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GPT-5.2 vs Muse Wonder Full

Full profiles: GPT-5.2 (OpenAI) and Muse Wonder Full (Meta): every benchmark, price and rank.

Updated · Data from 8 sources

As of 21 Oct 2026, Muse Wonder Full (max) is the better pick for most workloads: it leads on quality (70.7 vs 60.7 on the BenchLeader Index). Muse Wonder Full leads in every category we measure both in.

GPT-5.2 benchmarks xhigh OpenAI Muse Wonder Full benchmarks max MetaOpen in the comparison tool

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 63 category score; Vibe Code Bench v1.1 86.0% vs 53.5%High
ReasoningMuse Wonder Full95 vs 61 category score; CritPt 32.9% vs 11.6%High
KnowledgeMuse Wonder Full71 vs 57 category score; AA-Omniscience 30.1 vs -0.9High
Long documentsEither67 vs 67 category score; AA-LCR 82.7% 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: 70.7 vs 60.7.
  • GPT-5.2 (xhigh) is stronger in agents & tools, instruction following, maths.
  • Muse Wonder Full (max) is stronger in coding, composite, knowledge, long context, reasoning.

At a glance

SpecGPT-5.2Muse Wonder Full
DeveloperOpenAIMeta
Released11 Dec 202512 Oct 2026
Context window (tokens)400,0001,000,000
Compared atGPT-5.2 (xhigh)Muse Wonder Full (max)
Open weightsNoNo
Price in / out / cached input per 1M$1.75 / $14.00 / $0.175–

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-5.2 (xhigh)Muse Wonder Full (max)Leader
Reasoning60.795.0Muse Wonder Full
Coding62.972.1Muse Wonder Full
Agents & tools55.0–not comparable
Maths56.9–not comparable
Knowledge57.171.3Muse Wonder Full
Instruction following73.9–not comparable
Long context66.567.0level
Composite63.792.1Muse Wonder Full

Where sources disagree

Across the 10 benchmarks both have, GPT-5.2 leads 1, Muse Wonder Full leads 9. Every overall index that rates both puts Muse Wonder Full ahead.

Overall indexGPT-5.2 (xhigh)Muse Wonder Full (max)Leader
BenchLeader Index60.770.7Muse Wonder Full
AA Intelligence Index v4.3.230.455.8Muse 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-5.2 (xhigh)Muse Wonder Full (max)
Blended price per 1M tokens$4.81–
Input / output per 1M$1.75 / $14.00– / –
Cached input per 1M$0.175–
Price per task: chat reply$0.0049–
Price per task: summarize a 30-page report$0.029–
Price per task: code edit$0.032–
Price per task: agentic coding session$0.161–
Price per task: structured extraction$0.0063–
Output speed80 tok/s–
Time to first answer89.9 s–
Time to a complete answer96.1 s–

Each model is compared at its best-ranked reasoning-effort setting. GPT-5.2 (xhigh) scores 60.7 and takes 90 s to its first answer token; GPT-5.2 scores 58.0 in 3 s, GPT-5.2 (medium) scores 57.6 in 3 s. Muse Wonder Full (max) scores 70.7. 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

