BenchLeader

Gemini 3.8 Flash vs Muse Spark 1.3

Full profiles: Gemini 3.8 Flash (Google) and Muse Spark 1.3 (Meta): every benchmark, price and rank.

Updated · Data from 10 sources

As of 24 Oct 2026, Gemini 3.8 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (64.4 vs 67.1 on the BenchLeader Index, inside the ±5.9 margin of error), and Gemini 3.8 Flash (high) costs 1.3× less, which makes it the better buy for most workloads. Gemini 3.8 Flash (high)'s current price runs until 31 Dec 2026; from 1 Jan 2027 Muse Spark 1.3 (max) costs 1.5× less ($2.00 vs $3.00 per 1M blended); on use case, pick Gemini 3.8 Flash for multimodal (68 vs 66), Muse Spark 1.3 for agents & tools (66 vs 51).

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 Spark 1.365 vs 64 category score; Arena WebDev 1657 vs 1585Medium
Agents & tool useMuse Spark 1.366 vs 51 category score; τ³-Banking (AA) 50.5% vs 45.0%High
MathsMuse Spark 1.363 vs 62 category score; FrontierMath Tiers 1–3 74.0% vs 68.4%Medium
ReasoningMuse Spark 1.377 vs 68 category score; CritPt 24.9% vs 18.3%High
KnowledgeMuse Spark 1.373 vs 68 category score; AA-Omniscience 25 vs 29.6Medium
Long documentsEither66 vs 67 category score; AA-LCR 81.3% vs 83.0%Either
Images and other mediaGemini 3.8 Flash68 vs 66 category score; Arena Vision 1315 vs 1308Medium
Chat quality (human preference)Either69 vs 69 on Arena votesEither
Lowest costGemini 3.8 Flash (until 31 Dec 2026)$1.50 vs $2.00 per 1M blended; agentic coding session $0.060 vs $0.092; from 1 Jan 2027: $3.00 vs $2.00–
Fastest first answerGemini 3.8 Flash25.1 s (Gemini 3.8 Flash (high)) 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

  • Gemini 3.8 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (64.4 vs 67.1, within the ±5.9 margin).
  • Gemini 3.8 Flash (high) is stronger in multimodal.
  • Muse Spark 1.3 (max) is stronger in agents & tools, coding, composite, knowledge, long context, maths, reasoning.
  • Gemini 3.8 Flash (high) is 1.3× cheaper ($1.50 vs $2.00 per 1M blended) until 31 Dec 2026, then $3.00 vs $2.00 from 1 Jan 2027.

At a glance

SpecGemini 3.8 FlashMuse Spark 1.3
DeveloperGoogleMeta
Released2 Sept 20262 Sept 2026
Context window (tokens)1,048,5761,048,576
Compared atGemini 3.8 Flash (high)Muse Spark 1.3 (max)
Open weightsNoNo
Price in / out / cached input per 1M$0.750 / $3.75 / $0.075$1.25 / $4.25 / $0.150
Announced price change$1.50 / $7.50 from 1 Jan 2027None announced

Limits, availability and announced prices from the vendors' own pages: ai.google.dev pricing (checked 20 Oct 2026). Everything else is from the day's data.

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.

CategoryGemini 3.8 Flash (high)Muse Spark 1.3 (max)Leader
Reasoning68.277.4Muse Spark 1.3
Coding63.564.5Muse Spark 1.3
Agents & tools50.965.6Muse Spark 1.3
Maths62.463.4Muse Spark 1.3
Knowledge68.472.8Muse Spark 1.3
Human preference69.169.1level
Multimodal67.765.7Gemini 3.8 Flash
Long context65.766.6level
Composite75.383.3Muse Spark 1.3

Where sources disagree

Across the 56 benchmarks both have, Gemini 3.8 Flash leads 24, Muse Spark 1.3 leads 32. Independent sources split: Gemini 3.8 Flash leads on Arena Text; Muse Spark 1.3 leads on AA Intelligence Index v4.3.2.

Overall indexGemini 3.8 Flash (high)Muse Spark 1.3 (max)Leader
BenchLeader Index64.467.1neck and neck
AA Intelligence Index v4.3.240.948.1Muse Spark 1.3
Arena Text14961496Gemini 3.8 Flash

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.

