DeepSeek V4 Flash 0731 vs Muse Spark 1.1

Muse Spark 1.1 leads DeepSeek V4 Flash 0731 on coding, 70.3 to 51.8 on the Vibe Coding Index, and DeepSeek V4 Flash 0731 costs 10.7x less per output token ($0.396 vs $4.25 per million). Updated October 22, 2026; 37 benchmarks have a result for both.

Replace DeepSeek V4 Flash 0731 Replace Muse Spark 1.1

DeepSeek V4 Flash 0731DeepSeek

Coding: 51.8
Overall: 55.2
Output $/M: $0.396

Muse Spark 1.1Meta

Coding: 70.3
Overall: 67.0
Output $/M: $4.25

vs boards won of 37 shared, 1 tied

DeepSeek V4 Flash 0731 or Muse Spark 1.1: which to pick

Pick Muse Spark 1.1 for coding: it scores 70.3 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731, though on 3 benchmarks against 4.

Pick DeepSeek V4 Flash 0731 for output tokens 10.7x cheaper ($0.396 vs $4.25 per million) and a lower cost per solved task ($0.01 against $0.43).

Model ADeepSeek V4 Flash 0731DeepSeek51.8/1004 independent benchmarks$0.01 per solved task Model BMuse Spark 1.1Meta70.3/1003 independent benchmarks$0.43 per solved task

371859

Shared results: 37
DeepSeek V4 Flash 0731 only: 18
Muse Spark 1.1 only: 59
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.

Coding
Vibe Coding Index, six public coding benchmarks
Muse Spark 1.1
Muse Spark 1.1 scores 70.3 against 51.8.
4 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 34.3 against 33.7.
Same board, both measured
Agentic work
AA Agentic Index
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 leads, 41.0 against 25.8.
Same board, both measured
Reasoning
GPQA Diamond
Muse Spark 1.1
Muse Spark 1.1 leads, 91.2% against 89.9%.
Same board, both measured
Knowledge
MMLU Pro
Muse Spark 1.1
Muse Spark 1.1 leads, 88.7% against 86.2%.
Same board, both measured
Web design
Design Arena: websites
Muse Spark 1.1
Muse Spark 1.1 leads, 1270 against 1237.
Same board, both measured
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.0003, Muse Spark 1.1 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
DeepSeek V4 Flash 0731
DeepSeek V4 Flash 0731 $0.01, Muse Spark 1.1 $0.43.
Published attempt cost and pass rate

At a glance

Coding index: DeepSeek V4 Flash 0731 51.8 from 4 benchmarks, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category: Math, 17.0 points apart on average over 1 shared benchmark.
Widest single gap: SimpleQA Verified: DeepSeek V4 Flash 0731 33.6% against Muse Spark 1.1 57.8%, 24.2 points apart on a 0 to 100 scale.
Output price: DeepSeek V4 Flash 0731 $0.396 against Muse Spark 1.1 $4.25 per million output tokens, 10.7x 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
Category	DeepSeek V4 Flash 0731	Muse Spark 1.1	Ties
Coding	4	4	1 tie
Intelligence	2	0
Agentic work	2	2
Reasoning	1	3
Math	1	0
Knowledge	0	5
Web design	0	8
General	1	3
All shared boards	11	25	1 tie

