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DeepSeek V4.1 Flash vs Muse Spark 1.2

DeepSeek V4.1 Flash leads Muse Spark 1.2 on coding, 62.5 to 55.7 on the Vibe Coding Index, and DeepSeek V4.1 Flash costs 5.1x less per output token ($0.84 vs $4.25 per million). Updated October 22, 2026; 77 benchmarks have a result for both.

Replace DeepSeek V4.1 Flash Replace Muse Spark 1.2
DeepSeek V4.1 FlashDeepSeek
Coding
62.5
Overall
62.4
Output $/M
$0.84
35
Muse Spark 1.2Meta
Coding
55.7
Overall
60.4
Output $/M
$4.25
41
vs boards won of 77 shared, 1 tied

DeepSeek V4.1 Flash or Muse Spark 1.2: which to pick

Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 55.7 for Muse Spark 1.2.

Pick Muse Spark 1.2 for work measured by SciCode or LMArena Text: coding, where it leads.

Model ADeepSeek V4.1 FlashDeepSeek62.5/1005 independent benchmarksNo cost per solved taskModel BMuse Spark 1.2Meta55.7/1005 independent benchmarks$0.64 per solved task
Shared results
77
DeepSeek V4.1 Flash only
24
Muse Spark 1.2 only
20
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 V4.1 Flash 62.5 from 5 benchmarks, Muse Spark 1.2 55.7 from 5 benchmarks.
Widest category
Agentic work, 11.1 points apart on average over 10 shared benchmarks.
Widest single gap
LiveBench browser: DeepSeek V4.1 Flash 84.0% against Muse Spark 1.2 36.0%, 48.0 points apart on a 0 to 100 scale.
Output price
DeepSeek V4.1 Flash $0.84 against Muse Spark 1.2 $4.25 per million output tokens, 5.1x 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
CategoryDeepSeek V4.1 FlashBarsMuse Spark 1.2Ties
Coding1131 tie
Intelligence11
Agentic work64
Reasoning34
Math21
Knowledge07
Web design54
General717
All shared boards35411 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index113
Coding benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
LiveBench coding90.2%78.2%DeepSeek V4.1 Flash
LMArena WebDev16181534DeepSeek V4.1 Flash
AA Coding IndexNot measured72.2Only Muse Spark 1.2 measured
SWE-bench Verified (Vals AI)Not measured86.6%Only Muse Spark 1.2 measured
Terminal-Bench 4 (Vals AI)19.7%6.1%DeepSeek V4.1 Flash
Vibe Code Bench (Vals AI)84.7%79.1%DeepSeek V4.1 Flash
Code migration (Vals AI)45.6%29.9%DeepSeek V4.1 Flash
ProgramBench (Vals AI)0.5%0.5%Tie
IOI (Vals AI)40.3%21.8%DeepSeek V4.1 Flash
Terminal-Bench 2.1 (Vals AI)74.5%69.7%DeepSeek V4.1 Flash
SWE-bench Multimodal (Vals AI)46.5%Not measuredOnly DeepSeek V4.1 Flash measured
Vibe Code Bench 1-100 (Vals AI)16.4%Not measuredOnly DeepSeek V4.1 Flash measured
SkillsBench (Vals AI)69.8%53.0%DeepSeek V4.1 Flash
CyberBench (Vals AI)73.7%69.5%DeepSeek V4.1 Flash
SciCode51.9%57.4%Muse Spark 1.2
FrontierCode43.9%Not measuredOnly DeepSeek V4.1 Flash measured
FrontierSWENot measured12.0%Only Muse Spark 1.2 measured
WeirdMLNot measured60.3%Only Muse Spark 1.2 measured
ALE-Bench1092.3Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text: coding15021505Muse Spark 1.2
LMArena Text: software and IT14961505Muse Spark 1.2
LMArena WebDev: React16281526DeepSeek V4.1 Flash
LMArena WebDev: HTML16121543DeepSeek V4.1 Flash
LMArena WebDev: from an image1606Not measuredOnly DeepSeek V4.1 Flash measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index11
Intelligence benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
AA Intelligence Index24.739.6Muse Spark 1.2
Epoch Capabilities Index155.9155.1DeepSeek V4.1 Flash
Agentic workLike-for-likePublic boards, shown as published, kept out of the index64
Agentic work benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
AA Agentic IndexNot measured43.2Only Muse Spark 1.2 measured
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 measured1179Only Muse Spark 1.2 measured
Design Arena: HTML slidesNot measured1085Only Muse Spark 1.2 measured
Design Arena: PowerPoint slidesNot measured1172Only Muse Spark 1.2 measured
LiveBench research86.8%67.7%DeepSeek V4.1 Flash
LiveBench browser84.0%36.0%DeepSeek V4.1 Flash
LiveBench long agentic40.1%21.3%DeepSeek V4.1 Flash
SREBench (Vals AI)0.8%0.0%DeepSeek V4.1 Flash
Finance Agent (Vals AI)53.5%60.6%Muse Spark 1.2
Tax Agent Bench (Vals AI)26.6%32.8%Muse Spark 1.2
Legal Research Bench (Vals AI)41.4%43.8%Muse Spark 1.2
Excel Modeling Benchmark (Vals AI)57.2%57.0%DeepSeek V4.1 Flash
BioMysteryBench (Vals AI)67.8%64.8%DeepSeek V4.1 Flash
Terminal-Bench-Science (Vals AI)0.0%Not measuredOnly DeepSeek V4.1 Flash measured
Vals Science Index29.6%Not measuredOnly DeepSeek V4.1 Flash measured
APEX-Agents39.5%45.4%Muse Spark 1.2
Neither model has a result on the other 21 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index34
Reasoning benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
LiveBench reasoning86.7%90.0%Muse Spark 1.2
MysteryMechanism (Vals AI)21.2%Not measuredOnly DeepSeek V4.1 Flash measured