MeasureGemini 3.8 Flash (high)Muse Spark 1.3 (max)
Blended price per 1M tokens, until 31 Dec 2026$1.50$2.00
Input / output per 1M$0.750 / $3.75$1.25 / $4.25
Blended price per 1M from 1 Jan 2027$3.00$2.00
Input / output per 1M from 1 Jan 2027$1.50 / $7.50$1.25 / $4.25
Cached input per 1M$0.075$0.150
Price per task: chat reply$0.0014$0.0018
Price per task: summarize a 30-page report$0.011$0.018
Price per task: code edit$0.010$0.014
Price per task: agentic coding session$0.060$0.092
Price per task: structured extraction$0.0023$0.0034
Cost to run a full benchmark suite$1.24$1.60
Output speed141 tok/s116 tok/s
Time to first answer25.1 s90.1 s
Time to a complete answer28.7 s94.4 s

Per token is not per task: on Artificial Analysis' full suite Gemini 3.8 Flash (high) cost $1.24 and Muse Spark 1.3 (max) $1.60, because Gemini 3.8 Flash (high) used about 1.0× as many tokens for the same work.

Each model is compared at its best-ranked reasoning-effort setting. Gemini 3.8 Flash (high) scores 64.4 and takes 25 s to its first answer token; Gemini 3.8 Flash (medium) scores 64.4 in 3 s, Gemini 3.8 Flash (low) scores 61.0 in 3 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

138 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.

