LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

Muse Spark Open vs Qwen3.5 397B A17B

Updated October 21, 2026. 12 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Muse Spark OpenMeta
Coding
62.1
Overall
No data
Output $/M
$4.25
11
Qwen3.5 397B A17BQwen
Coding
28.6
Overall
21.4
Output $/M
$2.34
1
vs boards won of 12 shared

Decision reading

Pick Muse Spark Open for coding: it scores 62.1 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B.

Pick Qwen3.5 397B A17B when output tokens cost 1.8x less, or when the benchmark that matters is GPQA Diamond (Artificial Analysis run), where it leads.

Shared results
12
Muse Spark Open only
14
Qwen3.5 397B A17B only
53
Like-for-like categories
6 of 9

Shared results can support a head-to-head reading. Results only one model has describe coverage, not superiority.

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
Muse Spark Open 62.1 from 2 benchmarks, Qwen3.5 397B A17B 28.6 from 1 benchmark.
Widest category
Coding, 20.4 points apart on average over 5 shared benchmarks.
Widest single gap
ALE-Bench: Muse Spark Open 1590.1 against Qwen3.5 397B A17B 621.9, 32.3 points apart on a 0 to 100 scale.
Output price
Muse Spark Open $4.25 against Qwen3.5 397B A17B $2.34 per million output tokens, 1.8x apart.
Context window
Muse Spark Open takes 1.05M tokens, Qwen3.5 397B A17B 262K.

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
CategoryMuse Spark OpenBarsQwen3.5 397B A17BTies
Coding50
Intelligence10
Agentic work10
Reasoning11
Web design20
General10
All shared boards111
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
Coding benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
LiveBench coding73.6%Not measuredOnly Muse Spark Open measured
LMArena WebDev15281400Muse Spark Open
Terminal-Bench 4 (Vals AI)6.6%Not measuredOnly Muse Spark Open measured
Vibe Code Bench (Vals AI)76.2%Not measuredOnly Muse Spark Open measured
Code migration (Vals AI)21.2%Not measuredOnly Muse Spark Open measured
SciCode58.4%44.8%Muse Spark Open
Terminal-Bench Hard (Artificial Analysis run)Not measured40.9%Only Qwen3.5 397B A17B measured
ALE-Bench1590.1621.9Muse Spark Open
LMArena Text: codingNot measured1464Only Qwen3.5 397B A17B measured
LMArena Text: software and ITNot measured1463Only Qwen3.5 397B A17B measured
LMArena WebDev: React15291388Muse Spark Open
LMArena WebDev: HTML14951410Muse Spark Open
Neither model has a result on the other 26 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index10
Intelligence benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
AA Intelligence IndexNot measured21.4Only Qwen3.5 397B A17B measured
Epoch Capabilities Index155.1146.8Muse Spark Open
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
LiveBench research80.3%Not measuredOnly Muse Spark Open measured
LiveBench browser36.0%Not measuredOnly Muse Spark Open measured
LiveBench long agentic18.9%Not measuredOnly Muse Spark Open measured
Finance Agent (Vals AI)61.3%Not measuredOnly Muse Spark Open measured
Tax Agent Bench (Vals AI)26.3%Not measuredOnly Muse Spark Open measured
Legal Research Bench (Vals AI)38.5%Not measuredOnly Muse Spark Open measured
Excel Modeling Benchmark (Vals AI)53.7%Not measuredOnly Muse Spark Open measured
τ²-Bench TelecomNot measured95.6%Only Qwen3.5 397B A17B measured
APEX-Agents33.4%24.9%Muse Spark Open
Neither model has a result on the other 30 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index11
Reasoning benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
LiveBench reasoning73.7%Not measuredOnly Muse Spark Open measured
GPQA Diamond (Artificial Analysis run)89.0%89.3%Qwen3.5 397B A17B
Humanity's Last Exam (Artificial Analysis run)43.9%29.0%Muse Spark Open
GPQA Diamond (Epoch AI run)Not measured86.4%Only Qwen3.5 397B A17B measured
Mystery game puzzlesNot measured18.0%Only Qwen3.5 397B A17B measured
LMArena Text: hard promptsNot measured1448Only Qwen3.5 397B A17B measured
LMArena Text: expertNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: hard prompts in EnglishNot measured1450Only Qwen3.5 397B A17B measured
LMArena Vision: diagramsNot measured1277Only Qwen3.5 397B A17B measured
LMArena Vision: homeworkNot measured1292Only Qwen3.5 397B A17B measured
Neither model has a result on the other 11 boards here
MathDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Math benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
OTIS Mock AIMENot measured88.9%Only Qwen3.5 397B A17B measured
FrontierMath, tiers 1 to 3Not measured31.2%Only Qwen3.5 397B A17B measured
LMArena Text: mathNot measured1453Only Qwen3.5 397B A17B measured
LMArena Text: mathematical workNot measured1454Only Qwen3.5 397B A17B measured
Neither model has a result on the other 9 boards here
KnowledgeDirectional onlyPublic boards, shown as published, kept out of the index4 boards, none shared
Knowledge benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
LMArena Text: scienceNot measured1457Only Qwen3.5 397B A17B measured
LMArena Text: medicine and healthcareNot measured1455Only Qwen3.5 397B A17B measured
LMArena Text: legal and governmentNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: business and financeNot measured1435Only Qwen3.5 397B A17B measured
Neither model has a result on the other 13 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index20
Web design benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
Design Arena: websites13111191Muse Spark Open
Design Arena: UI componentsNot measured1163Only Qwen3.5 397B A17B measured
Design Arena: game dev12901141Muse Spark Open
Design Arena: data vizNot measured1175Only Qwen3.5 397B A17B measured
Design Arena: 3DNot measured1161Only Qwen3.5 397B A17B measured
Design Arena: all code categoriesNot measured1180Only Qwen3.5 397B A17B measured
Design Arena: SVGNot measured1139Only Qwen3.5 397B A17B measured
LiveBench design60.3%Not measuredOnly Muse Spark Open measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index10
General benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
LiveBench data analysis60.2%Not measuredOnly Muse Spark Open measured
IFBenchNot measured78.8%Only Qwen3.5 397B A17B measured
Long context reasoning (AA-LCR)78.3%77.3%Muse Spark Open
DTBenchNot measured87.5%Only Qwen3.5 397B A17B measured
LMCANot measured37.9%Only Qwen3.5 397B A17B measured
LMArena TextNot measured1437Only Qwen3.5 397B A17B measured
LMArena Text: instruction followingNot measured1424Only Qwen3.5 397B A17B measured
LMArena Text: creative writingNot measured1402Only Qwen3.5 397B A17B measured
LMArena VisionNot measured1262Only Qwen3.5 397B A17B measured
LMArena Text: EnglishNot measured1443Only Qwen3.5 397B A17B measured
LMArena Text: non-EnglishNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: ChineseNot measured1498Only Qwen3.5 397B A17B measured
LMArena Text: GermanNot measured1445Only Qwen3.5 397B A17B measured
LMArena Text: JapaneseNot measured1429Only Qwen3.5 397B A17B measured
LMArena Text: KoreanNot measured1384Only Qwen3.5 397B A17B measured
LMArena Text: FrenchNot measured1462Only Qwen3.5 397B A17B measured
LMArena Text: SpanishNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: RussianNot measured1430Only Qwen3.5 397B A17B measured
LMArena Text: PolishNot measured1447Only Qwen3.5 397B A17B measured
LMArena Text: multi-turnNot measured1446Only Qwen3.5 397B A17B measured
LMArena Text: longer queriesNot measured1441Only Qwen3.5 397B A17B measured
LMArena Text: writing and languageNot measured1415Only Qwen3.5 397B A17B measured
LMArena Text: entertainment and mediaNot measured1399Only Qwen3.5 397B A17B measured
LMArena Vision: EnglishNot measured1268Only Qwen3.5 397B A17B measured
LMArena Vision: ChineseNot measured1314Only Qwen3.5 397B A17B measured
LMArena Vision: reading textNot measured1271Only Qwen3.5 397B A17B measured
LMArena Vision: humorNot measured1262Only Qwen3.5 397B A17B measured
LMArena Vision: captioningNot measured1230Only Qwen3.5 397B A17B measured
LMArena Vision: recognizing thingsNot measured1265Only Qwen3.5 397B A17B measured
LMArena Vision: creative writingNot measured1260Only Qwen3.5 397B A17B measured
Neither model has a result on the other 16 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for Muse Spark Open and Qwen3.5 397B A17B
BenchmarkMuse Spark OpenQwen3.5 397B A17BLeader
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

