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GLM 5.2 vs Muse Spark 1.3

GLM 5.2 leads Muse Spark 1.3 on coding, 61.1 to 57.4 on the Vibe Coding Index, at about the same output price ($4.40 vs $4.25 per million). Updated October 22, 2026; 69 benchmarks have a result for both.

Replace GLM 5.2 Replace Muse Spark 1.3
GLM 5.2Z.ai
Coding
61.1
Overall
62.5
Output $/M
$4.40
2
Muse Spark 1.3Meta
Coding
57.4
Overall
68.6
Output $/M
$4.25
66
vs boards won of 69 shared, 1 tied

GLM 5.2 or Muse Spark 1.3: which to pick

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 57.4 for Muse Spark 1.3.

Pick Muse Spark 1.3 for output tokens 1.0x cheaper ($4.25 vs $4.40 per million) and work measured by LMArena WebDev or AA Coding Index, where it leads.

Model AGLM 5.2Z.ai61.1/1004 independent benchmarks$0.86 per solved taskModel BMuse Spark 1.3Meta57.4/1004 independent benchmarksNo cost per solved task
Shared results
69
GLM 5.2 only
29
Muse Spark 1.3 only
23
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 5.2 61.1 from 4 benchmarks, Muse Spark 1.3 57.4 from 4 benchmarks.
Widest category
Math, 11.8 points apart on average over 6 shared benchmarks.
Widest single gap
ProofBench: GLM 5.2 35.0% against Muse Spark 1.3 58.0%, 23.0 points apart on a 0 to 100 scale.
Output price
GLM 5.2 $4.40 against Muse Spark 1.3 $4.25 per million output tokens, 1.0x 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 5.2BarsMuse Spark 1.3Ties
Coding1101 tie
Intelligence02
Agentic work010
Reasoning07
Math06
Knowledge04
Web design08
General119
All shared boards2661 tie
CodingLike-for-likeSix of these boards feed the Vibe Coding Index110
Coding benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
LiveBench codingNot measured90.2%Only Muse Spark 1.3 measured
LMArena WebDev16041659Muse Spark 1.3
AA Coding Index68.875.8Muse Spark 1.3
LiveCodeBench (Vals AI)69.5%Not measuredOnly GLM 5.2 measured
SWE-bench Verified (Vals AI)82.8%Not measuredOnly GLM 5.2 measured
Terminal-Bench 4 (Vals AI)Not measured10.6%Only Muse Spark 1.3 measured
Vibe Code Bench (Vals AI)64.0%82.9%Muse Spark 1.3
Code migration (Vals AI)37.9%27.6%GLM 5.2
ProgramBench (Vals AI)0.5%0.5%Tie
IOI (Vals AI)Not measured43.9%Only Muse Spark 1.3 measured
Terminal-Bench 2.1 (Vals AI)67.8%72.3%Muse Spark 1.3
SkillsBench (Vals AI)45.1%Not measuredOnly GLM 5.2 measured
CyberBench (Vals AI)Not measured69.4%Only Muse Spark 1.3 measured
SciCode51.2%59.7%Muse Spark 1.3
Terminal-Bench Hard (Artificial Analysis run)50.8%Not measuredOnly GLM 5.2 measured
FrontierCode24.5%Not measuredOnly GLM 5.2 measured
FrontierSWENot measured25.8%Only Muse Spark 1.3 measured
WeirdML70.1%Not measuredOnly GLM 5.2 measured
ALE-Bench1047.01688.3Muse Spark 1.3
LMArena Text: coding14871510Muse Spark 1.3
LMArena Text: software and IT14861511Muse Spark 1.3
LMArena WebDev: React16171672Muse Spark 1.3
LMArena WebDev: HTML15651653Muse Spark 1.3
LMArena WebDev: from an imageNot measured1640Only Muse Spark 1.3 measured
Neither model has a result on the other 15 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
AA Intelligence Index33.748.1Muse Spark 1.3
Epoch Capabilities Index151.9157.2Muse Spark 1.3
Agentic workLike-for-likePublic boards, shown as published, kept out of the index010
Agentic work benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
AA Agentic Index38.455.5Muse Spark 1.3
Design Arena: agents building web apps12221297Muse Spark 1.3
Design Arena: agents building full-stack apps12411295Muse Spark 1.3
Design Arena: agents building mobile apps11591218Muse Spark 1.3
Design Arena: agents building Android apps1178Not measuredOnly GLM 5.2 measured
Design Arena: agents building Godot games11421241Muse Spark 1.3
Design Arena: agents building games1206Not measuredOnly GLM 5.2 measured
Design Arena: HTML slides1125Not measuredOnly GLM 5.2 measured
Design Arena: PowerPoint slides11701219Muse Spark 1.3
Design Arena: spreadsheetsNot measured1062Only Muse Spark 1.3 measured
LiveBench researchNot measured68.6%Only Muse Spark 1.3 measured
LiveBench browserNot measured80.0%Only Muse Spark 1.3 measured
LiveBench long agenticNot measured40.4%Only Muse Spark 1.3 measured
SREBench (Vals AI)0.0%Not measuredOnly GLM 5.2 measured
Finance Agent (Vals AI)49.7%58.9%Muse Spark 1.3
Tax Agent Bench (Vals AI)Not measured36.0%Only Muse Spark 1.3 measured
Legal Research Bench (Vals AI)31.3%40.9%Muse Spark 1.3
Excel Modeling Benchmark (Vals AI)61.5%62.7%Muse Spark 1.3
Terminal-Bench-Science (Vals AI)Not measured4.3%Only Muse Spark 1.3 measured
τ²-Bench Telecom99.1%Not measuredOnly GLM 5.2 measured
APEX-Agents45.2%58.6%Muse Spark 1.3
PostTrainBench31.7%Not measuredOnly GLM 5.2 measured
Vending-Bench 2$8,314Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 18 boards here
