# GLM-5.2 vs Muse Spark 1.1

> GLM-5.2 is the stronger model overall, scoring 50.9 to 49.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-2-vs-muse-spark-1-1
- Last updated: 2026-10-10
- Shared benchmarks: 33

## Summary

- They share 33 benchmarks with published results for both. GLM-5.2 scores higher in 5 categories and Muse Spark 1.1 in 4 categories; 5 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.2 leads 55.4 to 44.0.
- The biggest single-benchmark swing is SimpleQA Verified: 34.2% for GLM-5.2 and 57.8% for Muse Spark 1.1.
- Muse Spark 1.1 is cheaper at $1.25 / $4.25 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
- Muse Spark 1.1 accepts more context: 1.05M tokens versus 1M.
- GLM-5.2 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| Provider | Z.ai (Zhipu) | Meta |
| Noometry Index | 50.9 | 49.9 |
| Rank | 38 | 43 |
| Context | 1M | 1.05M |
| Input $/M | $1.40 | $1.25 |
| Output $/M | $4.40 | $4.25 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.2: 50.9 (#37)
- Muse Spark 1.1: 50.8 (#38)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| DeepSWE | 43.8% | 53.3% |
| LMArena WebDev | 1604 | 1542 |
| SciCode | 50.5% | 58.8% |
| LMArena Coding | 1484 | 1497 |
| SWE-bench Verified | 78.7% | — |
| FrontierCode | 24.5% | — |
| WeirdML | 70.1% | — |
| ALE-Bench | 1,047 | — |

## Agentic & Tool Use

- GLM-5.2: 31.6 (#63)
- Muse Spark 1.1: 33.9 (#45)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| τ²-bench Banking | 37.1% | 40.5% |
| GBAEval | 0% | 7.9% |
| Vending-Bench 2 | 8,314 | 6,520 |
| PostTrainBench | 31.7% | — |
| GDP.pdf | — | 15% |

## Reasoning

- GLM-5.2: 42.1 (#46)
- Muse Spark 1.1: 45.9 (#41)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| NYT Connections (extended) | 74.3% | 84.9% |
| CritPt | 20.9% | 15.1% |
| LMArena Hard Prompts | 1480 | 1486 |
| DTBench | 93.6% | 94.4% |
| LMCA | 45.8% | 49.9% |
| Surface Evolver Bench | 55.6% | 52.5% |
| Epoch Capabilities Index | 151.76 | 154.32 |
| ARC-AGI-2 | 22.8% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| ARC-AGI-1 | 77% | — |
| Chess Puzzles | 21% | — |
| EBR-Bench | 9.5% | — |
| Mystery Game Puzzles | 19% | — |

## Math

- GLM-5.2: 55.4 (#35)
- Muse Spark 1.1: 44.0 (#67)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| ProofBench | 35% | 39% |
| LMArena Math | 1482 | 1477 |
| FrontierMath (Tiers 1-3) | 59.2% | — |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| OTIS Mock AIME 2024-2025 | 86.4% | — |

## Knowledge

- GLM-5.2: 57.1 (#36)
- Muse Spark 1.1: 52.8 (#55)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| SimpleQA Verified | 34.2% | 57.8% |
| LMArena Expert | 1484 | 1480 |
| GPQA Diamond | 91.9% | — |

## Multimodal

- GLM-5.2: —
- Muse Spark 1.1: 41.9 (#28)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| LMArena Vision | — | 1292 |
| LMArena Document | — | 1465 |

## Multilingual

- GLM-5.2: 56.0 (#25)
- Muse Spark 1.1: 56.8 (#16)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| LMArena Non-English | 1459 | 1471 |
| LMArena Chinese | 1518 | 1518 |
| LMArena French | 1476 | 1494 |
| LMArena German | 1470 | 1466 |
| LMArena Japanese | 1451 | 1445 |
| LMArena Korean | 1445 | 1459 |
| LMArena Russian | 1467 | 1482 |
| LMArena Spanish | 1477 | 1471 |

## Instruction Following

- GLM-5.2: 77.1 (#32)
- Muse Spark 1.1: 76.8 (#36)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| LMArena Instruction Following | 1465 | 1457 |

## Long Context

- GLM-5.2: 45.3 (#43)
- Muse Spark 1.1: 44.8 (#55)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| LMArena Longer Query | 1479 | 1463 |

## Writing & Preference

- GLM-5.2: 70.7 (#20)
- Muse Spark 1.1: 73.6 (#11)

| Benchmark | GLM-5.2 | Muse Spark 1.1 |
|---|---|---|
| LMArena Text | 1470 | 1479 |
| LMArena Creative Writing | 1465 | 1440 |
| EQ-Bench Creative Writing | 1757 | 1927 |
| EQ-Bench 4 | 1222 | 1260 |
| LMArena Multi-Turn | 1468 | 1484 |

## FAQ

### Is GLM-5.2 better than Muse Spark 1.1?

GLM-5.2 is the stronger model overall, scoring 50.9 to 49.9 on the Noometry Index.

### Which is cheaper, GLM-5.2 or Muse Spark 1.1?

Muse Spark 1.1 is cheaper. It lists at $1.25 per million input tokens and $4.25 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.

### Is GLM-5.2 or Muse Spark 1.1 better for coding?

They score almost the same on coding (50.9 vs 50.8); test both on your own repository before choosing.

### Which has the bigger context window?

Muse Spark 1.1 does, with 1.05M tokens against 1M.

### How many benchmarks do GLM-5.2 and Muse Spark 1.1 share?

33 benchmarks have published results for both models. GLM-5.2 has 50 scored results on Noometry and Muse Spark 1.1 has 36.