MMMU Pro (Vals AI)Not measured86.1%Only Muse Spark 1.2 measured
GPQA Diamond (Artificial Analysis run)Not measured90.4%Only Muse Spark 1.2 measured
Humanity's Last Exam (Artificial Analysis run)39.2%45.5%Muse Spark 1.2
GPQA Diamond (Epoch AI run)89.8%Not measuredOnly DeepSeek V4.1 Flash measured
ARC-AGI94.5%Not measuredOnly DeepSeek V4.1 Flash measured
ARC-AGI-272.9%Not measuredOnly DeepSeek V4.1 Flash measured
SimpleBenchNot measured74.5%Only Muse Spark 1.2 measured
Chess puzzles48.0%27.0%DeepSeek V4.1 Flash
Mystery game puzzles43.0%Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text: hard prompts14831489Muse Spark 1.2
LMArena Text: expert15011475DeepSeek V4.1 Flash
LMArena Text: hard prompts in English14881487DeepSeek V4.1 Flash
LMArena Vision: diagrams12971317Muse Spark 1.2
LMArena Vision: homework1307Not measuredOnly DeepSeek V4.1 Flash measured
Neither model has a result on the other 6 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
OTIS Mock AIME98.3%Not measuredOnly DeepSeek V4.1 Flash measured
FrontierMath, tiers 1 to 367.4%Not measuredOnly DeepSeek V4.1 Flash measured
FrontierMath, tier 426.8%Not measuredOnly DeepSeek V4.1 Flash measured
ProofBench54.0%43.0%DeepSeek V4.1 Flash
LMArena Text: math14781484Muse Spark 1.2
LMArena Text: mathematical work14851480DeepSeek V4.1 Flash
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index07
Knowledge benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
MMLU ProNot measured88.3%Only Muse Spark 1.2 measured
LegalBench (Vals AI)83.3%85.3%Muse Spark 1.2
CorpFin (Vals AI)Not measured70.9%Only Muse Spark 1.2 measured
TaxEval (Vals AI)Not measured80.4%Only Muse Spark 1.2 measured
MortgageTax (Vals AI)Not measured65.4%Only Muse Spark 1.2 measured
MedCode (Vals AI)41.2%49.4%Muse Spark 1.2
SimpleQA Verified42.9%60.3%Muse Spark 1.2
LMArena Text: science14691500Muse Spark 1.2
LMArena Text: medicine and healthcare14841496Muse Spark 1.2
LMArena Text: legal and government14431517Muse Spark 1.2
LMArena Text: business and finance14611484Muse Spark 1.2
Neither model has a result on the other 7 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index54
Web design benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
Design Arena: websites13081312Muse Spark 1.2
Design Arena: UI components13121298DeepSeek V4.1 Flash
Design Arena: game dev13301301DeepSeek V4.1 Flash
Design Arena: data viz12911334Muse Spark 1.2
Design Arena: 3D13551301DeepSeek V4.1 Flash
Design Arena: all code categories13201312DeepSeek V4.1 Flash
Design Arena: SVG12451284Muse Spark 1.2
Design Arena: ASCII art12651284Muse Spark 1.2
LiveBench design79.2%67.1%DeepSeek V4.1 Flash
GeneralLike-for-likePublic boards, shown as published, kept out of the index717
General benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 FlashMuse Spark 1.2Leader
LiveBench data analysis79.3%76.5%DeepSeek V4.1 Flash
Public Benefits Bench (Vals AI)64.3%68.5%Muse Spark 1.2
SAGE (Vals AI)47.9%47.7%DeepSeek V4.1 Flash
MedScribe (Vals AI)85.5%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%DeepSeek V4.1 Flash
DTBench89.9%94.7%Muse Spark 1.2
LMCA47.0%48.4%Muse Spark 1.2
Surface Evolver Bench46.3%Not measuredOnly DeepSeek V4.1 Flash measured
Furniture assembly34.2%Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text14641482Muse Spark 1.2
LMArena Text: instruction following14731462DeepSeek V4.1 Flash
LMArena Text: creative writing14371436DeepSeek V4.1 Flash
LMArena Vision12781304Muse Spark 1.2
LMArena Text: English14731483Muse Spark 1.2
LMArena Text: non-English14491476Muse Spark 1.2
LMArena Text: Chinese15011509Muse Spark 1.2
LMArena Text: German1470Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text: Japanese1432Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text: Korean14361462Muse Spark 1.2
LMArena Text: French14651495Muse Spark 1.2
LMArena Text: Spanish14591484Muse Spark 1.2
LMArena Text: Russian14671483Muse Spark 1.2
LMArena Text: Polish1457Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Text: multi-turn14611502Muse Spark 1.2
LMArena Text: longer queries14731473DeepSeek V4.1 Flash
LMArena Text: writing and language14501453Muse Spark 1.2
LMArena Text: entertainment and media14451443DeepSeek V4.1 Flash
LMArena Vision: English12881291Muse Spark 1.2
LMArena Vision: Chinese1327Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Vision: reading text12821313Muse Spark 1.2
LMArena Vision: humor1260Not measuredOnly DeepSeek V4.1 Flash measured
LMArena Vision: creative writing1275Not measuredOnly DeepSeek V4.1 Flash measured
Neither model has a result on the other 13 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for DeepSeek V4.1 Flash and Muse Spark 1.2
BenchmarkDeepSeek V4.1 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

