# GLM-5.3-Flash vs QwQ-32B

> GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-qwq-32b
- Last updated: 2026-10-10
- Shared benchmarks: 21

## Summary

- They share 21 benchmarks with published results for both. GLM-5.3-Flash scores higher in 7 categories and QwQ-32B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.3-Flash leads 48.0 to 23.7.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 93.9% for GLM-5.3-Flash and 59.2% for QwQ-32B.

## Snapshot

| | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 51.8 | 39.8 |
| Rank | 41 | 159 |
| Context | 1M | — |
| Input $/M | $0.15 | — |
| Output $/M | $0.50 | — |
| Weights | Open | Open |

## Coding

- GLM-5.3-Flash: 53.1 (#31)
- QwQ-32B: 35.4 (#226)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Coding | 1508 | 1333 |
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| Aider Polyglot | — | 20.9% |
| CursorBench | 36.8% | — |
| LMArena WebDev | 1609 | — |
| FrontierSWE | 18.1% | — |
| SciCode | 51.6% | — |
| BigCodeBench Instruct | — | 44.6% |
| LiveBench Coding | — | 72.2% |
| BigCodeBench Complete | — | 54.4% |
| ALE-Bench | 303.55 | — |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.2 (#47)
- QwQ-32B: —

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 48.0 (#42)
- QwQ-32B: 23.7 (#174)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| Chess Puzzles | 14% | 5% |
| LMArena Hard Prompts | 1491 | 1325 |
| Epoch Capabilities Index | 151.88 | 137.6 |
| ARC-AGI-2 | 65.8% | — |
| ARC-AGI-1 | 91% | — |
| CritPt | 15.4% | — |
| LiveBench Reasoning | — | 83.5% |
| Mystery Game Puzzles | 8% | — |
| LiveBench Data Analysis | — | 65% |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |
| ForecastBench | — | 58.3 |
| LiveBench | — | 72% |

## Math

- GLM-5.3-Flash: 53.3 (#47)
- QwQ-32B: 38.0 (#143)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 93.9% | 59.2% |
| LMArena Math | 1500 | 1359 |
| FrontierMath (Tiers 1-3) | 55.8% | — |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
| LiveBench Math | — | 77.8% |

## Knowledge

- GLM-5.3-Flash: 58.4 (#36)
- QwQ-32B: 37.2 (#158)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| GPQA Diamond | 90.2% | 65.3% |
| LMArena Expert | 1513 | 1324 |
| Confabulations | — | 15.6% |

## Multimodal

- GLM-5.3-Flash: 42.8 (#27)
- QwQ-32B: —

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Vision | 1296 | — |

## Multilingual

- GLM-5.3-Flash: 56.0 (#25)
- QwQ-32B: 44.8 (#176)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Non-English | 1462 | 1305 |
| LMArena Chinese | 1527 | 1378 |
| LMArena French | 1496 | 1336 |
| LMArena German | 1470 | 1313 |
| LMArena Japanese | 1429 | 1262 |
| LMArena Korean | 1446 | 1279 |
| LMArena Russian | 1469 | 1297 |
| LMArena Spanish | 1471 | 1354 |

## Instruction Following

- GLM-5.3-Flash: 77.5 (#20)
- QwQ-32B: 72.6 (#137)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Instruction Following | 1478 | 1297 |
| LiveBench Instruction Following | — | 81.8% |

## Long Context

- GLM-5.3-Flash: 45.4 (#39)
- QwQ-32B: 49.0 (#11)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Longer Query | 1482 | 1308 |
| Fiction.LiveBench | — | 83.3% |

## Writing & Preference

- GLM-5.3-Flash: 65.3 (#50)
- QwQ-32B: 50.6 (#180)

| Benchmark | GLM-5.3-Flash | QwQ-32B |
|---|---|---|
| LMArena Text | 1471 | 1329 |
| LMArena Creative Writing | 1442 | 1288 |
| LMArena Multi-Turn | 1467 | 1314 |
| Short-Story Creative Writing | — | 80.2% |
| EQ-Bench Creative Writing | — | 1257 |
| LiveBench Language | — | 51.4% |

## FAQ

### Is GLM-5.3-Flash better than QwQ-32B?

GLM-5.3-Flash is the stronger model overall, scoring 51.8 to 39.8 on the Noometry Index.

### Is GLM-5.3-Flash or QwQ-32B better for coding?

GLM-5.3-Flash scores higher on coding benchmarks: 53.1 versus 35.4 in the Noometry coding category.

### How many benchmarks do GLM-5.3-Flash and QwQ-32B share?

21 benchmarks have published results for both models. GLM-5.3-Flash has 40 scored results on Noometry and QwQ-32B has 36.