CodingLike-for-likeSix of these boards feed the Vibe Coding Index44

Coding benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
LMArena WebDev	Not measured	1542	Only Muse Spark 1.1 measured
AA Coding Index	69.1	71.3	Muse Spark 1.1
LiveCodeBench (Vals AI)	87.3%	85.9%	DeepSeek V4 Flash 0731
SWE-bench Verified (Vals AI)	88.8%	82.0%	DeepSeek V4 Flash 0731
Terminal-Bench 4 (Vals AI)	18.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
Vibe Code Bench (Vals AI)	74.7%	72.2%	DeepSeek V4 Flash 0731
Code migration (Vals AI)	38.6%	31.1%	DeepSeek V4 Flash 0731
ProgramBench (Vals AI)	0.0%	0.0%	Tie
IOI (Vals AI)	32.7%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench 2.1 (Vals AI)	67.0%	69.3%	Muse Spark 1.1
SkillsBench (Vals AI)	50.7%	59.2%	Muse Spark 1.1
CyberBench (Vals AI)	72.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
SciCode	50.3%	58.8%	Muse Spark 1.1
FrontierCode	18.8%	Not measured	Only DeepSeek V4 Flash 0731 measured
WeirdML	63.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
ALE-Bench	1306.1	Not measured	Only DeepSeek V4 Flash 0731 measured
LMArena Text: coding	Not measured	1498	Only Muse Spark 1.1 measured
LMArena Text: software and IT	Not measured	1498	Only Muse Spark 1.1 measured
LMArena WebDev: React	Not measured	1532	Only Muse Spark 1.1 measured
LMArena WebDev: HTML	Not measured	1540	Only Muse Spark 1.1 measured
LMArena WebDev: from an image	Not measured	1540	Only Muse Spark 1.1 measured
Neither model has a result on the other 18 boards here

IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20

Intelligence benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
AA Intelligence Index	34.3	33.7	DeepSeek V4 Flash 0731
Epoch Capabilities Index	154.8	154.1	DeepSeek V4 Flash 0731

Agentic workLike-for-likePublic boards, shown as published, kept out of the index22

Agentic work benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
AA Agentic Index	41.0	25.8	DeepSeek V4 Flash 0731
Design Arena: agents building web apps	Not measured	1207	Only Muse Spark 1.1 measured
Design Arena: agents building full-stack apps	Not measured	1199	Only Muse Spark 1.1 measured
Design Arena: agents building mobile apps	Not measured	1175	Only Muse Spark 1.1 measured
Design Arena: agents building Android apps	Not measured	1178	Only Muse Spark 1.1 measured
Design Arena: agents building Godot games	Not measured	1103	Only Muse Spark 1.1 measured
Design Arena: agents building games	Not measured	1183	Only Muse Spark 1.1 measured
Design Arena: HTML slides	Not measured	1195	Only Muse Spark 1.1 measured
Design Arena: PowerPoint slides	Not measured	1155	Only Muse Spark 1.1 measured
Design Arena: spreadsheets	Not measured	1042	Only Muse Spark 1.1 measured
Finance Agent (Vals AI)	49.5%	57.2%	Muse Spark 1.1
Tax Agent Bench (Vals AI)	28.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
Legal Research Bench (Vals AI)	30.3%	38.0%	Muse Spark 1.1
Excel Modeling Benchmark (Vals AI)	57.0%	56.4%	DeepSeek V4 Flash 0731
BioMysteryBench (Vals AI)	64.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
Terminal-Bench-Science (Vals AI)	4.3%	Not measured	Only DeepSeek V4 Flash 0731 measured
Time Horizon Index (Vals AI)	Not measured	1.7%	Only Muse Spark 1.1 measured
APEX-Agents	Not measured	31.8%	Only Muse Spark 1.1 measured
Vending-Bench 2	Not measured	$6,520	Only Muse Spark 1.1 measured
Neither model has a result on the other 22 boards here

ReasoningLike-for-likePublic boards, shown as published, kept out of the index13

Reasoning benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
GPQA Diamond	89.9%	91.2%	Muse Spark 1.1
MMMU Pro (Vals AI)	Not measured	86.6%	Only Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)	90.8%	89.8%	DeepSeek V4 Flash 0731
Humanity's Last Exam (Artificial Analysis run)	38.6%	46.2%	Muse Spark 1.1
GPQA Diamond (Epoch AI run)	91.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
ARC-AGI	89.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
ARC-AGI-2	61.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
SimpleBench	61.1%	Not measured	Only DeepSeek V4 Flash 0731 measured
Chess puzzles	32.0%	34.0%	Muse Spark 1.1
Mystery game puzzles	34.0%	Not measured	Only DeepSeek V4 Flash 0731 measured
LMArena Text: hard prompts	Not measured	1485	Only Muse Spark 1.1 measured
LMArena Text: expert	Not measured	1478	Only Muse Spark 1.1 measured
LMArena Text: hard prompts in English	Not measured	1480	Only Muse Spark 1.1 measured
LMArena Vision: diagrams	Not measured	1305	Only Muse Spark 1.1 measured
LMArena Vision: homework	Not measured	1287	Only Muse Spark 1.1 measured
Neither model has a result on the other 7 boards here