MetricPublisherGemini 3.8 Flash (high)Muse Spark 1.3 (max)
BenchLeader IndexBenchLeader64.467.1
Agents & tools scoreBenchLeader50.965.6
Coding scoreBenchLeader63.564.5
Composite scoreBenchLeader75.383.3
Human preference scoreBenchLeader69.169.1
Knowledge scoreBenchLeader68.472.8
Long context scoreBenchLeader65.766.6
Maths scoreBenchLeader62.463.4
Multimodal scoreBenchLeader67.765.7
Reasoning scoreBenchLeader68.277.4
Blended price $/MBenchLeader$1.50$2.00
Output speedBenchLeader141 tok/s116 tok/s
Time to first answerBenchLeader25.1 s90.1 s
Context windowBenchLeader1,048,576 tokens1,048,576 tokens
Reasoning
GPQA DiamondEpoch AI Benchmarking Hub95.4%–
Humanity's Last ExamScale AI / CAIS44.5%†–
Arena Hard PromptsArena (LMArena)15171517
LiveBench 2.0 ReasoningLiveBench89.3%†89.7%†
LiveBench 1.0 ReasoningLiveBench89.3%89.7%†
GPQA Diamond (AA)Artificial Analysis95.3%93.5%
Humanity's Last Exam (AA)Artificial Analysis47.8%48.7%
GPQA Diamond (Vals)Vals AI94.4%–
ARC-AGI-1ARC Prize98.5%–
ARC-AGI-2ARC Prize89.2%–
ARC-AGI-3ARC Prize35.0%–
CritPtArtificial Analysis18.3%24.9%
MysteryMechanismVals AI36.5%36.0%
Chess PuzzlesEpoch AI Benchmarking Hub58.0%37.0%
Mystery Game PuzzlesEpoch AI Benchmarking Hub47.0%25.0%
LMCAEpoch AI Benchmarking Hub51.5%†53.9%†
DTBenchEpoch AI Benchmarking Hub95.7%†96.5%†
BTF-3Epoch AI Benchmarking Hub–14.1%†
Coding
SciCodeSciCode56.6%58.8%
WeirdMLWeirdML84.8%–
FrontierCodeCognition41.2%†–
Arena CodingArena (LMArena)15281536
Arena WebDevArena (LMArena)15851657
LiveBench 2.0 CodingLiveBench82.2%†90.2%†
LiveBench 1.0 CodingLiveBench72.5%81.1%†
Show all 138 benchmarks
MetricPublisherGemini 3.8 Flash (high)Muse Spark 1.3 (max)
Coding
LiveCodeBenchVals AI89.5%–
IOIVals AI56.9%56.6%
SWE-bench (Vals)Vals AI80.0%–
Code MigrationVals AI36.5%47.4%
Code Migration v1.1Vals AI38.6%–
ProgramBenchVals AI1.0%2.5%
SWE-bench MultimodalVals AI40.8%43.1%
Vibe Code Bench 1-100Vals AI18.8%20.5%
Vibe Code Bench v1.1Vals AI78.7%85.9%
SWE Atlas: Codebase QnAScale AI SEAL47.0%†–
SWE Atlas: RefactoringScale AI SEAL44.8%†–
SWE Atlas: Test WritingScale AI SEAL53.7%†–
Surface Evolver BenchEpoch AI Benchmarking Hub76.9%–
DeepSWE v1.1Epoch AI Benchmarking Hub73.8%–
CursorBenchCursor39.6%41.6%
ALE-BenchEpoch AI Benchmarking Hub1269.71688.3†
FrontierSWEEpoch AI Benchmarking Hub19.6%25.8%
Terminal-Bench 4.0 (AA)Artificial Analysis19.7%33.3%
Terminal-Bench 2.1 (AA)Artificial Analysis87.6%84.3%
Startrise FrontendStartrise64.6%†74.7%†
FrontierCode 1.1 (AA)Artificial Analysis36.4%40.6%
Agents & tools
Terminal-BenchTerminal-Bench19.1%14.6%†
Remote Labor IndexScale AI / CAIS5.8%†–
APEX-AgentsMercor64.3%†47.6%
Arena AgentArena (LMArena)3.63.4
LiveBench Long AgenticLiveBench30.1%†40.4%†
LiveBench BrowserLiveBench64.0%†80.0%†
LiveBench Agentic CodingLiveBench54.2%64.1%†
Terminal-Bench 2.1 (Vals)Vals AI81.3%79.0%
HiL-BenchScale AI SEAL41.5%†66.9%†
GDPval-AA v2.1Artificial Analysis46.8%–
τ³-Banking (AA)Artificial Analysis45.0%50.5%
ITBench SRE (AA)Artificial Analysis52.5%33.2%
Analyst Agent (AA)Artificial Analysis46.3%37.5%
CUA-benchVals AI4.2%5.8%
CyberBenchVals AI43.8%72.7%
Finance Agent v2Vals AI61.4%60.0%
Finance Agent v2.1Vals AI65.8%–
Harvey's Legal Agent Benchmark v1.1Vals AI12.1%–
Harvey's Legal Agent Benchmark v1Vals AI10.0%23.8%
Legal Research BenchVals AI38.9%55.3%
SkillsBenchVals AI58.0%–
SREBenchVals AI11.1%3.8%
Tax Agent BenchVals AI32.1%42.4%
Terminal-Bench 4.0 (Vals)Vals AI19.7%24.8%
Terminal-Bench ScienceVals AI8.6%10.0%
Time Horizon Index: KSPVals AI18.8%–
Vending-Bench 2Andon Labs5093.8†–
AutomationBenchArtificial Analysis59.9%57.9%
GDP.pdf (AA)Artificial Analysis21.0%26.6%
Harvey LAB-AA v1.1Harvey0.0%8.9%
AA-Briefcase v1.1Artificial Analysis12021581
Terminal-Bench-Science 0.1 (AA)Artificial Analysis10.0%10.9%
CWE-Bench (AA)Artificial Analysis52.5%–
DeepSec-Bench (AA)Artificial Analysis14.5%–
CyberGym end-to-end (AA)Artificial Analysis8.4%–
FACTS SearchGoogle76.3%†–
Maths
FrontierMath Tiers 1–3Epoch AI Benchmarking Hub68.4%74.0%
FrontierMath Tier 4Epoch AI Benchmarking Hub21.9%46.3%
OTIS Mock AIMEEpoch AI Benchmarking Hub98.9%99.2%†
ProofBenchVals AI48.0%†58.0%
LiveBench MathematicsLiveBench91.6%96.0%†
Arena MathsArena (LMArena)15261510
Knowledge
SimpleQA VerifiedEpoch AI Benchmarking Hub69.7%–
LiveBench 2.0 Data AnalysisLiveBench54.0%†79.6%†
LiveBench ResearchLiveBench79.1%†68.6%†
LiveBench 1.0 Data AnalysisLiveBench54.0%79.6%†
AA-OmniscienceArtificial Analysis29.625
MMLU-ProVals AI90.2%–
LegalBenchVals AI87.0%–
TaxEvalVals AI74.5%–
PRBench FinanceScale AI SEAL49.5%†59.5%†
PRBench LegalScale AI SEAL48.9%†61.6%†
BioMysteryBenchVals AI62.2%–
Excel Modeling BenchmarkVals AI72.2%67.4%
Excel Modeling Benchmark v1.1Vals AI72.9%–
MedCodeVals AI48.1%–
MedScribeVals AI84.5%–
Public Benefits Bench v1.1Vals AI65.3%–
DrugDiscoveryBenchScale AI SEAL–62.2%†
GDP.pdfEpoch AI Benchmarking Hub23.2%27.6%†
AA-Omniscience: accuracyArtificial Analysis54.6%43.6%
AA-Omniscience: non-hallucinationArtificial Analysis44.8%67.1%
Instruction following
LiveBench LanguageLiveBench87.8%82.8%†
LiveBench Instruction FollowingLiveBench81.4%78.0%†
Arena Instruction FollowingArena (LMArena)14901485
Human preference
Arena TextArena (LMArena)14961496
Arena Creative WritingArena (LMArena)14851463
Arena Multi-turnArena (LMArena)15041494
Arena Longer QueriesArena (LMArena)15101497
Multimodal
Arena VisionArena (LMArena)13151308
LiveBench DesignLiveBench72.7%†74.8%†
MMMU-ProArtificial Analysis85.6%82.0%†
MMMU-Pro (Vals)Vals AI89.1%–
MortgageTaxVals AI65.3%–
SAGEVals AI35.1%–
AudioMCScale AI SEAL60.4%–
AudioMC (text output)Scale AI SEAL60.4%–
Blueprint-Bench 2Epoch AI Benchmarking Hub38.6%†–
AA-3DArtificial Analysis9691037
Long context
AA-LCRArtificial Analysis81.3%83.0%
Arena DocumentArena (LMArena)–1468
MLCRArtificial Analysis10.6%13.9%
Composite
Epoch Capabilities IndexEpoch AI Benchmarking Hub157.4†157.2†
LiveBench 2.0LiveBench67.3%†74.8%†
LiveBench 1.0LiveBench75.8%81.6%†
AA Intelligence Index v4.3.2Artificial Analysis40.948.1
Vals IndexVals AI56.0–
Vals Finance IndexVals AI60.5%–
Vals RSI IndexVals AI19.9%19.6%
Vals Science IndexVals AI35.8%–
Vals Router IndexVals AI56.0%†–
AA Cyber IndexArtificial Analysis25.1–

