 5 independent benchmarks and Muse Spark 1.3's on 4. 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-5-5-vs-meta-muse-spark-1-3" title="GPT-5.5 vs Muse Spark 1.3, 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-5-5-vs-meta-muse-spark-1-3">LLMBenchmark.ai, GPT-5.5 vs Muse Spark 1.3</a></p>