ReasoningLike-for-likePublic boards, shown as published, kept out of the index07
Reasoning benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
GPQA Diamond85.6%Not measuredOnly GLM 5.2 measured
LiveBench reasoningNot measured89.7%Only Muse Spark 1.3 measured
GPQA Diamond (Artificial Analysis run)89.5%94.1%Muse Spark 1.3
Humanity's Last Exam (Artificial Analysis run)41.1%48.7%Muse Spark 1.3
GPQA Diamond (Epoch AI run)91.9%Not measuredOnly GLM 5.2 measured
ARC-AGI77.0%Not measuredOnly GLM 5.2 measured
ARC-AGI-222.8%Not measuredOnly GLM 5.2 measured
SimpleBench58.8%Not measuredOnly GLM 5.2 measured
Chess puzzles22.0%37.0%Muse Spark 1.3
Mystery game puzzles19.0%25.0%Muse Spark 1.3
EBR-bench9.5%Not measuredOnly GLM 5.2 measured
LMArena Text: hard prompts14811503Muse Spark 1.3
LMArena Text: expert14871519Muse Spark 1.3
LMArena Text: hard prompts in English14811500Muse Spark 1.3
LMArena Vision: diagramsNot measured1330Only Muse Spark 1.3 measured
LMArena Vision: homeworkNot measured1296Only Muse Spark 1.3 measured
Kagi LLM Benchmark62.6%Not measuredOnly GLM 5.2 measured
Neither model has a result on the other 5 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index06
Math benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
OTIS Mock AIME86.4%99.2%Muse Spark 1.3
FrontierMath, tiers 1 to 359.2%74.4%Muse Spark 1.3
FrontierMath, tier 429.3%46.3%Muse Spark 1.3
ProofBench35.0%58.0%Muse Spark 1.3
LMArena Text: math14831497Muse Spark 1.3
LMArena Text: mathematical work14891491Muse Spark 1.3
Neither model has a result on the other 7 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index04
Knowledge benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
MMLU Pro86.7%Not measuredOnly GLM 5.2 measured
LegalBench (Vals AI)84.1%Not measuredOnly GLM 5.2 measured
CorpFin (Vals AI)66.1%Not measuredOnly GLM 5.2 measured
TaxEval (Vals AI)73.3%Not measuredOnly GLM 5.2 measured
MedCode (Vals AI)40.8%Not measuredOnly GLM 5.2 measured
SimpleQA Verified34.2%Not measuredOnly GLM 5.2 measured
LMArena Text: science14891507Muse Spark 1.3
LMArena Text: medicine and healthcare14751493Muse Spark 1.3
LMArena Text: legal and government14861499Muse Spark 1.3
LMArena Text: business and finance14511490Muse Spark 1.3
Neither model has a result on the other 8 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
Design Arena: websites12851356Muse Spark 1.3
Design Arena: UI components12941349Muse Spark 1.3
Design Arena: game dev12681328Muse Spark 1.3
Design Arena: data viz12851343Muse Spark 1.3
Design Arena: 3D12871358Muse Spark 1.3
Design Arena: all code categories12871352Muse Spark 1.3
Design Arena: SVG12131301Muse Spark 1.3
Design Arena: ASCII art11911278Muse Spark 1.3
LiveBench designNot measured74.8%Only Muse Spark 1.3 measured
GeneralLike-for-likePublic boards, shown as published, kept out of the index119
General benchmarks for GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
LiveBench data analysisNot measured79.6%Only Muse Spark 1.3 measured
MedScribe (Vals AI)83.5%Not measuredOnly GLM 5.2 measured
IFBench73.3%Not measuredOnly GLM 5.2 measured
Long context reasoning (AA-LCR)78.3%83.0%Muse Spark 1.3
DTBench93.6%96.5%Muse Spark 1.3
LMCA45.8%53.9%Muse Spark 1.3
Surface Evolver Bench55.6%Not measuredOnly GLM 5.2 measured
LMArena Text14701490Muse Spark 1.3
LMArena Text: instruction following14661479Muse Spark 1.3
LMArena Text: creative writing14631462GLM 5.2
LMArena VisionNot measured1308Only Muse Spark 1.3 measured
LMArena Text: English14751495Muse Spark 1.3
LMArena Text: non-English14591481Muse Spark 1.3
LMArena Text: Chinese15221532Muse Spark 1.3
LMArena Text: German14701513Muse Spark 1.3
LMArena Text: Japanese14501470Muse Spark 1.3
LMArena Text: Korean14401490Muse Spark 1.3
LMArena Text: French14791511Muse Spark 1.3
LMArena Text: Spanish14781496Muse Spark 1.3
LMArena Text: Russian14681491Muse Spark 1.3
LMArena Text: Polish14561490Muse Spark 1.3
LMArena Text: multi-turn14691487Muse Spark 1.3
LMArena Text: longer queries14801488Muse Spark 1.3
LMArena Text: writing and language14631470Muse Spark 1.3
LMArena Text: entertainment and media14501457Muse Spark 1.3
LMArena Vision: EnglishNot measured1298Only Muse Spark 1.3 measured
LMArena Vision: ChineseNot measured1384Only Muse Spark 1.3 measured
LMArena Vision: reading textNot measured1319Only Muse Spark 1.3 measured
LMArena Vision: humorNot measured1293Only Muse Spark 1.3 measured
LMArena Vision: creative writingNot measured1296Only Muse Spark 1.3 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 GLM 5.2 and Muse Spark 1.3
BenchmarkGLM 5.2Muse Spark 1.3Leader
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 5.2$0.0036Fits in one request
Muse Spark 1.3$0.0034Fits in one request