126 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-5.2 (xhigh)Muse Wonder Full (max)
BenchLeader IndexBenchLeader60.770.7
Agents & tools scoreBenchLeader55.0–
Coding scoreBenchLeader62.972.1
Composite scoreBenchLeader63.792.1
Instruction following scoreBenchLeader73.9–
Knowledge scoreBenchLeader57.171.3
Long context scoreBenchLeader66.567.0
Maths scoreBenchLeader56.9–
Reasoning scoreBenchLeader60.795.0
Blended price $/MBenchLeader$4.81–
Output speedBenchLeader80 tok/s–
Time to first answerBenchLeader89.9 s–
Context windowBenchLeader400,000 tokens1,000,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub91.4%–
Humanity's Last ExamScale AI / CAIS27.8%†–
SimpleBenchSimpleBench45.8%†–
Arena Hard PromptsArena (LMArena)1496†–
LiveBench 1.0 ReasoningLiveBench83.2%†–
GPQA Diamond (AA)Artificial Analysis90.3%–
Humanity's Last Exam (AA)Artificial Analysis37.7%53.6%
GPQA Diamond (Vals)Vals AI91.7%–
Kagi LLM BenchmarkKagi LLM Benchmark73.3%†–
ARC-AGI-1ARC Prize86.2%–
ARC-AGI-2ARC Prize52.9%–
CritPtArtificial Analysis11.6%32.9%
MysteryMechanismVals AI–35.1%
SciPredictScale AI SEAL20.6%†–
Chess PuzzlesEpoch AI Benchmarking Hub48.0%–
Mystery Game PuzzlesEpoch AI Benchmarking Hub22.0%†–
CL-benchEpoch AI Benchmarking Hub18.2%†–
LMCAEpoch AI Benchmarking Hub43.9%–
DTBenchEpoch AI Benchmarking Hub90.9%–
ForecastBenchForecastBench64.2%†–
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub73.8%†–
WeirdMLWeirdML72.2%–
GSO-BenchGSO-Bench27.4%†–
Arena CodingArena (LMArena)1514†–
Arena WebDevArena (LMArena)1417†1726
Show all 126 benchmarks
MetricPublisherGPT-5.2 (xhigh)Muse Wonder Full (max)
Coding
LiveBench 1.0 CodingLiveBench76.1%†–
SciCode (AA)Artificial Analysis–62.6%
LiveCodeBenchVals AI85.4%–
IOIVals AI–79.8%
SWE-bench (Vals)Vals AI75.8%–
SWE-Bench ProScale AI SEAL29.9%†–
SWE-bench Verified (bash only)SWE-bench69.0%†–
SWE-bench Verified (any scaffold)SWE-bench72.8%†–
Code MigrationVals AI–61.0%
ProgramBenchVals AI–0.5%
Vibe Code Bench 1-100Vals AI–34.0%
Vibe Code Bench v1.1Vals AI53.5%86.0%
SWE-Bench Pro (private)Scale AI SEAL29.9%†–
ALE-BenchEpoch AI Benchmarking Hub1249.8†–
AlgoTuneAlgoTune2.0†–
Terminal-Bench 4.0 (AA)Artificial Analysis–57.1%
FrontierCode 1.1 (AA)Artificial Analysis–44.9%
Agents & tools
Terminal-BenchTerminal-Bench64.9%†–
GDPvalOpenAI49.7%†–
Remote Labor IndexScale AI / CAIS2.1%†–
LiveBench Agentic CodingLiveBench50.3%†–
Terminal-Bench HardArtificial Analysis47.0%–
τ²-Bench Telecom (AA)Artificial Analysis84.8%–
MCP AtlasScale AI SEAL67.6%–
BFCL OverallBerkeley Function Calling Leaderboard55.9%†–
τ²-benchτ²-bench84.8%†–
τ³-bench Bankingτ²-bench32.2%†–
GDPval-AA v2.1Artificial Analysis–67.8%
τ³-Banking (AA)Artificial Analysis11.1%†–
CyberBenchVals AI–73.6%
Finance Agent v2Vals AI–59.1%
Harvey's Legal Agent BenchmarkVals AI–23.3%
Legal Research BenchVals AI–53.4%
Poker AgentVals AI1131.8%†–
SREBenchVals AI–11.8%
Tax Agent BenchVals AI–43.0%
Terminal-Bench 2.0 (Vals)Vals AI51.7%†–
Terminal-Bench 4.0 (Vals)Vals AI–58.1%
Terminal-Bench ScienceVals AI–37.1%
DeepResearch BenchDeepResearch Bench41.1%†–
METR Time HorizonsMETR75.3%†–
Vending-Bench 2Andon Labs3591.3†–
AutomationBenchArtificial Analysis–71.3%
GDP.pdf (AA)Artificial Analysis–32.6%
Harvey LAB-AA v1.1Harvey–13.1%
AA-Briefcase v1.1Artificial Analysis–1729
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub67.4%–
FrontierMath Tier 4Epoch AI Benchmarking Hub31.7%–
OTIS Mock AIMEEpoch AI Benchmarking Hub96.1%–
ProofBenchVals AI15.0%–
LiveBench MathematicsLiveBench93.2%†–
AIME (Vals)Vals AI96.9%–
MGSMVals AI94.0%–
AIME 2026MathArena98.3%†–
HMMT February 2026MathArena97.0%†–
MathArena ApexMathArena13.5%†–
Arena MathsArena (LMArena)1454†–
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub37.1%–
LiveBench 1.0 Data AnalysisLiveBench78.2%†–
AA-OmniscienceArtificial Analysis-0.930.1
MMLU-ProVals AI86.2%–
LegalBenchVals AI82.8%87.4%
CorpFinVals AI65.9%–
TaxEvalVals AI75.8%–
MedQAVals AI94.1%–
MultiNRCScale AI SEAL42.2%†–
BioMysteryBenchVals AI–73.3%
CaseLaw v2Vals AI66.0%–
Excel Modeling BenchmarkVals AI–71.9%
MedCodeVals AI49.8%49.9%
MedScribeVals AI84.4%89.3%
Public Benefits BenchVals AI–73.8%
DrugDiscoveryBenchScale AI SEAL29.3%–
EBR-benchEpoch AI Benchmarking Hub23.0%–
AA-Omniscience: accuracyArtificial Analysis44.3%43.2%
AA-Omniscience: non-hallucinationArtificial Analysis18.8%77.0%
Instruction following
LiveBench LanguageLiveBench79.8%†–
LiveBench Instruction FollowingLiveBench61.8%†–
IFBenchArtificial Analysis75.4%–
TutorBenchScale AI SEAL53.5%†–
Arena Instruction FollowingArena (LMArena)1457†–
Human preference
Arena TextArena (LMArena)1476†–
Arena Creative WritingArena (LMArena)1433†–
Arena Multi-turnArena (LMArena)1495†–
Arena Longer QueriesArena (LMArena)1472†–
Multimodal
Arena VisionArena (LMArena)1268†–
MMMU-ProArtificial Analysis74.6%†–
VISTAScale AI SEAL46.6%†–
MMMU-Pro (Vals)Vals AI86.7%–
MortgageTaxVals AI67.1%–
SAGEVals AI49.3%–
VPCTEpoch AI Benchmarking Hub84.0%–
Long context
AA-LCRArtificial Analysis82.7%83.7%
Arena DocumentArena (LMArena)1425†–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub153.7†–
LiveBench 1.0LiveBench74.6%†–
AA Intelligence Index v4.3.2Artificial Analysis30.455.8
Vals IndexVals AI–66.8
Safety & honesty
FORTRESSScale AI SEAL17.5%†–
MASKScale AI SEAL86.7%†–
PropensityBenchScale AI SEAL34.4%†–

