# GLM-5.2 vs Qwen3.7 Plus

> GLM-5.2 is the stronger model overall, scoring 50.9 to 45.0 on the Noometry Index. Qwen3.7 Plus costs 3.1× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-5-2-vs-qwen3-7-plus
- Last updated: 2026-10-10
- Shared benchmarks: 29

## Summary

- They share 29 benchmarks with published results for both. GLM-5.2 scores higher in 9 categories and Qwen3.7 Plus in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in coding, where GLM-5.2 leads 50.9 to 36.1.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 59.2% for GLM-5.2 and 34.4% for Qwen3.7 Plus.
- Qwen3.7 Plus is cheaper at $0.40 / $1.60 per million input/output tokens, against $1.40 / $4.40 for GLM-5.2.
- GLM-5.2 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 50.9 | 45.0 |
| Rank | 38 | 66 |
| Context | 1M | 1M |
| Input $/M | $1.40 | $0.40 |
| Output $/M | $4.40 | $1.60 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.2: 50.9 (#37)
- Qwen3.7 Plus: 36.1 (#200)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| FrontierCode | 24.5% | 10.2% |
| SciCode | 50.5% | 45.5% |
| LMArena Coding | 1484 | 1473 |
| SWE-bench Verified | 78.7% | — |
| DeepSWE | 43.8% | — |
| LMArena WebDev | 1604 | — |
| WeirdML | 70.1% | — |
| ALE-Bench | 1,047 | — |

## Agentic & Tool Use

- GLM-5.2: 31.6 (#63)
- Qwen3.7 Plus: 21.2 (#130)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| OSWorld 2.0 | — | 2.8% |
| τ²-bench Banking | 37.1% | — |
| PostTrainBench | 31.7% | — |
| GBAEval | 0% | — |
| Vending-Bench 2 | 8,314 | — |

## Reasoning

- GLM-5.2: 42.1 (#46)
- Qwen3.7 Plus: 38.4 (#54)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| NYT Connections (extended) | 74.3% | 74.8% |
| CritPt | 20.9% | 9.1% |
| Chess Puzzles | 21% | 24% |
| LMArena Hard Prompts | 1480 | 1460 |
| Mystery Game Puzzles | 19% | 17% |
| DTBench | 93.6% | 84% |
| LMCA | 45.8% | 37.6% |
| Epoch Capabilities Index | 151.76 | 147.39 |
| ARC-AGI-2 | 22.8% | — |
| SimpleBench | 58.8% | — |
| Kagi LLM Benchmark | 62.6% | — |
| ARC-AGI-1 | 77% | — |
| EBR-Bench | 9.5% | — |
| Surface Evolver Bench | 55.6% | — |

## Math

- GLM-5.2: 55.4 (#35)
- Qwen3.7 Plus: 49.3 (#47)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| FrontierMath (Tiers 1-3) | 59.2% | 34.4% |
| OTIS Mock AIME 2024-2025 | 86.4% | 93.3% |
| LMArena Math | 1482 | 1467 |
| FrontierMath Tier 4 | 29.3% | — |
| MathArena Final-Answer Competitions | 67.6% | — |
| ProofBench | 35% | — |

## Knowledge

- GLM-5.2: 57.1 (#36)
- Qwen3.7 Plus: 54.9 (#46)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| GPQA Diamond | 91.9% | 87.9% |
| LMArena Expert | 1484 | 1467 |
| SimpleQA Verified | 34.2% | — |

## Multimodal

- GLM-5.2: —
- Qwen3.7 Plus: 41.2 (#30)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| LMArena Vision | — | 1281 |
| LMArena Document | — | 1444 |

## Multilingual

- GLM-5.2: 56.0 (#25)
- Qwen3.7 Plus: 55.0 (#36)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| LMArena Non-English | 1459 | 1445 |
| LMArena Chinese | 1518 | 1510 |
| LMArena French | 1476 | 1471 |
| LMArena German | 1470 | 1471 |
| LMArena Japanese | 1451 | 1411 |
| LMArena Korean | 1445 | 1416 |
| LMArena Russian | 1467 | 1457 |
| LMArena Spanish | 1477 | 1453 |

## Instruction Following

- GLM-5.2: 77.1 (#32)
- Qwen3.7 Plus: 75.9 (#49)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| LMArena Instruction Following | 1465 | 1439 |

## Long Context

- GLM-5.2: 45.3 (#43)
- Qwen3.7 Plus: 44.5 (#61)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| LMArena Longer Query | 1479 | 1454 |

## Writing & Preference

- GLM-5.2: 70.7 (#20)
- Qwen3.7 Plus: 64.5 (#54)

| Benchmark | GLM-5.2 | Qwen3.7 Plus |
|---|---|---|
| LMArena Text | 1470 | 1454 |
| LMArena Creative Writing | 1465 | 1439 |
| LMArena Multi-Turn | 1468 | 1459 |
| EQ-Bench Creative Writing | 1757 | — |
| EQ-Bench 4 | 1222 | — |

## FAQ

### Is GLM-5.2 better than Qwen3.7 Plus?

GLM-5.2 is the stronger model overall, scoring 50.9 to 45.0 on the Noometry Index. Qwen3.7 Plus costs 3.1× less per token, which makes it the better buy when GLM-5.2's lead doesn't matter for your workload.

### Which is cheaper, GLM-5.2 or Qwen3.7 Plus?

Qwen3.7 Plus is cheaper. It lists at $0.40 per million input tokens and $1.60 per million output tokens; GLM-5.2 lists at $1.40 and $4.40.

### Is GLM-5.2 or Qwen3.7 Plus better for coding?

GLM-5.2 scores higher on coding benchmarks: 50.9 versus 36.1 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do GLM-5.2 and Qwen3.7 Plus share?

29 benchmarks have published results for both models. GLM-5.2 has 50 scored results on Noometry and Qwen3.7 Plus has 32.