MathLike-for-likePublic boards, shown as published, kept out of the index10

Math benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
OTIS Mock AIME	94.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
FrontierMath, tiers 1 to 3	57.5%	Not measured	Only DeepSeek V4 Flash 0731 measured
FrontierMath, tier 4	24.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
ProofBench	56.0%	39.0%	DeepSeek V4 Flash 0731
LMArena Text: math	Not measured	1482	Only Muse Spark 1.1 measured
LMArena Text: mathematical work	Not measured	1487	Only Muse Spark 1.1 measured
Neither model has a result on the other 7 boards here

KnowledgeLike-for-likePublic boards, shown as published, kept out of the index05

Knowledge benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
MMLU Pro	86.2%	88.7%	Muse Spark 1.1
LegalBench (Vals AI)	77.7%	85.0%	Muse Spark 1.1
CorpFin (Vals AI)	61.9%	71.3%	Muse Spark 1.1
TaxEval (Vals AI)	70.7%	79.7%	Muse Spark 1.1
MortgageTax (Vals AI)	Not measured	66.1%	Only Muse Spark 1.1 measured
MedCode (Vals AI)	41.4%	Not measured	Only DeepSeek V4 Flash 0731 measured
SimpleQA Verified	33.6%	57.8%	Muse Spark 1.1
LMArena Text: science	Not measured	1484	Only Muse Spark 1.1 measured
LMArena Text: medicine and healthcare	Not measured	1479	Only Muse Spark 1.1 measured
LMArena Text: legal and government	Not measured	1481	Only Muse Spark 1.1 measured
LMArena Text: business and finance	Not measured	1470	Only Muse Spark 1.1 measured
Neither model has a result on the other 7 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 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
Design Arena: websites	1237	1270	Muse Spark 1.1
Design Arena: UI components	1233	1289	Muse Spark 1.1
Design Arena: game dev	1207	1269	Muse Spark 1.1
Design Arena: data viz	1180	1268	Muse Spark 1.1
Design Arena: 3D	1208	1260	Muse Spark 1.1
Design Arena: all code categories	1229	1276	Muse Spark 1.1
Design Arena: SVG	1184	1235	Muse Spark 1.1
Design Arena: ASCII art	1090	1271	Muse Spark 1.1
Neither model has a result on the other 1 board here

GeneralLike-for-likePublic boards, shown as published, kept out of the index13

General benchmarks for DeepSeek V4 Flash 0731 and Muse Spark 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
Public Benefits Bench (Vals AI)	Not measured	61.3%	Only Muse Spark 1.1 measured
SAGE (Vals AI)	Not measured	45.6%	Only Muse Spark 1.1 measured
MedScribe (Vals AI)	80.4%	88.9%	Muse Spark 1.1
Vals Multimodal Index	Not measured	66.7%	Only Muse Spark 1.1 measured
Long context reasoning (AA-LCR)	79.7%	77.7%	DeepSeek V4 Flash 0731
DTBench	90.9%	94.4%	Muse Spark 1.1
LMCA	41.7%	49.9%	Muse Spark 1.1
Surface Evolver Bench	Not measured	52.5%	Only Muse Spark 1.1 measured
LMArena Text	Not measured	1478	Only Muse Spark 1.1 measured
LMArena Text: instruction following	Not measured	1457	Only Muse Spark 1.1 measured
LMArena Text: creative writing	Not measured	1435	Only Muse Spark 1.1 measured
LMArena Vision	Not measured	1293	Only Muse Spark 1.1 measured
LMArena Text: English	Not measured	1478	Only Muse Spark 1.1 measured
LMArena Text: non-English	Not measured	1471	Only Muse Spark 1.1 measured
LMArena Text: Chinese	Not measured	1515	Only Muse Spark 1.1 measured
LMArena Text: German	Not measured	1469	Only Muse Spark 1.1 measured
LMArena Text: Japanese	Not measured	1450	Only Muse Spark 1.1 measured
LMArena Text: Korean	Not measured	1459	Only Muse Spark 1.1 measured
LMArena Text: French	Not measured	1492	Only Muse Spark 1.1 measured
LMArena Text: Spanish	Not measured	1464	Only Muse Spark 1.1 measured
LMArena Text: Russian	Not measured	1482	Only Muse Spark 1.1 measured
LMArena Text: Polish	Not measured	1499	Only Muse Spark 1.1 measured
LMArena Text: multi-turn	Not measured	1484	Only Muse Spark 1.1 measured
LMArena Text: longer queries	Not measured	1462	Only Muse Spark 1.1 measured
LMArena Text: writing and language	Not measured	1448	Only Muse Spark 1.1 measured
LMArena Text: entertainment and media	Not measured	1438	Only Muse Spark 1.1 measured
LMArena Vision: English	Not measured	1292	Only Muse Spark 1.1 measured
LMArena Vision: Chinese	Not measured	1348	Only Muse Spark 1.1 measured
LMArena Vision: reading text	Not measured	1301	Only Muse Spark 1.1 measured
LMArena Vision: humor	Not measured	1288	Only Muse Spark 1.1 measured
LMArena Vision: creative writing	Not measured	1253	Only Muse Spark 1.1 measured
LMArena Document	Not measured	1465	Only Muse Spark 1.1 measured
Neither model has a result on the other 14 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 1.1
Benchmark	DeepSeek V4 Flash 0731	Muse Spark 1.1	Leader
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 1.1$0.0034Fits in one request