DeepSeek V4.1 Flash$0.0006Fits in one request
Muse Spark 1.2$0.0034Fits in one request

DeepSeek V4.1 Flash costs less

Repository review

50K input + 3K output tokens

DeepSeek V4.1 Flash$0.014Fits in one request
Muse Spark 1.2$0.075Fits in one request

DeepSeek V4.1 Flash costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4.1 Flash$0.053Fits in one request
Muse Spark 1.2$0.292Fits in one request

DeepSeek V4.1 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 DeepSeek V4.1 Flash and Muse Spark 1.2
SpecificationDeepSeek V4.1 FlashMeta Muse Spark 1.2
MakerDeepSeekMeta
WeightsOpen weightsNo public weights listed
ReleasedSeptember 10, 2026August 5, 2026
Context window1.05M1.05M
Input $/Mtok$0.2225$1.25
Output $/Mtok$0.84$4.25
Coding index62.555.7
Independent measurements behind it55
Cost per solved taskNot computable$0.64
SourceOpenRouter listingOpenRouter listing

Questions

Is DeepSeek V4.1 Flash better than Muse Spark 1.2 for coding?

Pick DeepSeek V4.1 Flash for coding: it scores 62.5 on the Vibe Coding Index against 55.7 for Muse Spark 1.2. Pick Muse Spark 1.2 for work measured by SciCode or LMArena Text: coding, where it leads.

Which is cheaper, DeepSeek V4.1 Flash or Muse Spark 1.2?

DeepSeek V4.1 Flash costs $0.2225 per million input tokens and $0.84 per million output tokens; Muse Spark 1.2 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.2 only.

Which has the bigger context window, DeepSeek V4.1 Flash or Muse Spark 1.2?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4.1 Flash vs Muse Spark 1.2 comparison based on?

77 benchmarks have a result for both models as of October 22, 2026. DeepSeek V4.1 Flash's coding index rests on 5 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-v4-1-flash-vs-meta-muse-spark-1-2" title="DeepSeek V4.1 Flash 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-v4-1-flash-vs-meta-muse-spark-1-2">LLMBenchmark.ai, DeepSeek V4.1 Flash vs Muse Spark 1.2</a></p>