BenchLeader

Muse Spark 1.3 vs o3

Full profiles: Muse Spark 1.3 (Meta) and o3 (OpenAI): every benchmark, price and rank.

Updated · Data from 15 sources

As of 2 Nov 2026, Muse Spark 1.3 and o3 are neck and neck on quality (61.9 vs 61.0 on the BenchLeader Index, inside the ±4.8 margin), and Muse Spark 1.3 is 1.8× cheaper at $2.00 vs $3.50 per 1M tokens blended. Choose Muse Spark 1.3 for multimodal (66 vs 57), human preference (69 vs 61), and long context (66 vs 62); choose o3 for fast first answers (6.8 s vs 46.3 s) and maths (71 vs 63), agents & tools (70 vs 66), and coding (62 vs 61).

Key facts (as of 2 Nov 2026)

  • Muse Spark 1.3 scores 61.9 on the BenchLeader Index and o3 scores 61.0 (BenchLeader, 2 Nov 2026).
  • Muse Spark 1.3 costs $2.00 per 1M tokens blended (list price, 2 Nov 2026).
  • o3 costs $3.50 per 1M tokens blended (list price, 2 Nov 2026).
  • Of the 13 benchmarks both models have, Muse Spark 1.3 leads 13 (BenchLeader, 2 Nov 2026).

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
Codingo362 vs 61 category score; Arena Coding 1460 vs 1534Medium
Agents & tool useo370 vs 66 category scoreMedium
Mathso371 vs 63 category score; Arena Maths 1448 vs 1508Medium
ReasoningEither61 vs 61 category score; Arena Hard Prompts 1516 vs 1441Either
KnowledgeMuse Spark 1.359 vs 56 category scoreMedium
Long documentsMuse Spark 1.366 vs 62 category score; AA-LCR v1.1 83.0% vs 74.7%Medium
Images and other mediaMuse Spark 1.366 vs 57 category score; Arena Vision 1308 vs 1214High
Chat quality (human preference)Muse Spark 1.369 vs 61 on Arena votesHigh
Lowest costMuse Spark 1.3$2.00 vs $3.50 per 1M blended; agentic coding session $0.092 vs $0.152–
Fastest first answero36.8 s (o3) vs 46.3 s (Muse Spark 1.3 (max)) to the first answer token–
High volume on a budgetNeither flagshipA smaller model is usually the better fit: Cheapest good LLMs, Fastest LLMs–

Key differences

  • Muse Spark 1.3 (max) and o3 are neck and neck on quality (61.9 vs 61.0, within the ±4.8 margin).
  • Muse Spark 1.3 (max) is stronger in human preference, knowledge, long context, multimodal.
  • o3 is stronger in agents & tools, coding, maths, reasoning, instruction following.
  • Muse Spark 1.3 (max) is 1.8× cheaper ($2.00 vs $3.50 per 1M blended).

At a glance

SpecMuse Spark 1.3o3
DeveloperMetaOpenAI
Released2 Sep 202616 Apr 2025
Context window (tokens)1,048,576200,000
Compared atMuse Spark 1.3 (max)o3
Open weightsNoNo
Price in / out / cached input per 1M$1.25 / $4.25 / $0.150$2.00 / $8.00 / $0.500

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.

CategoryMuse Spark 1.3 (max)o3Leader
Reasoning60.660.9level
Coding60.861.8o3
Agents & tools65.570.3o3
Maths63.170.5o3
Knowledge58.556.1Muse Spark 1.3
Instruction following–65.1not comparable
Human preference68.861.1Muse Spark 1.3
Multimodal65.756.7Muse Spark 1.3
Long context66.462.1Muse Spark 1.3

On one chart

Each domain on the index's own scale, where 50 is an average model. Click a domain to see the benchmarks behind it. Pick up to 5 models from the list.

