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Gemini 3.8 Flash vs Muse Spark 1.2

Gemini 3.8 Flash leads Muse Spark 1.2 on coding, 61.6 to 55.7 on the Vibe Coding Index, at about the same output price ($3.75 vs $4.25 per million). Updated October 22, 2026; 92 benchmarks have a result for both.

Replace Gemini 3.8 Flash Replace Muse Spark 1.2
Gemini 3.8 FlashGoogle
Coding
61.6
Overall
69.0
Output $/M
$3.75
67
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
25
vs boards won of 92 shared

Gemini 3.8 Flash or Muse Spark 1.2: which to pick

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 55.7 for Muse Spark 1.2.

Pick Muse Spark 1.2 for a lower cost per solved task ($0.64 against $2.74) and work measured by SWE-bench Verified (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Model AGemini 3.8 FlashGoogle61.6/1006 independent benchmarks$2.74 per solved taskModel BMuse Spark 1.2Meta55.7/1005 independent benchmarks$0.64 per solved task
Shared results
92
Gemini 3.8 Flash only
36
Muse Spark 1.2 only
5
Like-for-like categories
8 of 9

Only benchmarks that tested both models count toward a pick; a result only one model has is shown but not compared.

Which one for your work

Each card is decided by one number both models carry. Where only one has it, the card says so and makes no call.

At a glance

Coding index
Gemini 3.8 Flash 61.6 from 6 benchmarks, Muse Spark 1.2 55.7 from 5 benchmarks.
Widest category
Coding, 9.3 points apart on average over 19 shared benchmarks.
Widest single gap
IOI (Vals AI): Gemini 3.8 Flash 56.9% against Muse Spark 1.2 21.8%, 35.2 points apart on a 0 to 100 scale.
Output price
Gemini 3.8 Flash $3.75 against Muse Spark 1.2 $4.25 per million output tokens, 1.1x apart.
Context window
Both take 1.05M tokens.

Benchmark by benchmark

First the score: boards each model leads, per category, where both have a result. Then every board, a category to a fold; bars are each result on a 0 to 100 scale, so compare the two in a row, not one row with another.

