LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

Muse Spark 1.1 vs Qwen3.5-35B-A3B

Updated October 21, 2026. 39 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Muse Spark 1.1Meta
Coding
48.9
Overall
33.7
Output $/M
$4.25
39
Qwen3.5-35B-A3BQwen
Coding
7.7
Overall
19.3
Output $/M
$1.00
0
vs boards won of 39 shared

Decision reading

Pick Muse Spark 1.1 for coding: it scores 48.9 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B.

Pick Qwen3.5-35B-A3B when output tokens cost 4.3x less.

Shared results
39
Muse Spark 1.1 only
57
Qwen3.5-35B-A3B only
6
Like-for-like categories
7 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 1.1 48.9 from 1 benchmark, Qwen3.5-35B-A3B 7.7 from 1 benchmark.
Widest category
Agentic work, 37.9 points apart on average over 1 shared benchmark.
Widest single gap
LMArena WebDev: React: Muse Spark 1.1 1532 against Qwen3.5-35B-A3B 1238, 49.0 points apart on a 0 to 100 scale.
Output price
Muse Spark 1.1 $4.25 against Qwen3.5-35B-A3B $1.00 per million output tokens, 4.3x apart.
Context window
Muse Spark 1.1 takes 1.05M tokens, Qwen3.5-35B-A3B 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 1.1BarsQwen3.5-35B-A3BTies
Coding50
Intelligence20
Agentic work10
Reasoning50
Math20
Knowledge40
General200
All shared boards390
CodingLike-for-likeFour of these boards feed the Vibe Coding Index50
Coding benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
LMArena WebDev15421254Muse Spark 1.1
AA Coding Index71.3Not measuredOnly Muse Spark 1.1 measured
LiveCodeBench (Vals AI)85.9%Not measuredOnly Muse Spark 1.1 measured
SWE-bench Verified (Vals AI)82.0%Not measuredOnly Muse Spark 1.1 measured
Vibe Code Bench (Vals AI)72.2%Not measuredOnly Muse Spark 1.1 measured
Code migration (Vals AI)31.1%Not measuredOnly Muse Spark 1.1 measured
ProgramBench (Vals AI)0.0%Not measuredOnly Muse Spark 1.1 measured
Terminal-Bench 2.1 (Vals AI)69.3%Not measuredOnly Muse Spark 1.1 measured
SkillsBench (Vals AI)59.2%Not measuredOnly Muse Spark 1.1 measured
SciCode58.8%Not measuredOnly Muse Spark 1.1 measured
Terminal-Bench Hard (Artificial Analysis run)Not measured26.5%Only Qwen3.5-35B-A3B measured
ALE-BenchNot measured221.8Only Qwen3.5-35B-A3B measured
LMArena Text: coding14981410Muse Spark 1.1
LMArena Text: software and IT14981415Muse Spark 1.1
LMArena WebDev: React15321238Muse Spark 1.1
LMArena WebDev: HTML15401301Muse Spark 1.1
LMArena WebDev: from an image1540Not measuredOnly Muse Spark 1.1 measured
Neither model has a result on the other 21 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
Intelligence benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
AA Intelligence Index33.719.3Muse Spark 1.1
Epoch Capabilities Index154.1142.5Muse Spark 1.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index10
Agentic work benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
AA Agentic Index25.8Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building web apps1207Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building full-stack apps1199Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building mobile apps1177Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building Android apps1184Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building Godot games1103Not measuredOnly Muse Spark 1.1 measured
Design Arena: agents building games1183Not measuredOnly Muse Spark 1.1 measured
Design Arena: HTML slides1194Not measuredOnly Muse Spark 1.1 measured
Design Arena: PowerPoint slides1156Not measuredOnly Muse Spark 1.1 measured
Design Arena: spreadsheets974Not measuredOnly Muse Spark 1.1 measured
Finance Agent (Vals AI)57.2%Not measuredOnly Muse Spark 1.1 measured
Legal Research Bench (Vals AI)38.0%Not measuredOnly Muse Spark 1.1 measured
Excel Modeling Benchmark (Vals AI)56.4%Not measuredOnly Muse Spark 1.1 measured
Time Horizon Index (Vals AI)1.7%Not measuredOnly Muse Spark 1.1 measured
τ²-Bench TelecomNot measured89.2%Only Qwen3.5-35B-A3B measured
APEX-Agents31.8%Not measuredOnly Muse Spark 1.1 measured
Vending-Bench 2$6,520$463Muse Spark 1.1
Neither model has a result on the other 22 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index50
Reasoning benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
GPQA Diamond91.2%Not measuredOnly Muse Spark 1.1 measured
MMMU Pro (Vals AI)86.6%Not measuredOnly Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)89.8%84.5%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)46.2%21.0%Muse Spark 1.1
