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GLM 4.5V vs Muse Spark 1.1

Muse Spark 1.1 leads GLM 4.5V on the Artificial Analysis Intelligence Index, 33.7 to 7.6, and GLM 4.5V costs 2.4x less per output token ($1.80 vs $4.25 per million). Updated October 22, 2026; 33 benchmarks have a result for both.

GLM 4.5VZ.ai
Coding
No data
Overall
No data
Output $/M
$1.80
0
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
33
vs boards won of 33 shared

GLM 4.5V or Muse Spark 1.1: which to pick

Only Muse Spark 1.1 has a coding score, 70.3 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding.

Pick GLM 4.5V for output tokens 2.4x cheaper ($1.80 vs $4.25 per million).

Shared results
33
GLM 4.5V only
8
Muse Spark 1.1 only
63
Like-for-like categories
6 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
GLM 4.5V not benchmarked, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category
General, 28.0 points apart on average over 17 shared benchmarks.
Widest single gap
Long context reasoning (AA-LCR): GLM 4.5V 0.0% against Muse Spark 1.1 77.7%, 77.7 points apart on a 0 to 100 scale.
Output price
GLM 4.5V $1.80 against Muse Spark 1.1 $4.25 per million output tokens, 2.4x apart.
Context window
GLM 4.5V takes 66K tokens, Muse Spark 1.1 1.05M.

