GLM 5.3 vs Muse Spark 1.1
GLM 5.3 leads Muse Spark 1.1 on coding, 70.6 to 70.3 on the Vibe Coding Index, at about the same output price ($4.40 vs $4.25 per million). Updated October 22, 2026; 73 benchmarks have a result for both.
GLM 5.3 or Muse Spark 1.1: which to pick
GLM 5.3 and Muse Spark 1.1 are level for coding, 70.6 against 70.3 on the Vibe Coding Index, so price and context decide.
Pick Muse Spark 1.1 for output tokens 1.0x cheaper ($4.25 vs $4.40 per million) and work measured by LiveCodeBench (Vals AI) or SkillsBench (Vals AI), where it leads. Pick GLM 5.3 for a lower cost per solved task ($0.36 against $0.43) and work measured by LMArena WebDev or AA Coding Index, where it leads.
- Shared results
- 73
- GLM 5.3 only
- 27
- Muse Spark 1.1 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.
Coding
Vibe Coding Index, six public coding benchmarks
No call
Level: 70.6 against 70.3, inside 2 points.
6 and 3 benchmarks behind the scores
Intelligence
AA Intelligence Index
GLM 5.3
GLM 5.3 leads, 44.8 against 33.7.
Same board, both measured
Agentic work
AA Agentic Index
GLM 5.3
GLM 5.3 leads, 53.1 against 25.8.
Same board, both measured
Reasoning
GPQA Diamond
Muse Spark 1.1
Muse Spark 1.1 leads, 91.2% against 88.1%.
Same board, both measured
Knowledge
MMLU Pro
Muse Spark 1.1
Muse Spark 1.1 leads, 88.7% against 86.8%.
Same board, both measured
Web design
Design Arena: websites
GLM 5.3
GLM 5.3 leads, 1295 against 1270.
Same board, both measured
General
Vals Index
No call
Only GLM 5.3 has a Vals Index result, 59.7%.
Directional only
Long documents
Listed context window
No call
Both take 1.05M tokens.
Listed by OpenRouter
Everyday cost
1K input + 500 output tokens
Muse Spark 1.1
GLM 5.3 $0.0036, Muse Spark 1.1 $0.0034 per turn.
List prices
Cost per solved task
One SWE-bench Verified task, solved
GLM 5.3
GLM 5.3 $0.36, Muse Spark 1.1 $0.43.
Published attempt cost and pass rate
At a glance
- Coding index
- GLM 5.3 70.6 from 6 benchmarks, Muse Spark 1.1 70.3 from 3 benchmarks.
- Widest category
- Agentic work, 9.7 points apart on average over 9 shared benchmarks.
- Widest single gap
- AA Agentic Index: GLM 5.3 53.1 against Muse Spark 1.1 25.8, 27.3 points apart on a 0 to 100 scale.
- Output price
- GLM 5.3 $4.40 against Muse Spark 1.1 $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.
| Category | GLM 5.3 | Bars | Muse Spark 1.1 | Ties |
|---|---|---|---|---|
| Coding | 10 | 4 | ||
| Intelligence | 2 | 0 | ||
| Agentic work | 6 | 3 | ||
| Reasoning | 5 | 2 | ||
| Math | 3 | 0 | ||
| Knowledge | 2 | 6 | ||
| Web design | 6 | 2 | ||
| General | 14 | 8 | ||
| All shared boards | 48 | 25 |
CodingLike-for-likeSix of these boards feed the Vibe Coding Index104
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| LiveBench coding | 82.8% | Not measured | Only GLM 5.3 measured |
| LMArena WebDev | 1621 | 1542 | GLM 5.3 |
| AA Coding Index | 74.8 | 71.3 | GLM 5.3 |
| LiveCodeBench (Vals AI) | 80.5% | 85.9% | Muse Spark 1.1 |
| SWE-bench Verified (Vals AI) | 95.4% | 82.0% | GLM 5.3 |
| Terminal-Bench 4 (Vals AI) | 38.9% | Not measured | Only GLM 5.3 measured |
| Vibe Code Bench (Vals AI) | 78.1% | 72.2% | GLM 5.3 |
| Code migration (Vals AI) | 44.2% | 31.1% | GLM 5.3 |
| ProgramBench (Vals AI) | 1.5% | 0.0% | GLM 5.3 |
| IOI (Vals AI) | 68.4% | Not measured | Only GLM 5.3 measured |
| Terminal-Bench 2.1 (Vals AI) | 71.5% | 69.3% | GLM 5.3 |
| Vibe Code Bench 1-100 (Vals AI) | 20.0% | Not measured | Only GLM 5.3 measured |
