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DeepSeek V4 Flash 0731 vs Muse Spark 1.2

Muse Spark 1.2 leads DeepSeek V4 Flash 0731 on coding, 55.7 to 51.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 15.2x less per output token ($0.28 vs $4.25 per million). Updated October 22, 2026; 43 benchmarks have a result for both.

DeepSeek V4 Flash 0731DeepSeek
Coding
51.8
Overall
55.2
Output $/M
$0.28
10
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
32
vs boards won of 43 shared, 1 tied

DeepSeek V4 Flash 0731 or Muse Spark 1.2: which to pick

Pick Muse Spark 1.2 for coding: it scores 55.7 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731.

Pick DeepSeek V4 Flash 0731 for output tokens 15.2x cheaper ($0.28 vs $4.25 per million) and a lower cost per solved task ($0.01 against $0.64).

Shared results
43
DeepSeek V4 Flash 0731 only
12
Muse Spark 1.2 only
54
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
DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, Muse Spark 1.2 55.7 from 5 benchmarks.
Widest category
Web design, 13.4 points apart on average over 8 shared benchmarks.
Widest single gap
SimpleQA Verified: DeepSeek V4 Flash 0731 33.6% against Muse Spark 1.2 60.3%, 26.7 points apart on a 0 to 100 scale.
Output price
DeepSeek V4 Flash 0731 $0.28 against Muse Spark 1.2 $4.25 per million output tokens, 15.2x 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
CategoryDeepSeek V4 Flash 0731BarsMuse Spark 1.2Ties
Coding66
Intelligence02
Agentic work051 tie
Reasoning22
Math10
Knowledge06
Web design08
General13
All shared boards10321 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index66
Coding benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
LiveBench codingNot measured78.2%Only Muse Spark 1.2 measured
LMArena WebDevNot measured1534Only Muse Spark 1.2 measured
AA Coding Index69.172.2Muse Spark 1.2
LiveCodeBench (Vals AI)87.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
SWE-bench Verified (Vals AI)88.8%86.6%DeepSeek V4 Flash 0731
Terminal-Bench 4 (Vals AI)18.7%6.1%DeepSeek V4 Flash 0731
Vibe Code Bench (Vals AI)74.7%79.1%Muse Spark 1.2
Code migration (Vals AI)38.6%29.9%DeepSeek V4 Flash 0731
ProgramBench (Vals AI)0.0%0.5%Muse Spark 1.2
IOI (Vals AI)32.7%21.8%DeepSeek V4 Flash 0731
Terminal-Bench 2.1 (Vals AI)67.0%69.7%Muse Spark 1.2
SkillsBench (Vals AI)50.7%53.0%Muse Spark 1.2
CyberBench (Vals AI)72.1%69.5%DeepSeek V4 Flash 0731
SciCode50.3%57.4%Muse Spark 1.2
FrontierCode18.8%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdML63.0%60.3%DeepSeek V4 Flash 0731
ALE-Bench1306.1Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: codingNot measured1505Only Muse Spark 1.2 measured
LMArena Text: software and ITNot measured1505Only Muse Spark 1.2 measured
LMArena WebDev: ReactNot measured1526Only Muse Spark 1.2 measured
LMArena WebDev: HTMLNot measured1543Only Muse Spark 1.2 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
AA Intelligence Index34.339.6Muse Spark 1.2
Epoch Capabilities Index154.8155.1Muse Spark 1.2
Agentic workLike-for-likePublic boards, shown as published, kept out of the index05
Agentic work benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
AA Agentic Index41.043.2Muse Spark 1.2
Design Arena: agents building web appsNot measured1221Only Muse Spark 1.2 measured
Design Arena: agents building full-stack appsNot measured1210Only Muse Spark 1.2 measured
Design Arena: agents building mobile appsNot measured1181Only Muse Spark 1.2 measured
Design Arena: agents building Android appsNot measured1222Only Muse Spark 1.2 measured
Design Arena: agents building gamesNot measured1178Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1074Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1170Only Muse Spark 1.2 measured
LiveBench researchNot measured67.7%Only Muse Spark 1.2 measured
LiveBench browserNot measured36.0%Only Muse Spark 1.2 measured
LiveBench long agenticNot measured21.3%Only Muse Spark 1.2 measured
SREBench (Vals AI)Not measured0.0%Only Muse Spark 1.2 measured
Finance Agent (Vals AI)49.5%60.6%Muse Spark 1.2
Tax Agent Bench (Vals AI)28.1%32.8%Muse Spark 1.2
Legal Research Bench (Vals AI)30.3%43.8%Muse Spark 1.2
Excel Modeling Benchmark (Vals AI)57.0%57.0%Tie
BioMysteryBench (Vals AI)64.4%64.8%Muse Spark 1.2
Terminal-Bench-Science (Vals AI)4.3%Not measuredOnly DeepSeek V4 Flash 0731 measured
APEX-AgentsNot measured45.4%Only Muse Spark 1.2 measured
Neither model has a result on the other 23 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index22
Reasoning benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
GPQA Diamond89.9%Not measuredOnly DeepSeek V4 Flash 0731 measured
