# GLM-5.1 vs Muse Spark 1.3

> Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 47.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-1-vs-muse-spark-1-3
- Last updated: 2026-10-10
- Shared benchmarks: 28

## Summary

- They share 28 benchmarks with published results for both. GLM-5.1 scores higher in 1 category and Muse Spark 1.3 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in math, where Muse Spark 1.3 leads 73.1 to 49.7.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 36.8% for GLM-5.1 and 74.4% for Muse Spark 1.3.
- Muse Spark 1.3 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.40 / $4.40 for GLM-5.1.
- Muse Spark 1.3 accepts more context: 1.05M tokens versus 200K.
- GLM-5.1 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 47.8 | 54.8 |
| Rank | 59 | 27 |
| Context | 200K | 1.05M |
| Input $/M | $1.40 | $1.25 |
| Output $/M | $4.40 | $4.25 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.1: 48.7 (#55)
- Muse Spark 1.3: 56.6 (#21)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena WebDev | 1508 | 1657 |
| SciCode | 43.8% | 59.7% |
| LMArena Coding | 1485 | 1514 |
| SWE-bench Verified | 74.2% | — |
| CursorBench | — | 41.6% |
| WeirdML | 57.1% | — |
| ALE-Bench | 887.1 | — |

## Agentic & Tool Use

- GLM-5.1: 24.9 (#113)
- Muse Spark 1.3: 38.6 (#30)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| APEX-Agents | 40.9% | 57.8% |
| ExploitBench | 18.1% | — |
| GBAEval | 0% | — |
| GDP.pdf | — | 27.6% |
| Vending-Bench 2 | 5,634 | — |

## Reasoning

- GLM-5.1: 39.1 (#60)
- Muse Spark 1.3: 54.0 (#27)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| NYT Connections (extended) | 77.7% | 85.1% |
| CritPt | 4.6% | 26% |
| Chess Puzzles | 19% | 38% |
| LMArena Hard Prompts | 1472 | 1503 |
| Epoch Capabilities Index | 149.84 | 156.75 |
| SimpleBench | 55.1% | — |
| Thematic Generalization | 69.8% | — |
| Mystery Game Puzzles | — | 25% |
| DTBench | — | 96.5% |
| LMCA | — | 53.9% |
| Bench to the Future 3 | — | 0.14 |

## Math

- GLM-5.1: 49.7 (#60)
- Muse Spark 1.3: 73.1 (#21)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| FrontierMath (Tiers 1-3) | 36.8% | 74.4% |
| OTIS Mock AIME 2024-2025 | 93.3% | 99.2% |
| ProofBench | 22.2% | 58% |
| LMArena Math | 1473 | 1494 |
| FrontierMath Tier 4 | — | 46.3% |
| MathArena Final-Answer Competitions | 67.1% | — |
| FrontierMath (Feb 2025 set) | 33.4% | — |
| FrontierMath Tier 4 (v1) | 12.5% | — |

## Knowledge

- GLM-5.1: 54.9 (#50)
- Muse Spark 1.3: 42.6 (#95)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Expert | 1476 | 1516 |
| GPQA Diamond | 89.9% | — |
| SimpleQA Verified | 34% | — |

## Multimodal

- GLM-5.1: —
- Muse Spark 1.3: 43.7 (#22)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Vision | — | 1309 |
| LMArena Document | — | 1471 |

## Multilingual

- GLM-5.1: 55.0 (#36)
- Muse Spark 1.3: 57.4 (#8)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Non-English | 1447 | 1481 |
| LMArena Chinese | 1515 | 1529 |
| LMArena French | 1474 | 1524 |
| LMArena German | 1465 | 1515 |
| LMArena Japanese | 1434 | 1474 |
| LMArena Korean | 1418 | 1501 |
| LMArena Russian | 1454 | 1490 |
| LMArena Spanish | 1469 | 1490 |

## Instruction Following

- GLM-5.1: 76.3 (#42)
- Muse Spark 1.3: 77.5 (#22)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Instruction Following | 1451 | 1477 |

## Long Context

- GLM-5.1: 44.9 (#53)
- Muse Spark 1.3: 45.6 (#32)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Longer Query | 1466 | 1488 |

## Writing & Preference

- GLM-5.1: 66.9 (#31)
- Muse Spark 1.3: 73.6 (#9)

| Benchmark | GLM-5.1 | Muse Spark 1.3 |
|---|---|---|
| LMArena Text | 1461 | 1490 |
| LMArena Creative Writing | 1453 | 1455 |
| EQ-Bench Creative Writing | 1592 | 1906 |
| LMArena Multi-Turn | 1472 | 1482 |

## FAQ

### Is GLM-5.1 better than Muse Spark 1.3?

Muse Spark 1.3 is the stronger model overall, scoring 54.8 to 47.8 on the Noometry Index.

### Which is cheaper, GLM-5.1 or Muse Spark 1.3?

Muse Spark 1.3 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GLM-5.1 lists at $1.40 and $4.40.

### Is GLM-5.1 or Muse Spark 1.3 better for coding?

Muse Spark 1.3 scores higher on coding benchmarks: 56.6 versus 48.7 in the Noometry coding category.

### Which has the bigger context window?

Muse Spark 1.3 does, with 1.05M tokens against 200K.

### How many benchmarks do GLM-5.1 and Muse Spark 1.3 share?

28 benchmarks have published results for both models. GLM-5.1 has 41 scored results on Noometry and Muse Spark 1.3 has 37.