LLMBenchmark.ai

Enter opens the highlighted result. Esc closes.

GLM 4.7 vs Muse Spark 1.1

Updated October 21, 2026. 61 benchmarks have a result for both. Coding is ranked on the Vibe Coding Index; every other board is shown as published.

Replace GLM 4.7 Replace Muse Spark 1.1
GLM 4.7Z.ai
Coding
33.6
Overall
22.2
Output $/M
$1.98
0
Muse Spark 1.1Meta
Coding
48.9
Overall
33.7
Output $/M
$4.25
61
vs boards won of 61 shared

Decision reading

Pick Muse Spark 1.1 for coding: it scores 48.9 on the Vibe Coding Index against 33.6 for GLM 4.7.

Pick GLM 4.7 when output tokens cost 2.1x less, or when a solved task costs $0.29 against $0.43.

Model AGLM 4.7Z.ai33.6/1001 independent benchmark$0.29 per solved taskModel BMuse Spark 1.1Meta48.9/1001 independent benchmark$0.43 per solved task
Shared results
61
GLM 4.7 only
19
Muse Spark 1.1 only
35
Like-for-like categories
8 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
GLM 4.7 33.6 from 1 benchmark, Muse Spark 1.1 48.9 from 1 benchmark.
Widest category
Math, 18.4 points apart on average over 3 shared benchmarks.
Widest single gap
ProofBench: GLM 4.7 6.0% against Muse Spark 1.1 39.0%, 33.0 points apart on a 0 to 100 scale.
Output price
GLM 4.7 $1.98 against Muse Spark 1.1 $4.25 per million output tokens, 2.1x apart.
Context window
GLM 4.7 takes 205K 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 4.7BarsMuse Spark 1.1Ties
Coding08
Intelligence02
Agentic work05
Reasoning07
Math03
Knowledge09
Web design08
General019
All shared boards061
CodingLike-for-likeFour of these boards feed the Vibe Coding Index08
Coding benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
LMArena WebDev14351542Muse Spark 1.1
AA Coding Index45.371.3Muse Spark 1.1
LiveCodeBench (Vals AI)82.2%85.9%Muse Spark 1.1
SWE-bench Verified (Vals AI)69.4%82.0%Muse Spark 1.1
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)89.4%Not measuredOnly GLM 4.7 measured
SciCodeNot measured58.8%Only Muse Spark 1.1 measured
Terminal-Bench Hard (Artificial Analysis run)31.8%Not measuredOnly GLM 4.7 measured
Terminal-Bench33.4%Not measuredOnly GLM 4.7 measured
ALE-Bench399.5Not measuredOnly GLM 4.7 measured
LMArena Text: coding14541498Muse Spark 1.1
LMArena Text: software and IT14531498Muse Spark 1.1
LMArena WebDev: React14201532Muse Spark 1.1
LMArena WebDev: HTML14471540Muse Spark 1.1
LMArena WebDev: from an imageNot measured1540Only Muse Spark 1.1 measured
Neither model has a result on the other 19 boards here
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index02
Intelligence benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
AA Intelligence Index22.233.7Muse Spark 1.1
Epoch Capabilities Index143.6154.1Muse Spark 1.1
Agentic workLike-for-likePublic boards, shown as published, kept out of the index05
Agentic work benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse 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 apps10501199Muse Spark 1.1
Design Arena: agents building mobile apps11051177Muse Spark 1.1
Design Arena: agents building Android apps11181184Muse Spark 1.1
Design Arena: agents building Godot games10581103Muse Spark 1.1
Design Arena: agents building gamesNot measured1183Only Muse Spark 1.1 measured
Design Arena: HTML slidesNot measured1194Only Muse Spark 1.1 measured
Design Arena: PowerPoint slidesNot measured1156Only Muse Spark 1.1 measured
Design Arena: spreadsheetsNot measured974Only 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 Telecom95.9%Not measuredOnly GLM 4.7 measured
APEX-AgentsNot measured31.8%Only Muse Spark 1.1 measured
Vending-Bench 2$2,377$6,520Muse 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 index07
Reasoning benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
GPQA Diamond80.0%91.2%Muse Spark 1.1
MMMU Pro (Vals AI)Not measured86.6%Only Muse Spark 1.1 measured
GPQA Diamond (Artificial Analysis run)85.9%89.8%Muse Spark 1.1
Humanity's Last Exam (Artificial Analysis run)27.4%46.2%Muse Spark 1.1
GPQA Diamond (Epoch AI run)83.3%Not measuredOnly GLM 4.7 measured
SimpleBench47.7%Not measuredOnly GLM 4.7 measured
Chess puzzles21.0%34.0%Muse Spark 1.1
LMArena Text: hard prompts14431485Muse Spark 1.1
LMArena Text: expert14241478Muse Spark 1.1
LMArena Text: hard prompts in English14521480Muse Spark 1.1
LMArena Vision: diagramsNot measured1305Only Muse Spark 1.1 measured
