# GLM-5.3 vs Qwen1.5-72B

> GLM-5.3 is the stronger model overall, scoring 54.6 to 30.3 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-vs-qwen1-5-72b
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. GLM-5.3 scores higher in 8 categories and Qwen1.5-72B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where GLM-5.3 leads 58.3 to 11.5.
- The biggest single-benchmark swing is GPQA Diamond: 90.9% for GLM-5.3 and 28.8% for Qwen1.5-72B.

## Snapshot

| | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 54.6 | 30.3 |
| Rank | 25 | 282 |
| Context | 1M | — |
| Input $/M | $1.40 | — |
| Output $/M | $4.40 | — |
| Weights | Open | Open |

## Coding

- GLM-5.3: 59.0 (#12)
- Qwen1.5-72B: 31.4 (#272)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Coding | 1499 | 1166 |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| LMArena WebDev | 1623 | — |
| FrontierSWE | 30.2% | — |
| SciCode | 59% | — |
| WeirdML | 75.4% | — |
| BigCodeBench Instruct | — | 33.2% |
| BigCodeBench Complete | — | 40.3% |
| ALE-Bench | 1,317 | — |
| HumanEval+ | — | 59.1% |
| MBPP+ | — | 61.6% |

## Agentic & Tool Use

- GLM-5.3: 36.3 (#34)
- Qwen1.5-72B: —

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Vending-Bench 2 | 8,164 | — |

## Reasoning

- GLM-5.3: 45.2 (#42)
- Qwen1.5-72B: 21.2 (#201)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Hard Prompts | 1491 | 1148 |
| NYT Connections (extended) | 74.2% | — |
| CritPt | 19.1% | — |
| Chess Puzzles | 21% | — |
| Mystery Game Puzzles | 33% | — |
| DTBench | 87.7% | — |
| LMCA | 55.5% | — |
| Bench to the Future 3 | 0.15 | — |
| Epoch Capabilities Index | 155.56 | — |

## Math

- GLM-5.3: 62.1 (#27)
- Qwen1.5-72B: 30.7 (#205)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Math | 1493 | 1164 |
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 91.1% | — |
| ProofBench | 49% | — |

## Knowledge

- GLM-5.3: 58.3 (#34)
- Qwen1.5-72B: 11.5 (#295)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| GPQA Diamond | 90.9% | 28.8% |
| LMArena Expert | 1512 | 1136 |
| SimpleQA Verified | 41% | — |

## Multilingual

- GLM-5.3: 55.9 (#27)
- Qwen1.5-72B: 33.4 (#248)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Non-English | 1457 | 1135 |
| LMArena Chinese | 1523 | 1186 |
| LMArena French | 1499 | 1158 |
| LMArena German | 1505 | 1084 |
| LMArena Japanese | 1438 | 1061 |
| LMArena Korean | 1478 | 1049 |
| LMArena Russian | 1460 | 1104 |
| LMArena Spanish | 1444 | 1110 |

## Instruction Following

- GLM-5.3: 77.8 (#15)
- Qwen1.5-72B: 59.6 (#251)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Instruction Following | 1481 | 1142 |

## Long Context

- GLM-5.3: 45.5 (#32)
- Qwen1.5-72B: 35.0 (#238)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Longer Query | 1485 | 1157 |

## Writing & Preference

- GLM-5.3: 75.9 (#6)
- Qwen1.5-72B: 37.4 (#253)

| Benchmark | GLM-5.3 | Qwen1.5-72B |
|---|---|---|
| LMArena Text | 1473 | 1166 |
| LMArena Creative Writing | 1459 | 1137 |
| LMArena Multi-Turn | 1473 | 1160 |
| EQ-Bench Creative Writing | 2075 | — |

## FAQ

### Is GLM-5.3 better than Qwen1.5-72B?

GLM-5.3 is the stronger model overall, scoring 54.6 to 30.3 on the Noometry Index.

### Is GLM-5.3 or Qwen1.5-72B better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 31.4 in the Noometry coding category.

### How many benchmarks do GLM-5.3 and Qwen1.5-72B share?

18 benchmarks have published results for both models. GLM-5.3 has 41 scored results on Noometry and Qwen1.5-72B has 22.