GPQA Diamond (Epoch AI run)Not measured83.5%Only Qwen3.5-35B-A3B measured
Chess puzzles34.0%Not measuredOnly Muse Spark 1.1 measured
LMArena Text: hard prompts14851400Muse Spark 1.1
LMArena Text: expert14781408Muse Spark 1.1
LMArena Text: hard prompts in English14801411Muse Spark 1.1
LMArena Vision: diagrams1305Not measuredOnly Muse Spark 1.1 measured
LMArena Vision: homework1287Not measuredOnly Muse Spark 1.1 measured
Neither model has a result on the other 10 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index20
Math benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
OTIS Mock AIMENot measured70.0%Only Qwen3.5-35B-A3B measured
ProofBench39.0%Not measuredOnly Muse Spark 1.1 measured
LMArena Text: math14821404Muse Spark 1.1
LMArena Text: mathematical work14871410Muse Spark 1.1
Neither model has a result on the other 9 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index40
Knowledge benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
MMLU Pro88.7%Not measuredOnly Muse Spark 1.1 measured
LegalBench (Vals AI)85.0%Not measuredOnly Muse Spark 1.1 measured
CorpFin (Vals AI)71.3%Not measuredOnly Muse Spark 1.1 measured
TaxEval (Vals AI)79.7%Not measuredOnly Muse Spark 1.1 measured
MortgageTax (Vals AI)66.1%Not measuredOnly Muse Spark 1.1 measured
SimpleQA Verified57.8%Not measuredOnly Muse Spark 1.1 measured
LMArena Text: science14841413Muse Spark 1.1
LMArena Text: medicine and healthcare14791421Muse Spark 1.1
LMArena Text: legal and government14811399Muse Spark 1.1
LMArena Text: business and finance14701394Muse Spark 1.1
Neither model has a result on the other 7 boards here
Web designDirectional onlyPublic boards, shown as published, kept out of the index8 boards, none shared
Web design benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
Design Arena: websites1270Not measuredOnly Muse Spark 1.1 measured
Design Arena: UI components1290Not measuredOnly Muse Spark 1.1 measured
Design Arena: game dev1269Not measuredOnly Muse Spark 1.1 measured
Design Arena: data viz1268Not measuredOnly Muse Spark 1.1 measured
Design Arena: 3D1260Not measuredOnly Muse Spark 1.1 measured
Design Arena: all code categories1276Not measuredOnly Muse Spark 1.1 measured
Design Arena: SVG1234Not measuredOnly Muse Spark 1.1 measured
Design Arena: ASCII art1270Not measuredOnly Muse Spark 1.1 measured
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index200
General benchmarks for Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
Public Benefits Bench (Vals AI)61.3%Not measuredOnly Muse Spark 1.1 measured
SAGE (Vals AI)45.6%Not measuredOnly Muse Spark 1.1 measured
MedScribe (Vals AI)88.9%Not measuredOnly Muse Spark 1.1 measured
Vals Multimodal Index66.7%Not measuredOnly Muse Spark 1.1 measured
IFBenchNot measured72.5%Only Qwen3.5-35B-A3B measured
Long context reasoning (AA-LCR)77.7%72.0%Muse Spark 1.1
DTBench94.4%80.0%Muse Spark 1.1
LMCA49.9%29.5%Muse Spark 1.1
Surface Evolver Bench52.5%Not measuredOnly Muse Spark 1.1 measured
LMArena Text14781395Muse Spark 1.1
LMArena Text: instruction following14571379Muse Spark 1.1
LMArena Text: creative writing14351347Muse Spark 1.1
LMArena Vision1293Not measuredOnly Muse Spark 1.1 measured
LMArena Text: English14781407Muse Spark 1.1
LMArena Text: non-English14711378Muse Spark 1.1
LMArena Text: Chinese15151457Muse Spark 1.1
LMArena Text: German14691367Muse Spark 1.1
LMArena Text: Japanese14501326Muse Spark 1.1
LMArena Text: Korean14591355Muse Spark 1.1
LMArena Text: French14921412Muse Spark 1.1
LMArena Text: Spanish14641390Muse Spark 1.1
LMArena Text: Russian14821376Muse Spark 1.1
LMArena Text: Polish14991385Muse Spark 1.1
LMArena Text: multi-turn14841390Muse Spark 1.1
LMArena Text: longer queries14621389Muse Spark 1.1
LMArena Text: writing and language14481365Muse Spark 1.1
LMArena Text: entertainment and media14381347Muse Spark 1.1
LMArena Vision: English1292Not measuredOnly Muse Spark 1.1 measured
LMArena Vision: Chinese1348Not measuredOnly Muse Spark 1.1 measured
LMArena Vision: reading text1301Not measuredOnly Muse Spark 1.1 measured
LMArena Vision: humor1288Not measuredOnly Muse Spark 1.1 measured
LMArena Vision: creative writing1253Not measuredOnly Muse Spark 1.1 measured
LMArena Document1465Not measuredOnly Muse Spark 1.1 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 Muse Spark 1.1 and Qwen3.5-35B-A3B
BenchmarkMuse Spark 1.1Qwen3.5-35B-A3BLeader
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 1.1$0.0034Fits in one request
Qwen3.5-35B-A3B$0.0006Fits in one request