| SkillsBench (Vals AI) | 47.5% | 59.2% | Muse Spark 1.1 |
| CyberBench (Vals AI) | 72.1% | Not measured | Only GLM 5.3 measured |
| SciCode | 59.0% | 58.8% | GLM 5.3 |
| FrontierCode | 40.1% | Not measured | Only GLM 5.3 measured |
| FrontierSWE | 30.2% | Not measured | Only GLM 5.3 measured |
| WeirdML | 75.4% | Not measured | Only GLM 5.3 measured |
| ALE-Bench | 1317.4 | Not measured | Only GLM 5.3 measured |
| LMArena Text: coding | 1497 | 1498 | Muse Spark 1.1 |
| LMArena Text: software and IT | 1493 | 1498 | Muse Spark 1.1 |
| LMArena WebDev: React | 1641 | 1532 | GLM 5.3 |
| LMArena WebDev: HTML | 1595 | 1540 | GLM 5.3 |
| LMArena WebDev: from an image | Not measured | 1540 | Only Muse Spark 1.1 measured |
| Neither model has a result on the other 15 boards here | |||
IntelligenceLike-for-likePublic boards, shown as published, kept out of the index20
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| AA Intelligence Index | 44.8 | 33.7 | GLM 5.3 |
| Epoch Capabilities Index | 156.0 | 154.1 | GLM 5.3 |
Agentic workLike-for-likePublic boards, shown as published, kept out of the index63
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| AA Agentic Index | 53.1 | 25.8 | GLM 5.3 |
| Design Arena: agents building web apps | Not measured | 1207 | Only Muse Spark 1.1 measured |
| Design Arena: agents building full-stack apps | Not measured | 1199 | Only Muse Spark 1.1 measured |
| Design Arena: agents building mobile apps | 1194 | 1175 | GLM 5.3 |
| Design Arena: agents building Android apps | Not measured | 1178 | Only Muse Spark 1.1 measured |
| Design Arena: agents building Godot games | Not measured | 1103 | Only Muse Spark 1.1 measured |
| Design Arena: agents building games | Not measured | 1183 | Only Muse Spark 1.1 measured |
| Design Arena: HTML slides | 1189 | 1195 | Muse Spark 1.1 |
| Design Arena: PowerPoint slides | 1230 | 1155 | GLM 5.3 |
| Design Arena: spreadsheets | Not measured | 1042 | Only Muse Spark 1.1 measured |
| LiveBench research | 73.2% | Not measured | Only GLM 5.3 measured |
| LiveBench browser | 0.0% | Not measured | Only GLM 5.3 measured |
| LiveBench long agentic | 35.9% | Not measured | Only GLM 5.3 measured |
| SREBench (Vals AI) | 9.2% | Not measured | Only GLM 5.3 measured |
| Finance Agent (Vals AI) | 55.8% | 57.2% | Muse Spark 1.1 |
| Tax Agent Bench (Vals AI) | 39.7% | Not measured | Only GLM 5.3 measured |
| Legal Research Bench (Vals AI) | 49.0% | 38.0% | GLM 5.3 |
| Harvey's Legal Agent Benchmark (Vals AI) | 14.6% | Not measured | Only GLM 5.3 measured |
| Excel Modeling Benchmark (Vals AI) | 56.3% | 56.4% | Muse Spark 1.1 |
| Terminal-Bench-Science (Vals AI) | 5.7% | Not measured | Only GLM 5.3 measured |
| Time Horizon Index (Vals AI) | Not measured | 1.7% | Only Muse Spark 1.1 measured |
| APEX-Agents | 56.6% | 31.8% | GLM 5.3 |
| Vending-Bench 2 | $8,164 | $6,520 | GLM 5.3 |
| Neither model has a result on the other 18 boards here | |||
ReasoningLike-for-likePublic boards, shown as published, kept out of the index52
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| GPQA Diamond | 88.1% | 91.2% | Muse Spark 1.1 |
| LiveBench reasoning | 85.8% | Not measured | Only GLM 5.3 measured |
| MysteryMechanism (Vals AI) | 23.0% | Not measured | Only GLM 5.3 measured |
| MMMU Pro (Vals AI) | Not measured | 86.6% | Only Muse Spark 1.1 measured |
| GPQA Diamond (Artificial Analysis run) | 91.7% | 89.8% | GLM 5.3 |
