BenchLeader

GPT-5.6 Luna vs Muse Wonder Full

Full profiles: GPT-5.6 Luna (OpenAI) and Muse Wonder Full (Meta): every benchmark, price and rank.

Updated · Data from 9 sources

As of 25 Oct 2026, Muse Wonder Full (max) is the better pick for most workloads: it leads on quality (70.6 vs 59.9 on the BenchLeader Index). Muse Wonder Full leads in every category we measure both in.

Which to pick for…

The pick's numbers come first. Category scores on the BenchLeader scale (50 is the average model, 15 points one standard deviation). High confidence means a lead of half a standard deviation or more; under one point is called either.

Use casePickWhyConfidence
CodingMuse Wonder Full72 vs 56 category score; IOI 79.8% vs 61.8%High
ReasoningMuse Wonder Full95 vs 63 category score; CritPt 32.9% vs 20.6%High
KnowledgeMuse Wonder Full71 vs 57 category score; AA-Omniscience 30.1 vs -10.3High
Long documentsEither67 vs 67 category score; AA-LCR 83.7% vs 83.7%Either
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Muse Wonder Full (max) leads on quality: 70.6 vs 59.9.
  • GPT-5.6 Luna (max) is stronger in agents & tools, maths, multimodal.
  • Muse Wonder Full (max) is stronger in coding, composite, knowledge, reasoning.

At a glance

SpecGPT-5.6 LunaMuse Wonder Full
DeveloperOpenAIMeta
Released9 Jul 202612 Oct 2026
Context window (tokens)1,050,0001,000,000
Compared atGPT-5.6 Luna (max)Muse Wonder Full (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.200 / $1.20 / $0.020–

Category by category

Category scores on the BenchLeader scale: 50 is the average evaluated model, 15 points is one standard deviation. A gap under one point is called level.

CategoryGPT-5.6 Luna (max)Muse Wonder Full (max)Leader
Reasoning62.994.9Muse Wonder Full
Coding56.072.1Muse Wonder Full
Agents & tools49.0–not comparable
Maths65.0–not comparable
Knowledge56.571.4Muse Wonder Full
Multimodal61.6–not comparable
Long context67.067.0level
Composite71.291.9Muse Wonder Full

Where sources disagree

Across the 33 benchmarks both have, GPT-5.6 Luna leads 0, Muse Wonder Full leads 31 and 2 are tied. Every overall index that rates both puts Muse Wonder Full ahead.

Overall indexGPT-5.6 Luna (max)Muse Wonder Full (max)Leader
BenchLeader Index59.970.6Muse Wonder Full
AA Intelligence Index v4.3.237.355.8Muse Wonder Full

Each publisher runs its own tasks, harnesses and effort settings, so their overall verdicts can differ; BenchLeader reconciles them on one scale. † measured at another effort setting of the same model (the publisher did not test the one compared here).

Price, speed and latency

List prices blended at three input tokens per output token. Per-task prices use the token counts on the methodology page; suite cost is what Artificial Analysis paid to run its whole Intelligence Index.

MeasureGPT-5.6 Luna (max)Muse Wonder Full (max)
Blended price per 1M tokens$0.450–
Input / output per 1M$0.200 / $1.20– / –
Cached input per 1M$0.020–
Price per task: chat reply$0.0004–
Price per task: summarize a 30-page report$0.0031–
Price per task: code edit$0.0030–
Price per task: agentic coding session$0.017–
Price per task: structured extraction$0.0006–
Cost to run a full benchmark suite$0.178–
Output speed126 tok/s–
Time to first answer62.0 s–
Time to a complete answer65.9 s–

Each model is compared at its best-ranked reasoning-effort setting. GPT-5.6 Luna (max) scores 59.9 and takes 62 s to its first answer token; GPT-5.6 Luna (xhigh) scores 59.7 in 24 s, GPT-5.6 Luna (high) scores 57.0 in 7 s. Muse Wonder Full (max) scores 70.6. Higher effort means more thinking before the answer: better scores, longer waits and more tokens billed. How reasoning effort changes scores and cost.

Every benchmark

125 benchmarks, grouped by category; each name links to the board and its leaders. † measured at another effort setting of the same model, shown for reference and not counted as a win.