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

What changed

  • Gemini 3.8 Flash: list price moves to $1.50 / $7.50 per 1M input / output tokens (announced).
  • Gemini 3.8 Flash (high): 8 new results (Code Migration v1.1, Excel Modeling Benchmark v1.1, Finance Agent v2.1…).
  • Muse Spark 1.3 (max): 3 new results (Harvey's Legal Agent Benchmark v1, Vals RSI Index, SWE-bench Multimodal); 1 score revision.
  • Gemini 3.8 Flash (high): 1 score revision.
  • Muse Spark 1.3 (max): 1 score revision.
  • Gemini 3.8 Flash (high): 3 score revisions.
  • Muse Spark 1.3 (max): 1 score revision.
  • Gemini 3.8 Flash (high): BenchLeader Index 63.7 → 64.5.
  • Gemini 3.8 Flash (high): 1 new result (AudioMC (text output)).
  • Gemini 3.8 Flash (high): 1 new result (SREBench); 2 score revisions.

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

Gemini 3.8 Flash vs Muse Spark 1.3: questions

Is Gemini 3.8 Flash better than Muse Spark 1.3?
Gemini 3.8 Flash (high) and Muse Spark 1.3 (max) are neck and neck on quality (64.4 vs 67.1, within the ±5.9 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, Gemini 3.8 Flash or Muse Spark 1.3, and will that change?
Gemini 3.8 Flash is cheaper today: $1.50 against $2.00 per million tokens, blended at three input tokens per output token. Yes, that changes: Gemini 3.8 Flash's list price changes on 1 Jan 2027, and from then Muse Spark 1.3 is cheaper ($2.00 vs $3.00 blended).
Is Gemini 3.8 Flash better than Muse Spark 1.3 for coding?
Muse Spark 1.3 scores higher in coding (65 vs 64 on the category index, where 50 is average). On Arena WebDev, the top shared coding benchmark, it is 1585 for Gemini 3.8 Flash against 1657 for Muse Spark 1.3.
Is Gemini 3.8 Flash better than Muse Spark 1.3 for agents and tool use?
Muse Spark 1.3 scores higher in agentic tasks (66 vs 51 on the category index, where 50 is average). On τ³-Banking (AA), the top shared agents & tools benchmark, it is 45.0% for Gemini 3.8 Flash against 50.5% for Muse Spark 1.3.
Which is better for long documents?
They are level on long-context benchmarks (66 vs 67). Both accept 1,048,576 tokens of context.
Which has lower latency?
Gemini 3.8 Flash (high) answers first: 25.1 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, Gemini 3.8 Flash or Muse Spark 1.3?
Gemini 3.8 Flash streams faster: 141 against 116 output tokens per second.
Do independent benchmarks agree on Gemini 3.8 Flash vs Muse Spark 1.3?
Across the 56 benchmarks both have, Gemini 3.8 Flash leads 24, Muse Spark 1.3 leads 32. Independent sources split: Gemini 3.8 Flash leads on Arena Text; Muse Spark 1.3 leads on AA Intelligence Index v4.3.2.
When was Gemini 3.8 Flash released?
Gemini 3.8 Flash was released on 2 Sept 2026.