Data as of 2026-10-21. Best configuration of each model; every score links to its source on the model pages.

What changed

  • 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.
  • Muse Wonder Full (max): 21 new results (IOI, LegalBench, Vals Index…).
  • GPT-5.2 (xhigh): 1 score revision.
  • Muse Wonder Full (max): 1 new result (Harvey LAB-AA v1.1).
  • Muse Wonder Full (max): first results.
  • GPT-5.2 (xhigh): 1 new result (DrugDiscoveryBench).
  • GPT-5.2 (xhigh): BenchLeader Index 61.3 → 60.8.
  • GPT-5.2 (xhigh): BenchLeader Index 63.5 → 61.3.

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

GPT-5.2 vs Muse Wonder Full: questions

Is GPT-5.2 better than Muse Wonder Full?
Muse Wonder Full (max) leads on quality: 70.7 vs 60.7. The BenchLeader Index combines every independent quality benchmark; Muse Wonder Full (max) is ahead overall as of 2026-10-21, but check the category scores for your use.
Is GPT-5.2 better than Muse Wonder Full for coding?
Muse Wonder Full scores higher in coding (72 vs 63 on the category index, where 50 is average).
Which is better for long documents?
They are level on long-context benchmarks (67 vs 67). Muse Wonder Full accepts more context: 1,000,000 against 400,000 tokens for GPT-5.2.
Do independent benchmarks agree on GPT-5.2 vs Muse Wonder Full?
Across the 10 benchmarks both have, GPT-5.2 leads 1, Muse Wonder Full leads 9. 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.