MetricPublisherGPT-5.6 Luna (max)Muse Wonder Full (max)
BenchLeader IndexBenchLeader59.970.6
Agents & tools scoreBenchLeader49.0–
Coding scoreBenchLeader56.072.1
Composite scoreBenchLeader71.291.9
Knowledge scoreBenchLeader56.571.4
Long context scoreBenchLeader67.067.0
Maths scoreBenchLeader65.0–
Multimodal scoreBenchLeader61.6–
Reasoning scoreBenchLeader62.994.9
Blended price $/MBenchLeader$0.450–
Output speedBenchLeader126 tok/s–
Time to first answerBenchLeader62.0 s–
Context windowBenchLeader1,050,000 tokens1,000,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub91.6%–
SimpleBenchSimpleBench46.8%†–
Arena Hard PromptsArena (LMArena)1475†–
LiveBench 2.0 ReasoningLiveBench85.6%†–
LiveBench 1.0 ReasoningLiveBench85.6%–
GPQA Diamond (AA)Artificial Analysis91.1%–
Humanity's Last Exam (AA)Artificial Analysis39.5%53.6%
GPQA Diamond (Vals)Vals AI91.7%–
Kagi LLM BenchmarkKagi LLM Benchmark49.1%†–
ARC-AGI-1ARC Prize90.7%–
ARC-AGI-2ARC Prize59.6%–
ARC-AGI-3ARC Prize0.2%–
CritPtArtificial Analysis20.6%32.9%
MysteryMechanismVals AI14.4%35.1%
Chess PuzzlesEpoch AI Benchmarking Hub43.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub21.0%–
LMCAEpoch AI Benchmarking Hub48.5%–
DTBenchEpoch AI Benchmarking Hub88.8%–
Coding
SciCodeSciCode53.6%–
WeirdMLWeirdML60.9%†–
FrontierCodeCognition39.8%†–
Arena CodingArena (LMArena)1502†–
Arena WebDevArena (LMArena)1519†1726
LiveBench 2.0 CodingLiveBench73.6%†–
LiveBench 1.0 CodingLiveBench82.9%–
Show all 125 benchmarks
MetricPublisherGPT-5.6 Luna (max)Muse Wonder Full (max)
Coding
SciCode (AA)Artificial Analysis53.6%62.6%
IOIVals AI61.8%79.8%
SWE-bench (Vals)Vals AI93.0%–
Code MigrationVals AI44.5%61.0%
Code Migration v1.1Vals AI–62.8%
ProgramBenchVals AI0.0%0.5%
SWE-bench MultimodalVals AI–47.3%
Vibe Code Bench 1-100Vals AI22.6%34.0%
Vibe Code Bench v1.1Vals AI77.1%86.0%
Surface Evolver BenchEpoch AI Benchmarking Hub61.9%†–
DeepSWE v1.1Epoch AI Benchmarking Hub67.2%–
CursorBenchCursor35.9%–
ALE-BenchEpoch AI Benchmarking Hub1667.4–
Terminal-Bench 4.0 (AA)Artificial Analysis11.6%57.1%
Terminal-Bench 2.1 (AA)Artificial Analysis80.9%–
Startrise FrontendStartrise65.0%†–
FrontierCode 1.1 (AA)Artificial Analysis–44.9%
Agents & tools
Terminal-BenchTerminal-Bench17.3%–
APEX-AgentsMercor43.0%†–
LiveBench Long AgenticLiveBench30.4%†–
LiveBench BrowserLiveBench68.0%†–
LiveBench Agentic CodingLiveBench48.4%–
Terminal-Bench 2.1 (Vals)Vals AI79.0%–
GDPval-AA v2.1Artificial Analysis–67.8%
τ³-Banking (AA)Artificial Analysis31.1%–
ITBench SRE (AA)Artificial Analysis40.3%–
APEX-Agents (AA)Artificial Analysis35.8%–
CyberBenchVals AI73.6%73.6%
Finance Agent v2Vals AI55.0%59.1%
Finance Agent v2.1Vals AI–67.6%
Harvey's Legal Agent Benchmark v1.1Vals AI–23.3%
Harvey's Legal Agent Benchmark v1Vals AI1.3%21.7%
Legal Research BenchVals AI36.5%53.4%
Robo-benchVals AI–10.4%
SkillsBenchVals AI60.5%–
SREBenchVals AI1.5%11.8%
Tax Agent BenchVals AI24.8%43.0%
Terminal-Bench 4.0 (Vals)Vals AI11.6%58.1%
Terminal-Bench ScienceVals AI0.0%37.1%
BALROGBALROG45.6%–
Vending-Bench 2Andon Labs4094.7†–
AutomationBenchArtificial Analysis50.2%71.3%
GDP.pdf (AA)Artificial Analysis24.0%32.6%
Harvey LAB-AA v1.1Harvey–13.1%
EnterpriseOps-GymArtificial Analysis40.8%–
AA-Briefcase v1.1Artificial Analysis13391729
Terminal-Bench-Science 0.1 (AA)Artificial Analysis3.3%37.1%
FACTS SearchGoogle79.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub82.1%–
FrontierMath Tier 4Epoch AI Benchmarking Hub61.0%–
OTIS Mock AIMEEpoch AI Benchmarking Hub98.3%–
ProofBenchVals AI60.0%–
LiveBench MathematicsLiveBench87.2%–
Arena MathsArena (LMArena)1478†–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub41.0%–
LiveBench 2.0 Data AnalysisLiveBench78.0%†–
LiveBench ResearchLiveBench51.0%†–
LiveBench 1.0 Data AnalysisLiveBench78.0%–
AA-OmniscienceArtificial Analysis-10.330.1
MMLU-ProVals AI86.0%–
LegalBenchVals AI84.0%87.4%
CorpFinVals AI64.2%–
TaxEvalVals AI76.2%–
BioMysteryBenchVals AI61.5%73.3%
Excel Modeling BenchmarkVals AI67.1%71.9%
Excel Modeling Benchmark v1.1Vals AI–75.0%
MedCodeVals AI42.4%49.9%
MedScribeVals AI84.4%89.3%
Public Benefits Bench v1.1Vals AI61.2%73.8%
GDP.pdfEpoch AI Benchmarking Hub22.7%†–
AA-Omniscience: accuracyArtificial Analysis42.7%43.2%
AA-Omniscience: non-hallucinationArtificial Analysis7.4%77.0%
Instruction following
LiveBench LanguageLiveBench72.6%–
LiveBench Instruction FollowingLiveBench60.1%–
Arena Instruction FollowingArena (LMArena)1444†–
Human preference
Arena TextArena (LMArena)1453†–
EQ-Bench 4EQ-Bench1149†–
Arena Creative WritingArena (LMArena)1410†–
Arena Multi-turnArena (LMArena)1459†–
Arena Longer QueriesArena (LMArena)1452†–
Multimodal
Arena VisionArena (LMArena)1257†–
LiveBench DesignLiveBench76.0%†–
MMMU-ProArtificial Analysis78.5%–
MMMU-Pro (Vals)Vals AI85.0%–
MortgageTaxVals AI67.3%–
SAGEVals AI44.2%–
Blueprint-Bench 2Epoch AI Benchmarking Hub22.6%†–
Long context
AA-LCRArtificial Analysis83.7%83.7%
Arena DocumentArena (LMArena)1462†–
MLCRArtificial Analysis20.0%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub156.5†–
LiveBench 2.0LiveBench66.1%†–
LiveBench 1.0LiveBench73.6%–
AA Intelligence Index v4.3.2Artificial Analysis37.355.8
Vals IndexVals AI–66.8
Vals Finance IndexVals AI–64.5%
Vals RSI IndexVals AI–24.4%
Vals Science IndexVals AI25.3%48.5%
Vals Multimodal IndexVals AI69.1%–
Vals Router IndexVals AI–66.8%†