Boards won, where both have a result
CategoryGemini 3.8 FlashBarsMuse Spark 1.2Ties
Coding154
Intelligence20
Agentic work106
Reasoning81
Math30
Knowledge55
Web design45
General204
All shared boards6725
CodingLike-for-likeSix of these boards feed the Vibe Coding Index154
Coding benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
LiveBench coding82.2%78.2%Gemini 3.8 Flash
LMArena WebDev15851534Gemini 3.8 Flash
AA Coding Index76.372.2Gemini 3.8 Flash
LiveCodeBench (Vals AI)89.5%Not measuredOnly Gemini 3.8 Flash measured
SWE-bench Verified (Vals AI)80.0%86.6%Muse Spark 1.2
Terminal-Bench 4 (Vals AI)19.7%6.1%Gemini 3.8 Flash
Vibe Code Bench (Vals AI)78.7%79.1%Muse Spark 1.2
Code migration (Vals AI)36.5%29.9%Gemini 3.8 Flash
ProgramBench (Vals AI)1.0%0.5%Gemini 3.8 Flash
IOI (Vals AI)56.9%21.8%Gemini 3.8 Flash
Terminal-Bench 2.1 (Vals AI)81.3%69.7%Gemini 3.8 Flash
SWE-bench Multimodal (Vals AI)40.8%Not measuredOnly Gemini 3.8 Flash measured
Vibe Code Bench 1-100 (Vals AI)18.8%Not measuredOnly Gemini 3.8 Flash measured
SkillsBench (Vals AI)58.0%53.0%Gemini 3.8 Flash
CyberBench (Vals AI)43.8%69.5%Muse Spark 1.2
SciCode56.6%57.4%Muse Spark 1.2
FrontierCode41.2%Not measuredOnly Gemini 3.8 Flash measured
FrontierSWE19.6%12.0%Gemini 3.8 Flash
WeirdML84.8%60.3%Gemini 3.8 Flash
ALE-Bench1269.7Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: coding15081505Gemini 3.8 Flash
LMArena Text: software and IT15071505Gemini 3.8 Flash
LMArena WebDev: React15771526Gemini 3.8 Flash
LMArena WebDev: HTML16161543Gemini 3.8 Flash
LMArena WebDev: from an image1593Not measuredOnly Gemini 3.8 Flash measured
SciCode12.3%Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 13 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
AA Intelligence Index40.939.6Gemini 3.8 Flash
Epoch Capabilities Index157.4155.1Gemini 3.8 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index106
Agentic work benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
AA Agentic Index40.243.2Muse Spark 1.2
Design Arena: agents building web apps12381221Gemini 3.8 Flash
Design Arena: agents building full-stack apps12441210Gemini 3.8 Flash
Design Arena: agents building mobile apps12361181Gemini 3.8 Flash
Design Arena: agents building Android apps10781222Muse Spark 1.2
Design Arena: agents building Godot games1273Not measuredOnly Gemini 3.8 Flash measured
Design Arena: agents building gamesNot measured1179Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1085Only Muse Spark 1.2 measured
Design Arena: PowerPoint slides11531172Muse Spark 1.2
Design Arena: spreadsheets1022Not measuredOnly Gemini 3.8 Flash measured
LiveBench research79.1%67.7%Gemini 3.8 Flash
LiveBench browser64.0%36.0%Gemini 3.8 Flash
LiveBench long agentic30.1%21.3%Gemini 3.8 Flash
SREBench (Vals AI)11.1%0.0%Gemini 3.8 Flash
Finance Agent (Vals AI)61.4%60.6%Gemini 3.8 Flash
Tax Agent Bench (Vals AI)32.1%32.8%Muse Spark 1.2
Legal Research Bench (Vals AI)38.9%43.8%Muse Spark 1.2
Harvey's Legal Agent Benchmark (Vals AI)12.1%Not measuredOnly Gemini 3.8 Flash measured
Excel Modeling Benchmark (Vals AI)72.2%57.0%Gemini 3.8 Flash
BioMysteryBench (Vals AI)62.2%64.8%Muse Spark 1.2
Terminal-Bench-Science (Vals AI)8.6%Not measuredOnly Gemini 3.8 Flash measured
Vals Science Index35.8%Not measuredOnly Gemini 3.8 Flash measured
Time Horizon Index (Vals AI)18.8%Not measuredOnly Gemini 3.8 Flash measured
CUA-bench (Vals AI)4.2%Not measuredOnly Gemini 3.8 Flash measured
APEX-Agents64.3%45.4%Gemini 3.8 Flash
Remote Labor Index5.8%Not measuredOnly Gemini 3.8 Flash measured
Vending-Bench 2$5,094Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 14 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index81
Reasoning benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
GPQA Diamond94.4%Not measuredOnly Gemini 3.8 Flash measured
LiveBench reasoning89.3%90.0%Muse Spark 1.2
MysteryMechanism (Vals AI)36.5%Not measuredOnly Gemini 3.8 Flash measured
MMMU Pro (Vals AI)89.1%86.1%Gemini 3.8 Flash
GPQA Diamond (Artificial Analysis run)95.3%90.4%Gemini 3.8 Flash
Humanity's Last Exam (Artificial Analysis run)47.8%45.5%Gemini 3.8 Flash
GPQA Diamond (Epoch AI run)95.4%Not measuredOnly Gemini 3.8 Flash measured
ARC-AGI98.5%Not measuredOnly Gemini 3.8 Flash measured
ARC-AGI-289.2%Not measuredOnly Gemini 3.8 Flash measured
SimpleBenchNot measured74.5%Only Muse Spark 1.2 measured
Chess puzzles58.0%27.0%Gemini 3.8 Flash
Mystery game puzzles47.0%Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: hard prompts15091489Gemini 3.8 Flash
LMArena Text: expert15261475Gemini 3.8 Flash
LMArena Text: hard prompts in English15041487Gemini 3.8 Flash
LMArena Vision: diagrams13451317Gemini 3.8 Flash
LMArena Vision: homework1351Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index30
Math benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
OTIS Mock AIME98.9%Not measuredOnly Gemini 3.8 Flash measured
FrontierMath, tiers 1 to 368.4%Not measuredOnly Gemini 3.8 Flash measured
FrontierMath, tier 422.0%Not measuredOnly Gemini 3.8 Flash measured
ProofBench48.0%43.0%Gemini 3.8 Flash
LMArena Text: math15321484Gemini 3.8 Flash
LMArena Text: mathematical work15191480Gemini 3.8 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index55
Knowledge benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
MMLU Pro90.2%88.3%Gemini 3.8 Flash
LegalBench (Vals AI)87.0%85.3%Gemini 3.8 Flash
CorpFin (Vals AI)Not measured70.9%Only Muse Spark 1.2 measured
TaxEval (Vals AI)74.5%80.4%Muse Spark 1.2
MortgageTax (Vals AI)65.3%65.4%Muse Spark 1.2
MedCode (Vals AI)48.1%49.4%Muse Spark 1.2
SimpleQA Verified69.7%60.3%Gemini 3.8 Flash
LMArena Text: science15231500Gemini 3.8 Flash
LMArena Text: medicine and healthcare15081496Gemini 3.8 Flash
LMArena Text: legal and government14971517Muse Spark 1.2
LMArena Text: business and finance14791484Muse Spark 1.2
FACTS Benchmark Suite69.4%Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 6 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index45
Web design benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
Design Arena: websites13001312Muse Spark 1.2
Design Arena: UI components13161298Gemini 3.8 Flash
Design Arena: game dev13041301Gemini 3.8 Flash
Design Arena: data viz12701334Muse Spark 1.2
Design Arena: 3D12941301Muse Spark 1.2
Design Arena: all code categories13031312Muse Spark 1.2
Design Arena: SVG12961284Gemini 3.8 Flash
Design Arena: ASCII art12621284Muse Spark 1.2
LiveBench design72.7%67.1%Gemini 3.8 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index204
General benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
Vals Index56.0%Not measuredOnly Gemini 3.8 Flash measured
LiveBench data analysis54.0%76.5%Muse Spark 1.2
Public Benefits Bench (Vals AI)65.3%68.5%Muse Spark 1.2
SAGE (Vals AI)35.1%47.7%Muse Spark 1.2
MedScribe (Vals AI)84.5%90.1%Muse Spark 1.2
Vals Multimodal IndexNot measured69.8%Only Muse Spark 1.2 measured
Long context reasoning (AA-LCR)84.0%79.0%Gemini 3.8 Flash
DTBench95.7%94.7%Gemini 3.8 Flash
LMCA52.9%48.4%Gemini 3.8 Flash
Surface Evolver Bench76.9%Not measuredOnly Gemini 3.8 Flash measured
Furniture assembly31.7%Not measuredOnly Gemini 3.8 Flash measured
LMArena Text14991482Gemini 3.8 Flash
LMArena Text: instruction following14921462Gemini 3.8 Flash
LMArena Text: creative writing14881436Gemini 3.8 Flash
LMArena Vision13151304Gemini 3.8 Flash
LMArena Text: English14981483Gemini 3.8 Flash
LMArena Text: non-English14911476Gemini 3.8 Flash
LMArena Text: Chinese15531509Gemini 3.8 Flash
LMArena Text: German1501Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: Japanese1507Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: Korean14641462Gemini 3.8 Flash
LMArena Text: French14961495Gemini 3.8 Flash
LMArena Text: Spanish14871484Gemini 3.8 Flash
LMArena Text: Russian15141483Gemini 3.8 Flash
LMArena Text: Polish1497Not measuredOnly Gemini 3.8 Flash measured
LMArena Text: multi-turn15031502Gemini 3.8 Flash
LMArena Text: longer queries15071473Gemini 3.8 Flash
LMArena Text: writing and language14941453Gemini 3.8 Flash
LMArena Text: entertainment and media14801443Gemini 3.8 Flash
LMArena Vision: English13181291Gemini 3.8 Flash
LMArena Vision: Chinese1416Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: reading text13331313Gemini 3.8 Flash
LMArena Vision: humor1321Not measuredOnly Gemini 3.8 Flash measured
LMArena Vision: creative writing1299Not measuredOnly Gemini 3.8 Flash measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Gemini 3.8 Flash and Muse Spark 1.2
BenchmarkGemini 3.8 FlashMuse Spark 1.2Leader
Neither model has a result on 5 boards here

