BenchLeader

GPT-5.4 Pro vs Muse Spark 1.3

Full profiles: GPT-5.4 Pro (OpenAI) and Muse Spark 1.3 (Meta): every benchmark, price and rank.

Updated · Data from 7 sources

As of 24 Oct 2026, GPT-5.4 Pro and Muse Spark 1.3 (max) are neck and neck on quality (63.3 vs 67.1 on the BenchLeader Index, inside the ±5.6 margin of error), and Muse Spark 1.3 (max) costs 34× less, which makes it the better buy for most workloads. Pick GPT-5.4 Pro for multimodal (70 vs 66); pick Muse Spark 1.3 for reasoning (77 vs 73).

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
ReasoningMuse Spark 1.377 vs 73 category scoreMedium
KnowledgeEither74 vs 73 category scoreEither
Images and other mediaGPT-5.4 Pro70 vs 66 category scoreMedium
Chat quality (human preference)–Only Muse Spark 1.3 has an Arena rating (69 category score)Not comparable
Lowest costMuse Spark 1.3$2.00 vs $67.50 per 1M blended; agentic coding session $0.092 vs $2.52–
Fastest first answerGPT-5.4 Pro6.1 s (GPT-5.4 Pro) vs 90.1 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

  • GPT-5.4 Pro and Muse Spark 1.3 (max) are neck and neck on quality (63.3 vs 67.1, within the ±5.6 margin).
  • GPT-5.4 Pro is stronger in instruction following, knowledge, multimodal.
  • Muse Spark 1.3 (max) is stronger in reasoning, agents & tools, coding, composite, human preference, long context, maths.
  • Muse Spark 1.3 (max) is 34× cheaper ($2.00 vs $67.50 per 1M blended).
  • Muse Spark 1.3 (max) streams 16.6× faster (116 vs 7 tokens per second).

At a glance

SpecGPT-5.4 ProMuse Spark 1.3
DeveloperOpenAIMeta
Released4 Mar 20262 Sept 2026
Context window (tokens)1,050,0001,048,576
Compared atGPT-5.4 ProMuse Spark 1.3 (max)
Open weightsNoNo
Price in / out / cached input per 1M$30.00 / $180.00 / –$1.25 / $4.25 / $0.150

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-5.4 ProMuse Spark 1.3 (max)Leader
Reasoning72.577.4Muse Spark 1.3
Coding–64.5not comparable
Agents & tools–65.6not comparable
Maths–63.4not comparable
Knowledge73.672.8level
Instruction following63.8–not comparable
Human preference–69.1not comparable
Multimodal69.865.7GPT-5.4 Pro
Long context–66.6not comparable
Composite–83.3not comparable

Where sources disagree

Across the 0 benchmarks both have, GPT-5.4 Pro leads 0, Muse Spark 1.3 leads 0.

Overall indexGPT-5.4 ProMuse Spark 1.3 (max)Leader
BenchLeader Index63.367.1neck and neck

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-5.4 ProMuse Spark 1.3 (max)
Blended price per 1M tokens$67.50$2.00
Input / output per 1M$30.00 / $180.00$1.25 / $4.25
Cached input per 1M–$0.150
Price per task: chat reply$0.066$0.0018
Price per task: summarize a 30-page report$0.468$0.018
Price per task: code edit$0.450$0.014
Price per task: agentic coding session$2.52$0.092
Price per task: structured extraction$0.096$0.0034
Cost to run a full benchmark suite–$1.60
Output speed7 tok/s116 tok/s
Time to first answer6.1 s90.1 s
Time to a complete answer–94.4 s

Each model is compared at its best-ranked reasoning-effort setting. GPT-5.4 Pro scores 63.3 and takes 6 s to its first answer token; GPT-5.4 Pro (xhigh) scores 61.9 in 6 s. Muse Spark 1.3 (max) scores 67.1 and takes 90 s to its first answer token; Muse Spark 1.3 (xhigh) scores 64.9 in 30 s, Muse Spark 1.3 scores 59.8 in 3 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