| Humanity's Last Exam (Artificial Analysis run) | 42.3% | 46.2% | Muse Spark 1.1 |
| GPQA Diamond (Epoch AI run) | 90.9% | Not measured | Only GLM 5.3 measured |
| Chess puzzles | 37.0% | 34.0% | GLM 5.3 |
| Mystery game puzzles | 33.0% | Not measured | Only GLM 5.3 measured |
| LMArena Text: hard prompts | 1490 | 1485 | GLM 5.3 |
| LMArena Text: expert | 1514 | 1478 | GLM 5.3 |
| LMArena Text: hard prompts in English | 1496 | 1480 | GLM 5.3 |
| LMArena Vision: diagrams | Not measured | 1305 | Only Muse Spark 1.1 measured |
| LMArena Vision: homework | Not measured | 1287 | Only Muse Spark 1.1 measured |
| Neither model has a result on the other 8 boards here | |||
MathLike-for-likePublic boards, shown as published, kept out of the index30
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| OTIS Mock AIME | 91.1% | Not measured | Only GLM 5.3 measured |
| FrontierMath, tiers 1 to 3 | 68.8% | Not measured | Only GLM 5.3 measured |
| FrontierMath, tier 4 | 29.3% | Not measured | Only GLM 5.3 measured |
| ProofBench | 49.0% | 39.0% | GLM 5.3 |
| LMArena Text: math | 1495 | 1482 | GLM 5.3 |
| LMArena Text: mathematical work | 1497 | 1487 | GLM 5.3 |
| Neither model has a result on the other 7 boards here | |||
KnowledgeLike-for-likePublic boards, shown as published, kept out of the index26
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| MMLU Pro | 86.8% | 88.7% | Muse Spark 1.1 |
| LegalBench (Vals AI) | 84.8% | 85.0% | Muse Spark 1.1 |
| CorpFin (Vals AI) | Not measured | 71.3% | Only Muse Spark 1.1 measured |
| TaxEval (Vals AI) | 72.4% | 79.7% | Muse Spark 1.1 |
| MortgageTax (Vals AI) | Not measured | 66.1% | Only Muse Spark 1.1 measured |
| MedCode (Vals AI) | 42.9% | Not measured | Only GLM 5.3 measured |
| SimpleQA Verified | 41.0% | 57.8% | Muse Spark 1.1 |
| LMArena Text: science | 1498 | 1484 | GLM 5.3 |
| LMArena Text: medicine and healthcare | 1481 | 1479 | GLM 5.3 |
| LMArena Text: legal and government | 1473 | 1481 | Muse Spark 1.1 |
| LMArena Text: business and finance | 1459 | 1470 | Muse Spark 1.1 |
| Neither model has a result on the other 7 boards here | |||
Web designLike-for-likePublic boards, shown as published, kept out of the index62
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| Design Arena: websites | 1295 | 1270 | GLM 5.3 |
| Design Arena: UI components | 1314 | 1289 | GLM 5.3 |
| Design Arena: game dev | 1311 | 1269 | GLM 5.3 |
| Design Arena: data viz | 1260 | 1268 | Muse Spark 1.1 |
| Design Arena: 3D | 1332 | 1260 | GLM 5.3 |
| Design Arena: all code categories | 1304 | 1276 | GLM 5.3 |
| Design Arena: SVG | 1294 | 1235 | GLM 5.3 |
| Design Arena: ASCII art | 1208 | 1271 | Muse Spark 1.1 |
| LiveBench design | 77.3% | Not measured | Only GLM 5.3 measured |
GeneralLike-for-likePublic boards, shown as published, kept out of the index148
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| Vals Index | 59.7% | Not measured | Only GLM 5.3 measured |
| LiveBench data analysis | 70.2% | Not measured | Only GLM 5.3 measured |
| Public Benefits Bench (Vals AI) | 68.5% | 61.3% | GLM 5.3 |
| SAGE (Vals AI) | Not measured | 45.6% | Only Muse Spark 1.1 measured |
| MedScribe (Vals AI) | 88.8% | 88.9% | Muse Spark 1.1 |
| Vals Multimodal Index | Not measured | 66.7% | Only Muse Spark 1.1 measured |
| Long context reasoning (AA-LCR) | 79.7% | 77.7% | GLM 5.3 |
| DTBench | 87.7% | 94.4% | Muse Spark 1.1 |
| LMCA | 55.5% | 49.9% | GLM 5.3 |