LiveBench reasoningNot measured90.0%Only Muse Spark 1.2 measured
MMMU Pro (Vals AI)Not measured86.1%Only Muse Spark 1.2 measured
GPQA Diamond (Artificial Analysis run)90.8%90.4%DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)38.6%45.5%Muse Spark 1.2
GPQA Diamond (Epoch AI run)91.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI89.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
ARC-AGI-261.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
SimpleBench61.1%74.5%Muse Spark 1.2
Chess puzzles32.0%27.0%DeepSeek V4 Flash 0731
Mystery game puzzles34.0%Not measuredOnly DeepSeek V4 Flash 0731 measured
LMArena Text: hard promptsNot measured1489Only Muse Spark 1.2 measured
LMArena Text: expertNot measured1475Only Muse Spark 1.2 measured
LMArena Text: hard prompts in EnglishNot measured1487Only Muse Spark 1.2 measured
LMArena Vision: diagramsNot measured1317Only Muse Spark 1.2 measured
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index10
Math benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
OTIS Mock AIME94.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tiers 1 to 357.5%Not measuredOnly DeepSeek V4 Flash 0731 measured
FrontierMath, tier 424.4%Not measuredOnly DeepSeek V4 Flash 0731 measured
ProofBench56.0%43.0%DeepSeek V4 Flash 0731
LMArena Text: mathNot measured1484Only Muse Spark 1.2 measured
LMArena Text: mathematical workNot measured1480Only Muse Spark 1.2 measured
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index06
Knowledge benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
MMLU Pro86.2%88.3%Muse Spark 1.2
LegalBench (Vals AI)77.7%85.3%Muse Spark 1.2
CorpFin (Vals AI)61.9%70.9%Muse Spark 1.2
TaxEval (Vals AI)70.7%80.4%Muse Spark 1.2
MortgageTax (Vals AI)Not measured65.4%Only Muse Spark 1.2 measured
MedCode (Vals AI)41.4%49.4%Muse Spark 1.2
SimpleQA Verified33.6%60.3%Muse Spark 1.2
LMArena Text: scienceNot measured1500Only Muse Spark 1.2 measured
LMArena Text: medicine and healthcareNot measured1496Only Muse Spark 1.2 measured
LMArena Text: legal and governmentNot measured1517Only Muse Spark 1.2 measured
LMArena Text: business and financeNot measured1484Only Muse Spark 1.2 measured
Neither model has a result on the other 9 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
Design Arena: websites12371312Muse Spark 1.2
Design Arena: UI components12331299Muse Spark 1.2
Design Arena: game dev12071300Muse Spark 1.2
Design Arena: data viz11801334Muse Spark 1.2
Design Arena: 3D12081300Muse Spark 1.2
Design Arena: all code categories12291312Muse Spark 1.2
Design Arena: SVG11841283Muse Spark 1.2
Design Arena: ASCII art10901284Muse Spark 1.2
LiveBench designNot measured67.1%Only Muse Spark 1.2 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index13
General benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse Spark 1.2Leader
LiveBench data analysisNot measured76.5%Only Muse Spark 1.2 measured
Public Benefits Bench (Vals AI)Not measured68.5%Only Muse Spark 1.2 measured
SAGE (Vals AI)Not measured47.7%Only Muse Spark 1.2 measured
MedScribe (Vals AI)80.4%90.1%Muse Spark 1.2
Vals Multimodal IndexNot measured69.8%Only Muse Spark 1.2 measured
Long context reasoning (AA-LCR)79.7%79.0%DeepSeek V4 Flash 0731
DTBench90.9%94.7%Muse Spark 1.2
LMCA41.7%48.4%Muse Spark 1.2
LMArena TextNot measured1482Only Muse Spark 1.2 measured
LMArena Text: instruction followingNot measured1462Only Muse Spark 1.2 measured
LMArena Text: creative writingNot measured1436Only Muse Spark 1.2 measured
LMArena VisionNot measured1304Only Muse Spark 1.2 measured
LMArena Text: EnglishNot measured1483Only Muse Spark 1.2 measured
LMArena Text: non-EnglishNot measured1476Only Muse Spark 1.2 measured
LMArena Text: ChineseNot measured1509Only Muse Spark 1.2 measured
LMArena Text: KoreanNot measured1462Only Muse Spark 1.2 measured
LMArena Text: FrenchNot measured1495Only Muse Spark 1.2 measured
LMArena Text: SpanishNot measured1484Only Muse Spark 1.2 measured
LMArena Text: RussianNot measured1483Only Muse Spark 1.2 measured
LMArena Text: multi-turnNot measured1502Only Muse Spark 1.2 measured
LMArena Text: longer queriesNot measured1473Only Muse Spark 1.2 measured
LMArena Text: writing and languageNot measured1453Only Muse Spark 1.2 measured
LMArena Text: entertainment and mediaNot measured1443Only Muse Spark 1.2 measured
LMArena Vision: EnglishNot measured1291Only Muse Spark 1.2 measured
LMArena Vision: reading textNot measured1313Only Muse Spark 1.2 measured
Neither model has a result on the other 23 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.2
BenchmarkDeepSeek V4 Flash 0731Muse 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