2550 avg75ReasoningCodingAgents & toolsMathsKnowledgeLong contextMultimodalHumanpreferenceMuse Spark 1.3, Reasoning: 60.6Muse Spark 1.3, Coding: 60.8Muse Spark 1.3, Agents & tools: 65.5Muse Spark 1.3, Maths: 63.1Muse Spark 1.3, Knowledge: 58.5Muse Spark 1.3, Long context: 66.4Muse Spark 1.3, Multimodal: 65.7Muse Spark 1.3, Human preference: 68.8o3, Reasoning: 60.9o3, Coding: 61.8o3, Agents & tools: 70.3o3, Maths: 70.5o3, Knowledge: 56.1o3, Long context: 62.1o3, Multimodal: 56.7o3, Human preference: 61.1

Not drawn, measured for fewer than two of these models: Instruction following.

ModelIndex

Where sources disagree

Across the 13 benchmarks both have, Muse Spark 1.3 leads 13, o3 leads 0. Every overall index that rates both puts Muse Spark 1.3 ahead.

Overall indexMuse Spark 1.3 (max)o3Leader
BenchLeader Index61.961.0neck and neck
Arena Text14951432Muse Spark 1.3

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. Cost, tokens and time per benchmark task are measured: Artificial Analysis’ averages over its whole Intelligence Index run.

MeasureMuse Spark 1.3 (max)o3
Blended price per 1M tokens$2.00$3.50
Input / output per 1M$1.25 / $4.25$2.00 / $8.00
Cached input per 1M$0.150$0.500
Price per task: chat reply$0.0018$0.0032
Price per task: summarize a 30-page report$0.018$0.029
Price per task: code edit$0.014$0.024
Price per task: agentic coding session$0.092$0.152
Price per task: structured extraction$0.0034$0.0056
Agentic coding session, input mostly cached$0.043$0.085
Cost per benchmark task (AA Index)$2.39–
Output tokens per task (AA Index)91k–
Of which reasoning55k–
Time per task (AA Index)8 min–
Output speed194 tok/s160 tok/s
Time to first answer46.3 s6.8 s
Time to a complete answer48.9 s9.9 s

Each model is compared at its best-ranked reasoning-effort setting. Muse Spark 1.3 (max) scores 61.9 and takes 46 s to its first answer token; Muse Spark 1.3 (xhigh) scores 58.5 in 22 s, Muse Spark 1.3 scores 57.8 in 2 s. o3 scores 61.0 and takes 7 s to its first answer token; o3 (high) scores 53.8 in 7 s, o3 (medium) scores 53.3 in 7 s. 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

162 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.