| Surface Evolver Bench | Not measured | 52.5% | Only Muse Spark 1.1 measured |
| LMArena Text | 1474 | 1478 | Muse Spark 1.1 |
| LMArena Text: instruction following | 1479 | 1457 | GLM 5.3 |
| LMArena Text: creative writing | 1458 | 1435 | GLM 5.3 |
| LMArena Vision | Not measured | 1293 | Only Muse Spark 1.1 measured |
| LMArena Text: English | 1482 | 1478 | GLM 5.3 |
| LMArena Text: non-English | 1459 | 1471 | Muse Spark 1.1 |
| LMArena Text: Chinese | 1532 | 1515 | GLM 5.3 |
| LMArena Text: German | 1488 | 1469 | GLM 5.3 |
| LMArena Text: Japanese | 1460 | 1450 | GLM 5.3 |
| LMArena Text: Korean | 1460 | 1459 | GLM 5.3 |
| LMArena Text: French | 1503 | 1492 | GLM 5.3 |
| LMArena Text: Spanish | 1462 | 1464 | Muse Spark 1.1 |
| LMArena Text: Russian | 1469 | 1482 | Muse Spark 1.1 |
| LMArena Text: Polish | 1466 | 1499 | Muse Spark 1.1 |
| LMArena Text: multi-turn | 1472 | 1484 | Muse Spark 1.1 |
| LMArena Text: longer queries | 1483 | 1462 | GLM 5.3 |
| LMArena Text: writing and language | 1469 | 1448 | GLM 5.3 |
| LMArena Text: entertainment and media | 1447 | 1438 | GLM 5.3 |
| LMArena Vision: English | Not measured | 1292 | Only Muse Spark 1.1 measured |
| LMArena Vision: Chinese | Not measured | 1348 | Only Muse Spark 1.1 measured |
| LMArena Vision: reading text | Not measured | 1301 | Only Muse Spark 1.1 measured |
| LMArena Vision: humor | Not measured | 1288 | Only Muse Spark 1.1 measured |
| LMArena Vision: creative writing | Not measured | 1253 | Only Muse Spark 1.1 measured |
| LMArena Document | Not measured | 1465 | Only 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
| Benchmark | GLM 5.3 | Muse Spark 1.1 | Leader |
|---|---|---|---|
| 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 costs less
Repository review
50K input + 3K output tokens
Muse Spark 1.1 costs less
Agent loop
200K input + 10K output tokens
Muse Spark 1.1 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.
| Specification | Z.ai GLM 5.3 | Meta Muse Spark 1.1 |
|---|---|---|
| Maker | Z.ai | Meta |
| Weights | Open weights | No public weights listed |
| Released | August 18, 2026 | July 16, 2026 |
| Context window | 1.05M | 1.05M |
| Input $/Mtok | $1.40 | $1.25 |
| Output $/Mtok | $4.40 | $4.25 |
| Coding index | 70.6 | 70.3 |
| Independent measurements behind it | 6 | 3 |
| Cost per solved task | $0.36 | $0.43 |
| Source | OpenRouter listing | OpenRouter listing |
Questions
Is GLM 5.3 better than Muse Spark 1.1 for coding?
GLM 5.3 and Muse Spark 1.1 are level for coding, 70.6 against 70.3 on the Vibe Coding Index, so price and context decide. Pick Muse Spark 1.1 for output tokens 1.0x cheaper ($4.25 vs $4.40 per million) and work measured by LiveCodeBench (Vals AI) or SkillsBench (Vals AI), where it leads. Pick GLM 5.3 for a lower cost per solved task ($0.36 against $0.43) and work measured by LMArena WebDev or AA Coding Index, where it leads.
Which is cheaper, GLM 5.3 or Muse Spark 1.1?
GLM 5.3 costs $1.40 per million input tokens and $4.40 per million output tokens; Muse Spark 1.1 costs $1.25 and $4.25. Per solved SWE-bench Verified task, GLM 5.3 costs $0.36 and Muse Spark 1.1 $0.43.
Which has the bigger context window, GLM 5.3 or Muse Spark 1.1?
Neither: both take 1.05M tokens.
How many benchmarks is the GLM 5.3 vs Muse Spark 1.1 comparison based on?
73 benchmarks have a result for both models as of October 22, 2026. GLM 5.3'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.