105 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-5.4 ProMuse Spark 1.3 (max)
BenchLeader IndexBenchLeader63.367.1
Instruction following scoreBenchLeader63.8–
Knowledge scoreBenchLeader73.672.8
Multimodal scoreBenchLeader69.865.7
Reasoning scoreBenchLeader72.577.4
Agents & tools scoreBenchLeader–65.6
Coding scoreBenchLeader–64.5
Composite scoreBenchLeader–83.3
Human preference scoreBenchLeader–69.1
Long context scoreBenchLeader–66.6
Maths scoreBenchLeader–63.4
Blended price $/MBenchLeader$67.50$2.00
Output speedBenchLeader7 tok/s116 tok/s
Time to first answerBenchLeader6.1 s90.1 s
Context windowBenchLeader1,050,000 tokens1,048,576 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub94.6%†–
Humanity's Last ExamScale AI / CAIS44.3%–
SimpleBenchSimpleBench74.1%–
Arena Hard PromptsArena (LMArena)–1517
LiveBench 2.0 ReasoningLiveBench–89.7%†
LiveBench 1.0 ReasoningLiveBench–89.7%†
GPQA Diamond (AA)Artificial Analysis–93.5%
Humanity's Last Exam (AA)Artificial Analysis–48.7%
ARC-AGI-1ARC Prize94.5%†–
ARC-AGI-2ARC Prize83.3%†–
CritPtArtificial Analysis30.0%†24.9%
MysteryMechanismVals AI–36.0%
Chess PuzzlesEpoch AI Benchmarking Hub59.0%†37.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub–25.0%
LMCAEpoch AI Benchmarking Hub–53.9%†
DTBenchEpoch AI Benchmarking Hub–96.5%†
BTF-3Epoch AI Benchmarking Hub–14.1%†
Coding
SciCodeSciCode–58.8%
WeirdMLWeirdML57.4%†–
Arena CodingArena (LMArena)–1536
Arena WebDevArena (LMArena)–1657
LiveBench 2.0 CodingLiveBench–90.2%†
LiveBench 1.0 CodingLiveBench–81.1%†
IOIVals AI–56.6%
Code MigrationVals AI–47.4%
Show all 105 benchmarks
MetricPublisherGPT-5.4 ProMuse Spark 1.3 (max)
Coding
ProgramBenchVals AI–2.5%
SWE-bench MultimodalVals AI–43.1%
Vibe Code Bench 1-100Vals AI–20.5%
Vibe Code Bench v1.1Vals AI–85.9%
CursorBenchCursor–41.6%
ALE-BenchEpoch AI Benchmarking Hub–1688.3†
FrontierSWEEpoch AI Benchmarking Hub–25.8%
Terminal-Bench 4.0 (AA)Artificial Analysis–33.3%
Terminal-Bench 2.1 (AA)Artificial Analysis–84.3%
Startrise FrontendStartrise–74.7%†
FrontierCode 1.1 (AA)Artificial Analysis–40.6%
Agents & tools
Terminal-BenchTerminal-Bench–14.6%†
APEX-AgentsMercor–47.6%
Arena AgentArena (LMArena)–3.4
LiveBench Long AgenticLiveBench–40.4%†
LiveBench BrowserLiveBench–80.0%†
LiveBench Agentic CodingLiveBench–64.1%†
Terminal-Bench 2.1 (Vals)Vals AI–79.0%
HiL-BenchScale AI SEAL–66.9%†
τ³-Banking (AA)Artificial Analysis–50.5%
ITBench SRE (AA)Artificial Analysis–33.2%
Analyst Agent (AA)Artificial Analysis–37.5%
CUA-benchVals AI–5.8%
CyberBenchVals AI–72.7%
Finance Agent v2Vals AI–60.0%
Harvey's Legal Agent Benchmark v1Vals AI–23.8%
Legal Research BenchVals AI–55.3%
SREBenchVals AI–3.8%
Tax Agent BenchVals AI–42.4%
Terminal-Bench 4.0 (Vals)Vals AI–24.8%
Terminal-Bench ScienceVals AI–10.0%
AutomationBenchArtificial Analysis–57.9%
GDP.pdf (AA)Artificial Analysis–26.6%
Harvey LAB-AA v1.1Harvey–8.9%
AA-Briefcase v1.1Artificial Analysis–1581
Terminal-Bench-Science 0.1 (AA)Artificial Analysis–10.9%
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub82.5%†74.0%
FrontierMath Tier 4Epoch AI Benchmarking Hub58.5%†46.3%
OTIS Mock AIMEEpoch AI Benchmarking Hub–99.2%†
ProofBenchVals AI–58.0%
LiveBench MathematicsLiveBench–96.0%†
MathArena ApexMathArena69.8%†–
Arena MathsArena (LMArena)–1510
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub46.3%†–
LiveBench 2.0 Data AnalysisLiveBench–79.6%†
LiveBench ResearchLiveBench–68.6%†
LiveBench 1.0 Data AnalysisLiveBench–79.6%†
AA-OmniscienceArtificial Analysis–25
PRBench FinanceScale AI SEAL–59.5%†
PRBench LegalScale AI SEAL–61.6%†
MultiNRCScale AI SEAL62.3%–
Excel Modeling BenchmarkVals AI–67.4%
DrugDiscoveryBenchScale AI SEAL–62.2%†
GDP.pdfEpoch AI Benchmarking Hub–27.6%†
AA-Omniscience: accuracyArtificial Analysis–43.6%
AA-Omniscience: non-hallucinationArtificial Analysis–67.1%
Instruction following
LiveBench LanguageLiveBench–82.8%†
LiveBench Instruction FollowingLiveBench–78.0%†
MultiChallengeScale AI SEAL69.2%–
TutorBenchScale AI SEAL56.6%–
Arena Instruction FollowingArena (LMArena)–1485
Human preference
Arena TextArena (LMArena)–1496
Arena Creative WritingArena (LMArena)–1463
Arena Multi-turnArena (LMArena)–1494
Arena Longer QueriesArena (LMArena)–1497
Multimodal
Arena VisionArena (LMArena)–1308
LiveBench DesignLiveBench–74.8%†
MMMU-ProArtificial Analysis–82.0%†
VISTAScale AI SEAL53.9%–
AA-3DArtificial Analysis–1037
Long context
AA-LCRArtificial Analysis–83.0%
Arena DocumentArena (LMArena)–1468
MLCRArtificial Analysis–13.9%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub159.6157.2†
LiveBench 2.0LiveBench–74.8%†
LiveBench 1.0LiveBench–81.6%†
AA Intelligence Index v4.3.2Artificial Analysis–48.1
Vals RSI IndexVals AI–19.6%
Safety & honesty
FORTRESSScale AI SEAL14.8%–
MASKScale AI SEAL91.7%–