MetricPublisherMuse Spark 1.3 (max)o3
BenchLeader IndexBenchLeader61.961.0
Agents & tools scoreBenchLeader65.570.3
Coding scoreBenchLeader60.861.8
Human preference scoreBenchLeader68.861.1
Knowledge scoreBenchLeader58.556.1
Long context scoreBenchLeader66.462.1
Maths scoreBenchLeader63.170.5
Multimodal scoreBenchLeader65.756.7
Reasoning scoreBenchLeader60.660.9
Instruction following scoreBenchLeader–65.1
Blended price $/MBenchLeader$2.00$3.50
Output speedBenchLeader194 tok/s160 tok/s
Time to first answerBenchLeader46.3 s6.8 s
Context windowBenchLeader1,048,576 tokens200,000 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub–81.8%†
Humanity's Last ExamScale AI / CAIS–20.3%†
SimpleBenchSimpleBench–53.1%†
Arena Hard PromptsArena (LMArena)15161441
LiveBench 2.0 ReasoningLiveBench89.7%†–
LiveBench 1.0 ReasoningLiveBench89.7%†–
GPQA Diamond (AA)Artificial Analysis93.5%82.7%
Humanity's Last Exam (AA)Artificial Analysis48.7%20.1%
HLE-Diamond (AA)Artificial Analysis33.7%–
GPQA Diamond (Vals)Vals AI–84.1%†
Kagi LLM BenchmarkKagi LLM Benchmark–67.6%
GPQA Diamond (HELM)HELM Capabilities–75.3%
ARC-AGI-1ARC Prize–60.8%†
ARC-AGI-2ARC Prize–6.5%†
CritPtArtificial Analysis24.9%1.1%
CritPt v2 hard subset (AA)Artificial Analysis46.0%–
MysteryMechanismVals AI36.0%–
SciPredictScale AI SEAL–17.9%
Chess PuzzlesEpoch AI Benchmarking Hub37.0%36.0%†
Mystery Game PuzzlesEpoch AI Benchmarking Hub25.0%29.0%†
CL-benchEpoch AI Benchmarking Hub–17.8%†
LMCAEpoch AI Benchmarking Hub53.9%†39.7%†
DTBenchEpoch AI Benchmarking Hub96.5%†84.8%†
ForecastBenchForecastBench–64.6%
BTF-3Epoch AI Benchmarking Hub14.1%†–
Show all 162 benchmarks
MetricPublisherMuse Spark 1.3 (max)o3
Coding
SWE-bench Verified (Epoch)Epoch AI Benchmarking Hub–62.3%†
SciCodeSciCode58.8%–
WeirdMLWeirdML–52.4%†
GSO-BenchGSO-Bench–8.8%†
Arena CodingArena (LMArena)15341460
Arena WebDevArena (LMArena)1656–
LiveBench 2.0 CodingLiveBench90.2%†–
LiveBench 1.0 CodingLiveBench81.1%†–
LiveCodeBenchVals AI–83.9%†
IOIVals AI56.6%–
Aider PolyglotAider polyglot leaderboard–81.3%
SWE-bench Verified (bash only)SWE-bench–58.4%
SWE-bench Verified (any scaffold)SWE-bench–58.4%
Code MigrationVals AI47.4%–
ProgramBenchVals AI2.5%–
SWE-bench MultimodalVals AI43.1%–
Vibe Code Bench 1-100Vals AI20.5%–
Vibe Code Bench v1.1Vals AI85.9%–
CadEvalEpoch AI Benchmarking Hub–74.0%†
CursorBenchCursor41.6%–
ALE-BenchEpoch AI Benchmarking Hub1688.3†933.5†
FrontierSWEEpoch AI Benchmarking Hub25.8%–
Terminal-Bench 4.0 (AA)Artificial Analysis33.3%–
Terminal-Bench 2.1 (AA)Artificial Analysis84.3%–
Startrise FrontendStartrise74.7%†–
GameBench 2 OverallDuelLab GameBench 259.7†36.2
GameBench 2 by reasoning settingDuelLab GameBench 270.9†32.0†
FrontierCode 1.1 (AA)Artificial Analysis40.6%–
FrontierCode 2.0 (AA)Artificial Analysis23.1%–
LiveCodeBench (AA)Artificial Analysis–80.8%
Agents & tools
Terminal-BenchTerminal-Bench14.6%†–
GDPvalOpenAI–30.8%†
APEX-AgentsMercor47.6%–
Arena AgentArena (LMArena)2.6–
LiveBench Long AgenticLiveBench25.5%†–
LiveBench BrowserLiveBench30.9%†–
LiveBench Agentic CodingLiveBench64.1%†–
Terminal-Bench HardArtificial Analysis–37.1%
τ²-Bench Telecom (AA)Artificial Analysis–80.7%
Terminal-Bench 2.1 (Vals)Vals AI79.0%–
HiL-BenchScale AI SEAL66.9%†–
BFCL OverallBerkeley Function Calling Leaderboard–63.0%
τ³-Banking (AA)Artificial Analysis50.5%–
ITBench SRE (AA)Artificial Analysis33.2%–
Analyst Agent (AA)Artificial Analysis37.5%–
CUA-benchVals AI5.8%–