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
CategoryGLM 4.5VBarsMuse Spark 1.1Ties
Coding02
Intelligence01
Reasoning07
Math02
Knowledge04
General017
All shared boards033
CodingLike-for-likeSix of these boards feed the Vibe Coding Index02
Coding benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
LMArena WebDevNot measured1542Only Muse Spark 1.1 measured
AA Coding IndexNot measured71.3Only Muse Spark 1.1 measured
LiveCodeBench (Vals AI)Not measured85.9%Only Muse Spark 1.1 measured
SWE-bench Verified (Vals AI)Not measured82.0%Only Muse Spark 1.1 measured
Vibe Code Bench (Vals AI)Not measured72.2%Only Muse Spark 1.1 measured
Code migration (Vals AI)Not measured31.1%Only Muse Spark 1.1 measured
ProgramBench (Vals AI)Not measured0.0%Only Muse Spark 1.1 measured
Terminal-Bench 2.1 (Vals AI)Not measured69.3%Only Muse Spark 1.1 measured
SkillsBench (Vals AI)Not measured59.2%Only Muse Spark 1.1 measured
LiveCodeBench (Artificial Analysis run)60.4%Not measuredOnly GLM 4.5V measured
SciCodeNot measured58.8%Only Muse Spark 1.1 measured
Terminal-Bench Hard (Artificial Analysis run)6.8%Not measuredOnly GLM 4.5V measured
LMArena Text: coding13471498Muse Spark 1.1
LMArena Text: software and IT13531498Muse Spark 1.1
LMArena WebDev: ReactNot measured1532Only Muse Spark 1.1 measured
LMArena WebDev: HTMLNot measured1540Only Muse Spark 1.1 measured
LMArena WebDev: from an imageNot measured1540Only Muse Spark 1.1 measured
Neither model has a result on the other 22 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index01
Intelligence benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
AA Intelligence Index7.633.7Muse Spark 1.1
Epoch Capabilities IndexNot measured154.1Only Muse Spark 1.1 measured
Agentic workDirectional onlyPublic boards, shown as published, kept out of the index17 boards, none shared
Agentic work benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
AA Agentic IndexNot measured25.8Only Muse Spark 1.1 measured
Design Arena: agents building web appsNot measured1207Only Muse Spark 1.1 measured
Design Arena: agents building full-stack appsNot measured1199Only Muse Spark 1.1 measured
Design Arena: agents building mobile appsNot measured1175Only Muse Spark 1.1 measured
Design Arena: agents building Android appsNot measured1178Only Muse Spark 1.1 measured
Design Arena: agents building Godot gamesNot measured1103Only Muse Spark 1.1 measured
Design Arena: agents building gamesNot measured1183Only Muse Spark 1.1 measured
Design Arena: HTML slidesNot measured1195Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1155Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured1042Only Muse Spark 1.1 measured
Finance Agent (Vals AI)Not measured57.2%Only Muse Spark 1.1 measured
Legal Research Bench (Vals AI)Not measured38.0%Only Muse Spark 1.1 measured
Excel Modeling Benchmark (Vals AI)Not measured56.4%Only Muse Spark 1.1 measured
Time Horizon Index (Vals AI)Not measured1.7%Only Muse Spark 1.1 measured
τ²-Bench Telecom22.5%Not measuredOnly GLM 4.5V measured
APEX-AgentsNot measured31.8%Only Muse Spark 1.1 measured
Vending-Bench 2Not measured$6,520Only Muse Spark 1.1 measured
Neither model has a result on the other 24 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
GPQA DiamondNot measured91.2%Only Muse Spark 1.1 measured
MMMU Pro (Vals AI)Not measured86.6%Only Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)68.4%89.8%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)6.3%46.2%Muse Spark 1.1
Chess puzzlesNot measured34.0%Only Muse Spark 1.1 measured
LMArena Text: hard prompts13351485Muse Spark 1.1
LMArena Text: expert13531478Muse Spark 1.1
LMArena Text: hard prompts in English13571480Muse Spark 1.1
LMArena Vision: diagrams11511305Muse Spark 1.1
LMArena Vision: homework11631287Muse Spark 1.1
Kagi LLM Benchmark59.8%Not measuredOnly GLM 4.5V measured
Neither model has a result on the other 11 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index02
Math benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
AA Math Index73.0Not measuredOnly GLM 4.5V measured
AIME 2025 (Artificial Analysis run)73.0%Not measuredOnly GLM 4.5V measured
ProofBenchNot measured39.0%Only Muse Spark 1.1 measured
LMArena Text: math13541482Muse Spark 1.1
LMArena Text: mathematical work13361487Muse Spark 1.1
Neither model has a result on the other 8 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
MMLU ProNot measured88.7%Only Muse Spark 1.1 measured
LegalBench (Vals AI)Not measured85.0%Only Muse Spark 1.1 measured
CorpFin (Vals AI)Not measured71.3%Only Muse Spark 1.1 measured
TaxEval (Vals AI)Not measured79.7%Only Muse Spark 1.1 measured
MortgageTax (Vals AI)Not measured66.1%Only Muse Spark 1.1 measured
MMLU Pro (Artificial Analysis run)78.8%Not measuredOnly GLM 4.5V measured
SimpleQA VerifiedNot measured57.8%Only Muse Spark 1.1 measured
LMArena Text: science13301484Muse Spark 1.1
LMArena Text: medicine and healthcare13491479Muse Spark 1.1
LMArena Text: legal and government13381481Muse Spark 1.1
LMArena Text: business and finance13091470Muse 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 GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
Design Arena: websitesNot measured1270Only Muse Spark 1.1 measured
Design Arena: UI componentsNot measured1289Only Muse Spark 1.1 measured
Design Arena: game devNot measured1269Only Muse Spark 1.1 measured
Design Arena: data vizNot measured1268Only Muse Spark 1.1 measured
Design Arena: 3DNot measured1260Only Muse Spark 1.1 measured
Design Arena: all code categoriesNot measured1276Only Muse Spark 1.1 measured
Design Arena: SVGNot measured1235Only Muse Spark 1.1 measured
Design Arena: ASCII artNot measured1271Only 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 index017
General benchmarks for GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
Public Benefits Bench (Vals AI)Not measured61.3%Only Muse Spark 1.1 measured
SAGE (Vals AI)Not measured45.6%Only Muse Spark 1.1 measured
MedScribe (Vals AI)Not measured88.9%Only Muse Spark 1.1 measured
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
IFBench34.2%Not measuredOnly GLM 4.5V measured
Long context reasoning (AA-LCR)0.0%77.7%Muse Spark 1.1
DTBenchNot measured94.4%Only Muse Spark 1.1 measured
LMCANot measured49.9%Only Muse Spark 1.1 measured
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
LMArena Text13331478Muse Spark 1.1
LMArena Text: instruction following13111457Muse Spark 1.1
LMArena Text: creative writing12941435Muse Spark 1.1
LMArena Vision11541293Muse Spark 1.1
LMArena Text: English13621478Muse Spark 1.1
LMArena Text: non-English13031471Muse Spark 1.1
LMArena Text: Chinese13371515Muse Spark 1.1
LMArena Text: GermanNot measured1469Only Muse Spark 1.1 measured
LMArena Text: JapaneseNot measured1450Only Muse Spark 1.1 measured
LMArena Text: KoreanNot measured1459Only Muse Spark 1.1 measured
LMArena Text: FrenchNot measured1492Only Muse Spark 1.1 measured
LMArena Text: Spanish13361464Muse Spark 1.1
LMArena Text: Russian12981482Muse Spark 1.1
LMArena Text: Polish13021499Muse Spark 1.1
LMArena Text: multi-turn13331484Muse Spark 1.1
LMArena Text: longer queries13051462Muse Spark 1.1
LMArena Text: writing and language13021448Muse Spark 1.1
LMArena Text: entertainment and media13031438Muse Spark 1.1
LMArena Vision: English11831292Muse Spark 1.1
LMArena Vision: ChineseNot measured1348Only Muse Spark 1.1 measured
LMArena Vision: reading text11511301Muse Spark 1.1
LMArena Vision: humorNot measured1288Only Muse Spark 1.1 measured
LMArena Vision: creative writingNot measured1253Only Muse Spark 1.1 measured
LMArena DocumentNot measured1465Only 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 GLM 4.5V and Muse Spark 1.1
BenchmarkGLM 4.5VMuse Spark 1.1Leader
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