DeepSeek V4 Flash 0731 costs less

Repository review

50K input + 3K output tokens

DeepSeek V4 Flash 0731$0.0082Fits in one request

Muse Spark 1.1$0.075Fits in one request

DeepSeek V4 Flash 0731 costs less

Agent loop

200K input + 10K output tokens

DeepSeek V4 Flash 0731$0.032Fits in one request

Muse Spark 1.1$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 1.1
Specification	DeepSeek V4 Flash 0731	Meta Muse Spark 1.1
Maker	DeepSeek	Meta
Weights	Open weights	No public weights listed
Released	July 31, 2026	July 16, 2026
Context window	1.05M	1.05M
Input $/Mtok	$0.14	$1.25
Output $/Mtok	$0.396	$4.25
Coding index	51.8	70.3
Independent measurements behind it	4	3
Cost per solved task	$0.01	$0.43
Source	OpenRouter listing	OpenRouter listing

Questions

Is DeepSeek V4 Flash 0731 better than Muse Spark 1.1 for coding?

Pick Muse Spark 1.1 for coding: it scores 70.3 on the Vibe Coding Index against 51.8 for DeepSeek V4 Flash 0731, though on 3 benchmarks against 4. Pick DeepSeek V4 Flash 0731 for output tokens 10.7x cheaper ($0.396 vs $4.25 per million) and a lower cost per solved task ($0.01 against $0.43).

Which is cheaper, DeepSeek V4 Flash 0731 or Muse Spark 1.1?

DeepSeek V4 Flash 0731 costs $0.14 per million input tokens and $0.396 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Per solved SWE-bench Verified task, DeepSeek V4 Flash 0731 costs $0.01 and Muse Spark 1.1 $0.43.

Which has the bigger context window, DeepSeek V4 Flash 0731 or Muse Spark 1.1?

Neither: both take 1.05M tokens.

How many benchmarks is the DeepSeek V4 Flash 0731 vs Muse Spark 1.1 comparison based on?

37 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 1.1's on 3. 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-1-1" title="DeepSeek V4 Flash 0731 vs Muse Spark 1.1, 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-1-1">LLMBenchmark.ai, DeepSeek V4 Flash 0731 vs Muse Spark 1.1</a></p>

DeepSeek V4 Flash 0731 or Muse Spark 1.1: which to pick

Which one for your work

Coding

Intelligence

Agentic work

Reasoning

Knowledge

Web design

Long documents

Everyday cost

Cost per solved task

At a glance

Benchmark by benchmark

What each workload costs

Chat turn

Repository review

Agent loop

Specification differences

Questions

Compare next