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GLM 5.3 Flash vs Muse Spark 1.1

Muse Spark 1.1 leads GLM 5.3 Flash on coding, 70.3 to 57.7 on the Vibe Coding Index, and GLM 5.3 Flash costs 8.5x less per output token ($0.50 vs $4.25 per million). Updated October 22, 2026; 76 benchmarks have a result for both.

Replace GLM 5.3 Flash Replace Muse Spark 1.1
GLM 5.3 FlashZ.ai
Coding
57.7
Overall
66.0
Output $/M
$0.50
40
Muse Spark 1.1Meta
Coding
70.3
Overall
67.0
Output $/M
$4.25
34
vs boards won of 76 shared, 2 tied

GLM 5.3 Flash 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 57.7 for GLM 5.3 Flash, though on 3 benchmarks against 6.

Pick GLM 5.3 Flash for output tokens 8.5x cheaper ($0.50 vs $4.25 per million) and a lower cost per solved task ($0.02 against $0.43).

Model AGLM 5.3 FlashZ.ai57.7/1006 independent benchmarks$0.02 per solved taskModel BMuse Spark 1.1Meta70.3/1003 independent benchmarks$0.43 per solved task
Shared results
76
GLM 5.3 Flash only
26
Muse Spark 1.1 only
28
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
GLM 5.3 Flash 57.7 from 6 benchmarks, Muse Spark 1.1 70.3 from 3 benchmarks.
Widest category
Agentic work, 10.9 points apart on average over 5 shared benchmarks.
Widest single gap
Vibe Code Bench (Vals AI): GLM 5.3 Flash 30.8% against Muse Spark 1.1 72.2%, 41.4 points apart on a 0 to 100 scale.
Output price
GLM 5.3 Flash $0.50 against Muse Spark 1.1 $4.25 per million output tokens, 8.5x 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
CategoryGLM 5.3 FlashBarsMuse Spark 1.1Ties
Coding861 tie
Intelligence11
Agentic work41
Reasoning64
Math21
Knowledge07
Web design62
General13121 tie
All shared boards40342 ties
CodingLike-for-likeSix of these boards feed the Vibe Coding Index86
Coding benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
LiveBench coding80.6%Not measuredOnly GLM 5.3 Flash measured
LMArena WebDev16071542GLM 5.3 Flash
AA Coding Index71.571.3GLM 5.3 Flash
LiveCodeBench (Vals AI)80.5%85.9%Muse Spark 1.1
SWE-bench Verified (Vals AI)92.0%82.0%GLM 5.3 Flash
Terminal-Bench 4 (Vals AI)37.4%Not measuredOnly GLM 5.3 Flash measured
Vibe Code Bench (Vals AI)30.8%72.2%Muse Spark 1.1
Code migration (Vals AI)20.5%31.1%Muse Spark 1.1
ProgramBench (Vals AI)0.0%0.0%Tie
IOI (Vals AI)52.5%Not measuredOnly GLM 5.3 Flash measured
Terminal-Bench 2.1 (Vals AI)62.9%69.3%Muse Spark 1.1
Vibe Code Bench 1-100 (Vals AI)16.0%Not measuredOnly GLM 5.3 Flash measured
SkillsBench (Vals AI)40.2%59.2%Muse Spark 1.1
CyberBench (Vals AI)67.9%Not measuredOnly GLM 5.3 Flash measured
SciCode51.6%58.8%Muse Spark 1.1
FrontierCode31.8%Not measuredOnly GLM 5.3 Flash measured
FrontierSWE18.1%Not measuredOnly GLM 5.3 Flash measured
ALE-Bench303.6Not measuredOnly GLM 5.3 Flash measured
LMArena Text: coding15071498GLM 5.3 Flash
LMArena Text: software and IT15001498GLM 5.3 Flash
LMArena WebDev: React16241532GLM 5.3 Flash
LMArena WebDev: HTML15771540GLM 5.3 Flash
LMArena WebDev: from an image15781540GLM 5.3 Flash
SWE Atlas: Codebase QnANot measured42.2%Only Muse Spark 1.1 measured
SWE Atlas: Test WritingNot measured41.5%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 index11
Intelligence benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
AA Intelligence Index41.833.7GLM 5.3 Flash
Epoch Capabilities Index153.1154.1Muse Spark 1.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index41
Agentic work benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
AA Agentic Index50.925.8GLM 5.3 Flash
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 measured1145Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1134Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured1021Only Muse Spark 1.1 measured
LiveBench research70.1%Not measuredOnly GLM 5.3 Flash measured
LiveBench browser84.0%Not measuredOnly GLM 5.3 Flash measured
LiveBench long agentic28.4%Not measuredOnly GLM 5.3 Flash measured
SREBench (Vals AI)0.8%Not measuredOnly GLM 5.3 Flash measured
Finance Agent (Vals AI)57.9%57.2%GLM 5.3 Flash
Tax Agent Bench (Vals AI)31.6%Not measuredOnly GLM 5.3 Flash measured
Legal Research Bench (Vals AI)45.2%38.0%GLM 5.3 Flash
Harvey's Legal Agent Benchmark (Vals AI)10.4%Not measuredOnly GLM 5.3 Flash measured
Excel Modeling Benchmark (Vals AI)55.9%56.4%Muse Spark 1.1
Terminal-Bench-Science (Vals AI)2.9%Not measuredOnly GLM 5.3 Flash measured
Time Horizon Index (Vals AI)Not measured1.7%Only Muse Spark 1.1 measured
APEX-Agents52.8%31.8%GLM 5.3 Flash
Vending-Bench 2Not measured$6,520Only Muse Spark 1.1 measured
MCP AtlasNot measured88.1%Only Muse Spark 1.1 measured
Neither model has a result on the other 18 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index64
Reasoning benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