LMArena Vision: homeworkNot measured1287Only Muse Spark 1.1 measured
Neither model has a result on the other 9 boards here
MathLike-for-likePublic boards, shown as published, kept out of the index03
Math benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
AIME93.3%Not measuredOnly GLM 4.7 measured
MGSM (Vals AI)88.2%Not measuredOnly GLM 4.7 measured
AA Math Index95.0Not measuredOnly GLM 4.7 measured
AIME 2025 (Artificial Analysis run)95.0%Not measuredOnly GLM 4.7 measured
OTIS Mock AIME83.3%Not measuredOnly GLM 4.7 measured
ProofBench6.0%39.0%Muse Spark 1.1
LMArena Text: math14241482Muse Spark 1.1
LMArena Text: mathematical work14111487Muse Spark 1.1
Neither model has a result on the other 5 boards here
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index09
Knowledge benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
MMLU Pro82.7%88.7%Muse Spark 1.1
LegalBench (Vals AI)83.4%85.0%Muse Spark 1.1
CaseLaw (Vals AI)54.9%Not measuredOnly GLM 4.7 measured
CorpFin (Vals AI)46.4%71.3%Muse Spark 1.1
TaxEval (Vals AI)68.8%79.7%Muse Spark 1.1
MortgageTax (Vals AI)Not measured66.1%Only Muse Spark 1.1 measured
MedQA (Vals AI)93.7%Not measuredOnly GLM 4.7 measured
MedCode (Vals AI)32.8%Not measuredOnly GLM 4.7 measured
MMLU Pro (Artificial Analysis run)85.6%Not measuredOnly GLM 4.7 measured
SimpleQA Verified32.2%57.8%Muse Spark 1.1
LMArena Text: science14571484Muse Spark 1.1
LMArena Text: medicine and healthcare14691479Muse Spark 1.1
LMArena Text: legal and government14441481Muse Spark 1.1
LMArena Text: business and finance14291470Muse Spark 1.1
Neither model has a result on the other 3 boards here
Web designLike-for-likePublic boards, shown as published, kept out of the index08
Web design benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse Spark 1.1Leader
Design Arena: websites12261270Muse Spark 1.1
Design Arena: UI components11991290Muse Spark 1.1
Design Arena: game dev11891269Muse Spark 1.1
Design Arena: data viz11951268Muse Spark 1.1
Design Arena: 3D11911260Muse Spark 1.1
Design Arena: all code categories12171276Muse Spark 1.1
Design Arena: SVG11421234Muse Spark 1.1
Design Arena: ASCII art11651270Muse Spark 1.1
Neither model has a result on the other 1 board here
GeneralLike-for-likePublic boards, shown as published, kept out of the index019
General benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse 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)68.6%88.9%Muse Spark 1.1
Vals Multimodal IndexNot measured66.7%Only Muse Spark 1.1 measured
IFBench67.9%Not measuredOnly GLM 4.7 measured
Long context reasoning (AA-LCR)71.0%77.7%Muse Spark 1.1
DTBenchNot measured94.4%Only Muse Spark 1.1 measured
LMCANot measured49.9%Only Muse Spark 1.1 measured
CL-bench15.9%Not measuredOnly GLM 4.7 measured
Surface Evolver BenchNot measured52.5%Only Muse Spark 1.1 measured
CL-bench Life10.9%Not measuredOnly GLM 4.7 measured
LMArena Text14351478Muse Spark 1.1
LMArena Text: instruction following14121457Muse Spark 1.1
LMArena Text: creative writing14011435Muse Spark 1.1
LMArena VisionNot measured1293Only Muse Spark 1.1 measured
LMArena Text: English14531478Muse Spark 1.1
LMArena Text: non-English14171471Muse Spark 1.1
LMArena Text: Chinese14951515Muse Spark 1.1
LMArena Text: German14261469Muse Spark 1.1
LMArena Text: Japanese14391450Muse Spark 1.1
LMArena Text: Korean13991459Muse Spark 1.1
LMArena Text: French14321492Muse Spark 1.1
LMArena Text: Spanish14341464Muse Spark 1.1
LMArena Text: Russian14231482Muse Spark 1.1
LMArena Text: Polish14351499Muse Spark 1.1
LMArena Text: multi-turn14461484Muse Spark 1.1
LMArena Text: longer queries14321462Muse Spark 1.1
LMArena Text: writing and language14111448Muse Spark 1.1
LMArena Text: entertainment and media14001438Muse Spark 1.1
LMArena Vision: EnglishNot measured1292Only Muse Spark 1.1 measured
LMArena Vision: ChineseNot measured1348Only Muse Spark 1.1 measured
LMArena Vision: reading textNot measured1301Only Muse Spark 1.1 measured
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 11 boards here
Image generationNot comparablePublic boards, shown as published, kept out of the index0 boards, none shared
Image generation benchmarks for GLM 4.7 and Muse Spark 1.1
BenchmarkGLM 4.7Muse 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 4.7$0.0015Fits in one request
Muse Spark 1.1$0.0034Fits in one request