Qwen3.5-35B-A3B costs less

Repository review

50K input + 3K output tokens

Muse Spark 1.1$0.075Fits in one request
Qwen3.5-35B-A3B$0.010Fits in one request

Qwen3.5-35B-A3B costs less

Agent loop

200K input + 10K output tokens

Muse Spark 1.1$0.292Fits in one request
Qwen3.5-35B-A3B$0.038Fits in one request

Qwen3.5-35B-A3B 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 1.1 and Qwen3.5-35B-A3B
SpecificationMeta Muse Spark 1.1Qwen3.5-35B-A3B
MakerMetaQwen
WeightsNo public weights listedOpen weights
ReleasedJuly 16, 2026February 25, 2026
Context window1.05M262K
Input $/Mtok$1.25$0.14
Output $/Mtok$4.25$1.00
Coding index48.97.7
Independent measurements behind it11
Cost per solved task$0.43Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is Muse Spark 1.1 better than Qwen3.5-35B-A3B for coding?

Pick Muse Spark 1.1 for coding: it scores 48.9 on the Vibe Coding Index against 7.7 for Qwen3.5-35B-A3B. Pick Qwen3.5-35B-A3B when output tokens cost 4.3x less.

Which is cheaper, Muse Spark 1.1 or Qwen3.5-35B-A3B?

Muse Spark 1.1 costs $1.25 per million input tokens and $4.25 per million output tokens; Qwen3.5-35B-A3B costs $0.14 and $1.00. Cost per solved task is known for Muse Spark 1.1 only.

Which has the bigger context window, Muse Spark 1.1 or Qwen3.5-35B-A3B?

Muse Spark 1.1, with 1.05M tokens against 262K.

How many benchmarks is the Muse Spark 1.1 vs Qwen3.5-35B-A3B comparison based on?

39 benchmarks have a result for both models as of October 21, 2026. Muse Spark 1.1's coding index rests on 1 independent benchmark and Qwen3.5-35B-A3B's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next