Data as of 2026-10-24. Best configuration of each model; every score links to its source on the model pages.

What changed

  • Muse Spark 1.3 (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, SWE-bench Multimodal); 1 score revision.
  • GPT-5.4 Pro: 1 score revision.
  • Muse Spark 1.3 (max): 1 score revision.
  • Muse Spark 1.3 (max): 1 score revision.
  • Muse Spark 1.3 (max): 2 new results (ProgramBench, SREBench); 1 score revision.
  • Muse Spark 1.3 (max): 2 new results (APEX-Agents, FrontierSWE); 1 score revision.
  • Muse Spark 1.3 (max): BenchLeader Index 68.0 → 67.5.
  • Muse Spark 1.3 (max): 1 new result (Analyst Agent (AA)); 1 score revision.
  • Muse Spark 1.3 (max): 3 new results (FrontierCode 1.1 (AA), Terminal-Bench-Science 0.1 (AA), AA-3D).
  • GPT-5.4 Pro: BenchLeader Index 62.1 → 63.6.

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

GPT-5.4 Pro vs Muse Spark 1.3: questions

Is GPT-5.4 Pro better than Muse Spark 1.3?
GPT-5.4 Pro and Muse Spark 1.3 (max) are neck and neck on quality (63.3 vs 67.1, within the ±5.6 margin). The BenchLeader Index combines every independent quality benchmark; the two are within the margin of error as of 2026-10-24, so check the category scores for your use.
Which is cheaper, GPT-5.4 Pro or Muse Spark 1.3, and will that change?
Muse Spark 1.3 is cheaper today: $2.00 against $67.50 per million tokens, blended at three input tokens per output token. No price change has been announced for either.
Which is better for long documents?
Both take about 1.1M tokens: GPT-5.4 Pro 1,050,000, Muse Spark 1.3 1,048,576.
Which has lower latency?
GPT-5.4 Pro answers first: 6.1 s against 90.1 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.
Which is faster, GPT-5.4 Pro or Muse Spark 1.3?
Muse Spark 1.3 streams faster: 116 against 7 output tokens per second.
When was Muse Spark 1.3 released?
Muse Spark 1.3 was released on 2 Sept 2026.