GLM 4.7 costs less

Repository review

50K input + 3K output tokens

GLM 4.7$0.033Fits in one request
Muse Spark 1.1$0.075Fits in one request

GLM 4.7 costs less

Agent loop

200K input + 10K output tokens

GLM 4.7$0.128Exceeds the context window
Muse Spark 1.1$0.292Fits in one request

GLM 4.7 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 4.7 and Muse Spark 1.1
SpecificationZ.ai GLM 4.7Meta Muse Spark 1.1
MakerZ.aiMeta
WeightsOpen weightsNo public weights listed
ReleasedDecember 22, 2025July 16, 2026
Context window205K1.05M
Input $/Mtok$0.54$1.25
Output $/Mtok$1.98$4.25
Coding index33.648.9
Independent measurements behind it11
Cost per solved task$0.29$0.43
SourceOpenRouter listingOpenRouter listing

Questions

Is GLM 4.7 better than Muse Spark 1.1 for coding?

Pick Muse Spark 1.1 for coding: it scores 48.9 on the Vibe Coding Index against 33.6 for GLM 4.7. Pick GLM 4.7 when output tokens cost 2.1x less, or when a solved task costs $0.29 against $0.43.

Which is cheaper, GLM 4.7 or Muse Spark 1.1?

GLM 4.7 costs $0.54 per million input tokens and $1.98 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GLM 4.7 costs $0.29 and Muse Spark 1.1 $0.43.

Which has the bigger context window, GLM 4.7 or Muse Spark 1.1?

Muse Spark 1.1, with 1.05M tokens against 205K.

How many benchmarks is the GLM 4.7 vs Muse Spark 1.1 comparison based on?

61 benchmarks have a result for both models as of October 21, 2026. GLM 4.7's coding index rests on 1 independent benchmark and Muse Spark 1.1's on 1. Where only one model has a result, the page says so instead of naming a winner.

Compare next