GPQA Diamond86.4%91.2%Muse Spark 1.1
LiveBench reasoning77.6%Not measuredOnly GLM 5.3 Flash measured
MMMU Pro (Vals AI)86.0%86.6%Muse Spark 1.1
GPQA Diamond (Artificial Analysis run)91.2%89.8%GLM 5.3 Flash
Humanity's Last Exam (Artificial Analysis run)39.9%46.2%Muse Spark 1.1
GPQA Diamond (Epoch AI run)90.2%Not measuredOnly GLM 5.3 Flash measured
ARC-AGI91.0%Not measuredOnly GLM 5.3 Flash measured
ARC-AGI-265.8%Not measuredOnly GLM 5.3 Flash measured
Chess puzzles21.0%34.0%Muse Spark 1.1
Mystery game puzzles8.0%Not measuredOnly GLM 5.3 Flash measured
LMArena Text: hard prompts14901485GLM 5.3 Flash
LMArena Text: expert15111478GLM 5.3 Flash
LMArena Text: hard prompts in English14881480GLM 5.3 Flash
LMArena Vision: diagrams13171305GLM 5.3 Flash
LMArena Vision: homework13181287GLM 5.3 Flash
Neither model has a result on the other 8 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index21
Math benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
OTIS Mock AIME93.9%Not measuredOnly GLM 5.3 Flash measured
FrontierMath, tiers 1 to 355.8%Not measuredOnly GLM 5.3 Flash measured
FrontierMath, tier 417.1%Not measuredOnly GLM 5.3 Flash measured
ProofBench21.0%39.0%Muse Spark 1.1
LMArena Text: math15031482GLM 5.3 Flash
LMArena Text: mathematical work14971487GLM 5.3 Flash
MathArenaNot measured42.5%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 index07
Knowledge benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
MMLU Pro86.1%88.7%Muse Spark 1.1
LegalBench (Vals AI)83.9%85.0%Muse Spark 1.1
CorpFin (Vals AI)Not measured71.3%Only Muse Spark 1.1 measured
TaxEval (Vals AI)75.6%79.7%Muse Spark 1.1
MortgageTax (Vals AI)Not measured66.1%Only Muse Spark 1.1 measured
SimpleQA VerifiedNot measured57.8%Only Muse Spark 1.1 measured
LMArena Text: science14841484Muse Spark 1.1
LMArena Text: medicine and healthcare14751479Muse Spark 1.1
LMArena Text: legal and government14731481Muse Spark 1.1
LMArena Text: business and finance14601470Muse Spark 1.1
PRBench FinanceNot measured55.0%Only Muse Spark 1.1 measured
PRBench LegalNot measured57.0%Only Muse Spark 1.1 measured
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index62
Web design benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
Design Arena: websites12711270GLM 5.3 Flash
Design Arena: UI components13141287GLM 5.3 Flash
Design Arena: game dev12771269GLM 5.3 Flash
Design Arena: data viz12621267Muse Spark 1.1
Design Arena: 3D13151259GLM 5.3 Flash
Design Arena: all code categories12811276GLM 5.3 Flash
Design Arena: SVG12841234GLM 5.3 Flash
Design Arena: ASCII art12671269Muse Spark 1.1
LiveBench design77.2%Not measuredOnly GLM 5.3 Flash measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index1312
General benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse Spark 1.1Leader
Vals Index50.9%Not measuredOnly GLM 5.3 Flash measured
LiveBench data analysis76.4%Not measuredOnly GLM 5.3 Flash measured
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)88.9%88.9%GLM 5.3 Flash
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
Long context reasoning (AA-LCR)80.0%77.7%GLM 5.3 Flash
DTBenchNot measured94.4%Only Muse Spark 1.1 measured
LMCANot measured49.9%Only Muse Spark 1.1 measured
Surface Evolver Bench52.5%52.5%Tie
LMArena Text14711478Muse Spark 1.1
LMArena Text: instruction following14781457GLM 5.3 Flash
LMArena Text: creative writing14411435GLM 5.3 Flash
LMArena Vision12941293GLM 5.3 Flash
LMArena Text: English14741478Muse Spark 1.1
LMArena Text: non-English14621471Muse Spark 1.1
LMArena Text: Chinese15311515GLM 5.3 Flash
LMArena Text: German14621469Muse Spark 1.1
LMArena Text: Japanese14441450Muse Spark 1.1
LMArena Text: Korean14361459Muse Spark 1.1
LMArena Text: French14911492Muse Spark 1.1
LMArena Text: Spanish14751464GLM 5.3 Flash
LMArena Text: Russian14651482Muse Spark 1.1
LMArena Text: Polish14501499Muse Spark 1.1
LMArena Text: multi-turn14691484Muse Spark 1.1
LMArena Text: longer queries14811462GLM 5.3 Flash
LMArena Text: writing and language14551448GLM 5.3 Flash
LMArena Text: entertainment and media14401438GLM 5.3 Flash
LMArena Vision: English12951292GLM 5.3 Flash
LMArena Vision: Chinese13631348GLM 5.3 Flash
LMArena Vision: reading text12991301Muse Spark 1.1
LMArena Vision: humor12791288Muse Spark 1.1
LMArena Vision: creative writing12701253GLM 5.3 Flash
LMArena DocumentNot measured1465Only Muse Spark 1.1 measured
MultiChallengeNot measured75.3%Only Muse Spark 1.1 measured
EQ-Bench 4Not measured1260Only Muse Spark 1.1 measured
Neither model has a result on the other 12 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 5.3 Flash and Muse Spark 1.1
BenchmarkGLM 5.3 FlashMuse 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 5.3 Flash$0.0004Fits in one request
Muse Spark 1.1$0.0034Fits in one request