What each workload costs

Three fixed token mixes at each model's listed price, so per-token rates become a bill.

Chat turn

1K input + 500 output tokens

Gemini 3.8 Flash$0.0026Fits in one request
Muse Spark 1.2$0.0034Fits in one request

Gemini 3.8 Flash costs less

Repository review

50K input + 3K output tokens

Gemini 3.8 Flash$0.049Fits in one request
Muse Spark 1.2$0.075Fits in one request

Gemini 3.8 Flash costs less

Agent loop

200K input + 10K output tokens

Gemini 3.8 Flash$0.188Fits in one request
Muse Spark 1.2$0.292Fits in one request

Gemini 3.8 Flash costs less

Listed OpenRouter rates, without cache or batch discounts. A workload that does not fit a model's context window would need splitting.

Specification differences

The leading value in a row is marked; a row with a missing value names no leader. Our two rows are marked in red.

Specifications of Gemini 3.8 Flash and Muse Spark 1.2
SpecificationGoogle Gemini 3.8 FlashMeta Muse Spark 1.2
MakerGoogleMeta
WeightsNo public weights listedNo public weights listed
ReleasedSeptember 2, 2026August 5, 2026
Context window1.05M1.05M
Input $/Mtok$0.75$1.25
Output $/Mtok$3.75$4.25
Coding index61.655.7
Independent measurements behind it65
Cost per solved task$2.74$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is Gemini 3.8 Flash better than Muse Spark 1.2 for coding?

Pick Gemini 3.8 Flash for coding: it scores 61.6 on the Vibe Coding Index against 55.7 for Muse Spark 1.2. Pick Muse Spark 1.2 for a lower cost per solved task ($0.64 against $2.74) and work measured by SWE-bench Verified (Vals AI) or Vibe Code Bench (Vals AI), where it leads.

Which is cheaper, Gemini 3.8 Flash or Muse Spark 1.2?

Gemini 3.8 Flash costs $0.75 per million input tokens and $3.75 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Per solved SWE-bench Verified task, Gemini 3.8 Flash costs $2.74 and Muse Spark 1.2 $0.64.

Which has the bigger context window, Gemini 3.8 Flash or Muse Spark 1.2?

Neither: both take 1.05M tokens.

How many benchmarks is the Gemini 3.8 Flash vs Muse Spark 1.2 comparison based on?

92 benchmarks have a result for both models as of October 22, 2026. Gemini 3.8 Flash's coding index rests on 6 independent benchmarks and Muse Spark 1.2's on 5. Where only one model has a result, the page says so instead of naming a winner.

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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/gemini-3-8-flash-vs-meta-muse-spark-1-2">LLMBenchmark.ai, Gemini 3.8 Flash vs Muse Spark 1.2</a></p>