Data as of 2026-10-25. Best configuration of each model; every score links to its source on the model pages.

What changed

  • GPT-5.6 Luna (max): 1 new result (AA-Briefcase v1.1).
  • Muse Wonder Full (max): 1 new result (Terminal-Bench-Science 0.1 (AA)).
  • GPT-5.6 Luna (max): 2 new results (Harvey's Legal Agent Benchmark v1, Vals Science Index).
  • Muse Wonder Full (max): 9 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
  • GPT-5.6 Luna (max): 1 score revision.
  • Muse Wonder Full (max): 1 new result (FrontierCode 1.1 (AA)).
  • Muse Wonder Full (max): BenchLeader Index 68.6 → 70.7.
  • Muse Wonder Full (max): 1 new result (Arena WebDev); 2 score revisions.
  • GPT-5.6 Luna (max): BenchLeader Index 58.8 → 59.9.
  • GPT-5.6 Luna (max): 5 new results (AutomationBench, GDP.pdf (AA), MLCR…).

Rankings: Best LLM overall · Best LLM for coding · Best LLM for agents · Best cheap LLMs

GPT-5.6 Luna vs Muse Wonder Full: questions

Is GPT-5.6 Luna better than Muse Wonder Full?
Muse Wonder Full (max) leads on quality: 70.6 vs 59.9. The BenchLeader Index combines every independent quality benchmark; Muse Wonder Full (max) is ahead overall as of 2026-10-25, but check the category scores for your use.
Is GPT-5.6 Luna better than Muse Wonder Full for coding?
Muse Wonder Full scores higher in coding (72 vs 56 on the category index, where 50 is average). On IOI, the top shared coding benchmark, it is 61.8% for GPT-5.6 Luna against 79.8% for Muse Wonder Full.
Which is better for long documents?
They are level on long-context benchmarks (67 vs 67). Both take about 1.1M tokens: GPT-5.6 Luna 1,050,000, Muse Wonder Full 1,000,000.
Do independent benchmarks agree on GPT-5.6 Luna vs Muse Wonder Full?
Across the 33 benchmarks both have, GPT-5.6 Luna leads 0, Muse Wonder Full leads 31 and 2 are tied. Every overall index that rates both puts Muse Wonder Full ahead.
When was Muse Wonder Full released?
Muse Wonder Full was released on 12 Oct 2026.