GLM 5.3 Flash costs less

Repository review

50K input + 3K output tokens

GLM 5.3 Flash$0.0090Fits in one request
Muse Spark 1.1$0.075Fits in one request

GLM 5.3 Flash costs less

Agent loop

200K input + 10K output tokens

GLM 5.3 Flash$0.035Fits in one request
Muse Spark 1.1$0.292Fits in one request

GLM 5.3 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 GLM 5.3 Flash and Muse Spark 1.1
SpecificationZ.ai GLM 5.3 FlashMeta Muse Spark 1.1
MakerZ.aiMeta
WeightsOpen weightsNo public weights listed
ReleasedAugust 26, 2026July 16, 2026
Context window1.05M1.05M
Input $/Mtok$0.15$1.25
Output $/Mtok$0.50$4.25
Coding index57.770.3
Independent measurements behind it63
Cost per solved task$0.02$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.3 Flash 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 57.7 for GLM 5.3 Flash, though on 3 benchmarks against 6. Pick GLM 5.3 Flash for output tokens 8.5x cheaper ($0.50 vs $4.25 per million) and a lower cost per solved task ($0.02 against $0.43).

Which is cheaper, GLM 5.3 Flash or Muse Spark 1.1?

GLM 5.3 Flash costs $0.15 per million input tokens and $0.50 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GLM 5.3 Flash costs $0.02 and Muse Spark 1.1 $0.43.

Which has the bigger context window, GLM 5.3 Flash or Muse Spark 1.1?

Neither: both take 1.05M tokens.

How many benchmarks is the GLM 5.3 Flash vs Muse Spark 1.1 comparison based on?

76 benchmarks have a result for both models as of October 22, 2026. GLM 5.3 Flash's coding index rests on 6 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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<p style="font:13px/1.4 sans-serif;margin:6px 0 0">Source: <a href="https://llmbenchmark.ai/compare/glm-5-3-flash-vs-meta-muse-spark-1-1">LLMBenchmark.ai, GLM 5.3 Flash vs Muse Spark 1.1</a></p>