CyberBenchVals AI72.7%–
Finance Agent v2Vals AI60.0%–
Harvey's Legal Agent Benchmark v1Vals AI23.8%–
Legal Research BenchVals AI55.3%–
SREBenchVals AI3.8%–
Tax Agent BenchVals AI42.4%–
Terminal-Bench 4.0 (Vals)Vals AI24.8%–
Terminal-Bench ScienceVals AI10.0%–
DeepResearch BenchDeepResearch Bench–45.2%†
METR Time HorizonsMETR–63.6%
AutomationBenchArtificial Analysis57.9%–
GDP.pdf (AA)Artificial Analysis26.6%–
Harvey LAB-AA v1.1Harvey8.9%–
AA-Briefcase v1.1Artificial Analysis1581–
Terminal-Bench-Science 0.1 (AA)Artificial Analysis10.9%–
BrowseComp-PlusBrowseComp-Plus–50.5%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub74.0%33.3%†
FrontierMath Tier 4Epoch AI Benchmarking Hub46.3%–
OTIS Mock AIMEEpoch AI Benchmarking Hub99.2%†83.9%†
MATH Level 5Epoch AI Benchmarking Hub–97.8%†
ProofBenchVals AI58.0%–
LiveBench MathematicsLiveBench96.0%†–
AIME (Vals)Vals AI–85.3%†
MGSMVals AI–91.8%†
IMO 2025MathArena–16.7%†
Omni-MATH (HELM)HELM Capabilities–71.4%
MATH 500Vals AI–94.6%†
Arena MathsArena (LMArena)15081448
AIME 2025 (AA)Artificial Analysis–88.3%
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub–49.4%†
LiveBench 2.0 Data AnalysisLiveBench79.6%†–
LiveBench ResearchLiveBench68.6%†–
LiveBench 1.0 Data AnalysisLiveBench79.6%†–
AA-Omniscience v1.1Artificial Analysis22.4–
MMLU-ProVals AI–85.6%†
LegalBenchVals AI–83.8%†
CorpFinVals AI–59.7%†
TaxEvalVals AI–74.6%†
MedQAVals AI–96.1%†
PRBench FinanceScale AI SEAL59.5%†47.7%
PRBench LegalScale AI SEAL61.6%†48.6%
MultiNRCScale AI SEAL–45.5%†
MMLU-Pro (HELM)HELM Capabilities–85.9%
Excel Modeling BenchmarkVals AI67.4%–
MedCodeVals AI–47.3%†
MedScribeVals AI–76.7%†
DrugDiscoveryBenchScale AI SEAL62.2%†–
GDP.pdfEpoch AI Benchmarking Hub27.6%†–
AA-Omniscience v1.1: accuracyArtificial Analysis38.0%–
AA-Omniscience v1.1: non-hallucinationArtificial Analysis74.8%–
Instruction following
LiveBench LanguageLiveBench82.8%†–
LiveBench Instruction FollowingLiveBench78.0%†–
IFBenchArtificial Analysis–71.4%
MultiChallengeScale AI SEAL–56.6%†
TutorBenchScale AI SEAL–52.1%†
IFEval (HELM)HELM Capabilities–86.9%
WildBench (HELM)HELM Capabilities–86.1%
Arena Instruction FollowingArena (LMArena)14831403
Human preference
Arena TextArena (LMArena)14951432
Arena Creative WritingArena (LMArena)14641383
Arena Multi-turnArena (LMArena)14931420
Arena Longer QueriesArena (LMArena)14961411
Lech Mazur Creative WritingLech Mazur–83.9%†
Multimodal
Arena VisionArena (LMArena)13081214
LiveBench DesignLiveBench74.8%†–
MMMU-ProArtificial Analysis82.0%†70.1%
VISTAScale AI SEAL–50.1%†
MMMU (validation)MMMU–82.9%
MMMU-Pro (official)MMMU–76.4%
MMMU-Pro (Vals)Vals AI–80.4%†
MortgageTaxVals AI–65.7%†
VTBScale AI SEAL–13.7%
GeoBenchGeoBench–60.0%†
VPCTEpoch AI Benchmarking Hub–52.0%†
Code2Video-AAArtificial Analysis1019–
AA-3DArtificial Analysis1033–
Long context
Fiction.LiveBench 120kFiction.live–100.0%†
AA-LCR v1.1Artificial Analysis83.0%74.7%
Arena DocumentArena (LMArena)1468–
MLCRArtificial Analysis13.9%–
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.4†146.9
LiveBench 2.0LiveBench63.0%†–
LiveBench 1.0LiveBench81.6%†–
AA Intelligence Index v5.0Artificial Analysis36.4–
AA Intelligence Index v4.3.2Artificial Analysis48.120.2
AA Progress Index v1Artificial Analysis324.5258.3
HELM Capabilities meanHELM Capabilities–81.1%
Vals RSI IndexVals AI19.6%–
Safety & honesty
FORTRESSScale AI SEAL–16.0%
MASKScale AI SEAL–84.5%†
PropensityBenchScale AI SEAL–10.5%