GLM 4.5V$0.0015Fits in one request
Muse Spark 1.1$0.0034Fits in one request

GLM 4.5V costs less

Repository review

50K input + 3K output tokens

GLM 4.5V$0.035Fits in one request
Muse Spark 1.1$0.075Fits in one request

GLM 4.5V costs less

Agent loop

200K input + 10K output tokens

GLM 4.5V$0.138Exceeds the context window
Muse Spark 1.1$0.292Fits in one request

GLM 4.5V 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 GLM 4.5V and Muse Spark 1.1
SpecificationZ.ai GLM 4.5VMeta Muse Spark 1.1
MakerZ.aiMeta
WeightsOpen weightsNo public weights listed
ReleasedAugust 11, 2025July 16, 2026
Context window66K1.05M
Input $/Mtok$0.60$1.25
Output $/Mtok$1.80$4.25
Coding indexNot benchmarked70.3
Independent measurements behind it03
Cost per solved taskNot computable$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.5V better than Muse Spark 1.1 for coding?

Only Muse Spark 1.1 has a coding score, 70.3 on the Vibe Coding Index; GLM 4.5V has none, so the two cannot be ranked on coding. Pick GLM 4.5V for output tokens 2.4x cheaper ($1.80 vs $4.25 per million).

Which is cheaper, GLM 4.5V or Muse Spark 1.1?

GLM 4.5V costs $0.60 per million input tokens and $1.80 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Cost per solved task is known for Muse Spark 1.1 only.

Which has the bigger context window, GLM 4.5V or Muse Spark 1.1?

Muse Spark 1.1, with 1.05M tokens against 66K.

How many benchmarks is the GLM 4.5V vs Muse Spark 1.1 comparison based on?

33 benchmarks have a result for both models as of October 22, 2026. GLM 4.5V's coding index rests on 0 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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