DeepSeek V4 Flash 0731$0.0003Fits in one request
Muse Spark 1.2$0.0034Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0078Fits in one request
Muse Spark 1.2$0.075Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.031Fits in one request
Muse Spark 1.2$0.292Fits in one request

DeepSeek V4 Flash 0731 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 DeepSeek V4 Flash 0731 and Muse Spark 1.2
SpecificationDeepSeek V4 Flash 0731Meta Muse Spark 1.2
MakerDeepSeekMeta
WeightsOpen weightsNo public weights listed
ReleasedJuly 31, 2026August 5, 2026
Context window1.05M1.05M
Input $/Mtok$0.14$1.25
Output $/Mtok$0.28$4.25
Coding index51.855.7
Independent measurements behind it45
Cost per solved task$0.01$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than Muse Spark 1.2 for coding?

Pick Muse Spark 1.2 for coding: it scores 55.7 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731. Pick DeepSeek V4 Flash 0731 for output tokens 15.2x cheaper ($0.28 vs $4.25 per million) and a lower cost per solved task ($0.01 against $0.64).

Which is cheaper, DeepSeek V4 Flash 0731 or Muse Spark 1.2?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.28 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and Muse Spark 1.2 $0.64.

Which has the bigger context window, DeepSeek V4 Flash 0731 or Muse Spark 1.2?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Flash 0731 vs Muse Spark 1.2 comparison based on?

43 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4 Flash 0731's coding index rests on 4 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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<iframe src="https://llmbenchmark.ai/embed/compare/deepseek-v4-flash-0731-vs-meta-muse-spark-1-2" title="DeepSeek V4 Flash 0731 vs Muse Spark 1.2, LLMBenchmark.ai" width="100%" height="360" style="border:0;max-width:100%" loading="lazy"></iframe>
<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/deepseek-v4-flash-0731-vs-meta-muse-spark-1-2">LLMBenchmark.ai, DeepSeek V4 Flash 0731 vs Muse Spark 1.2</a></p>