Muse Spark 1.3 costs less

Repository review

50K input + 3K output tokens

GLM 5.2$0.083Fits in one request
Muse Spark 1.3$0.075Fits in one request

Muse Spark 1.3 costs less

Agent loop

200K input + 10K output tokens

GLM 5.2$0.324Fits in one request
Muse Spark 1.3$0.292Fits in one request

Muse Spark 1.3 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 5.2 and Muse Spark 1.3
SpecificationZ.ai GLM 5.2Meta Muse Spark 1.3
MakerZ.aiMeta
WeightsOpen weightsNo public weights listed
ReleasedJune 16, 2026September 2, 2026
Context window1.05M1.05M
Input $/Mtok$1.40$1.25
Output $/Mtok$4.40$4.25
Coding index61.157.4
Independent measurements behind it44
Cost per solved task$0.86Not computable
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 5.2 better than Muse Spark 1.3 for coding?

Pick GLM 5.2 for coding: it scores 61.1 on the Vibe Coding Index against 57.4 for Muse Spark 1.3. Pick Muse Spark 1.3 for output tokens 1.0x cheaper ($4.25 vs $4.40 per million) and work measured by LMArena WebDev or AA Coding Index, where it leads.

Which is cheaper, GLM 5.2 or Muse Spark 1.3?

GLM 5.2 costs $1.40 per million input tokens and $4.40 per million output tokens; Muse Spark 1.3 costs $1.25 and $4.25. Cost per solved task is known for GLM 5.2 only.

Which has the bigger context window, GLM 5.2 or Muse Spark 1.3?

Neither: both take 1.05M tokens.

How many benchmarks is the GLM 5.2 vs Muse Spark 1.3 comparison based on?

69 benchmarks have a result for both models as of October 22, 2026. GLM 5.2's coding index rests on 4 independent benchmarks and Muse Spark 1.3's on 4. 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-5-2-vs-meta-muse-spark-1-3">LLMBenchmark.ai, GLM 5.2 vs Muse Spark 1.3</a></p>