Muse Spark Open$0.0034Fits in one request
Qwen3.5 397B A17B$0.0016Fits in one request

Qwen3.5 397B A17B costs less

Repository review

50K input + 3K output tokens

Muse Spark Open$0.075Fits in one request
Qwen3.5 397B A17B$0.027Fits in one request

Qwen3.5 397B A17B costs less

Agent loop

200K input + 10K output tokens

Muse Spark Open$0.292Fits in one request
Qwen3.5 397B A17B$0.101Fits in one request

Qwen3.5 397B A17B 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 Muse Spark Open and Qwen3.5 397B A17B
SpecificationMeta Muse Spark OpenQwen3.5 397B A17B
MakerMetaQwen
WeightsOpen weightsOpen weights
ReleasedOctober 15, 2026February 16, 2026
Context window1.05M262K
Input $/Mtok$1.25$0.39
Output $/Mtok$4.25$2.34
Coding index62.128.6
Independent measurements behind it21
Cost per solved taskNot computableNot computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Muse Spark Open better than Qwen3.5 397B A17B for coding?

Pick Muse Spark Open for coding: it scores 62.1 on the Vibe Coding Index against 28.6 for Qwen3.5 397B A17B. Pick Qwen3.5 397B A17B when output tokens cost 1.8x less, or when the benchmark that matters is GPQA Diamond (Artificial Analysis run), where it leads.

Which is cheaper, Muse Spark Open or Qwen3.5 397B A17B?

Muse Spark Open costs $1.25 per million input tokens and $4.25 per million output tokens; Qwen3.5 397B A17B costs $0.39 and $2.34. Cost per solved task is known for neither of them.

Which has the bigger context window, Muse Spark Open or Qwen3.5 397B A17B?

Muse Spark Open, with 1.05M tokens against 262K.

How many benchmarks is the Muse Spark Open vs Qwen3.5 397B A17B comparison based on?

12 benchmarks have a result for both models as of October 21, 2026. Muse Spark Open's coding index rests on 2 independent benchmarks and Qwen3.5 397B A17B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next