Data as of 2026-11-02. Best configuration of each model; every score links to its source on the model pages.

DuelLab GameBench 2, release gb2-20261026-cb69502a12d9 (https://benchmarks.duellab.org/releases/gb2-20261026-cb69502a12d9/), CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/). Scores mapped to BenchLeader model names; not endorsed by DuelLab.

What changed

  • Muse Spark 1.3 (max): 1 score revision.
  • Muse Spark 1.3 (max): BenchLeader Index 64.5 → 61.8.
  • Muse Spark 1.3 (max): 5 new results (AA Intelligence Index v5.0, AA Progress Index v1, HLE-Diamond (AA)…); 3 score revisions; cost per task moved from $1.31/M to $2.39/M (81% up).
  • o3: 1 new result (AA Progress Index v1).
  • Muse Spark 1.3 (max): cost per task moved from $3.69/M to $1.31/M (64% down).
  • Muse Spark 1.3 (max): cost per task moved from $1.60/M to $3.69/M (130% up).
  • Muse Spark 1.3 (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, SWE-bench Multimodal); 1 score revision.
  • Muse Spark 1.3 (max): 1 score revision.
  • Muse Spark 1.3 (max): 1 score revision.
  • o3: 1 score revision.

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

Muse Spark 1.3 vs o3: questions

Is Muse Spark 1.3 better than o3?
Muse Spark 1.3 (max) and o3 are neck and neck on quality (61.9 vs 61.0, within the ±4.8 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2 Nov 2026, so check the category scores for your use.
Muse Spark 1.3 vs o3: which is cheaper, and will that change?
Muse Spark 1.3 is cheaper today: $2.00 against $3.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Is Muse Spark 1.3 or o3 better for coding?
o3 scores higher in coding (62 vs 61 on the category index, where 50 is average). On Arena Coding, the top shared coding benchmark, it is 1534 for Muse Spark 1.3 against 1460 for o3.
Which is faster, Muse Spark 1.3 or o3?
Muse Spark 1.3 streams faster (194 vs 160 output tokens per second, Artificial Analysis 7-day median).
Is Muse Spark 1.3 or o3 better for agents and tool use?
o3 scores higher in agentic tasks (70 vs 66 on the category index, where 50 is average).
More questions (4)
Which is better for long documents?
Muse Spark 1.3 scores higher on long-context benchmarks (66 vs 62). Muse Spark 1.3 accepts more context: 1,048,576 against 200,000 tokens for o3.
Which has lower latency?
o3 answers first: 6.8 s against 46.3 s to the first answer token, as Artificial Analysis measures it. Reasoning effort drives most of this: a higher setting thinks longer before it answers.
Do independent benchmarks agree on Muse Spark 1.3 vs o3?
Across the 13 benchmarks both have, Muse Spark 1.3 leads 13, o3 leads 0. Every overall index that rates both puts Muse Spark 1.3 ahead.
When was Muse Spark 1.3 released?
Muse Spark 1.3 was released on 2 Sep 2026.