# GLM-5.3-Flash vs Qwen3.7 Flash

> GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 39.5 on the Noometry Index. Qwen3.7 Flash costs 4.3× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-5-3-flash-vs-qwen3-7-flash
- Last updated: 2026-10-10
- Shared benchmarks: 6

## Summary

- They share 6 benchmarks with published results for both. GLM-5.3-Flash scores higher in 3 categories and Qwen3.7 Flash in 0 categories; 3 gaps are clear of the uncertainty.
- The widest gap is in math, where GLM-5.3-Flash leads 53.1 to 37.3.
- The biggest single-benchmark swing is FrontierMath (Tiers 1-3): 55.8% for GLM-5.3-Flash and 19.3% for Qwen3.7 Flash.
- Qwen3.7 Flash is cheaper at $0.03 / $0.13 per million input/output tokens, against $0.15 / $0.50 for GLM-5.3-Flash.
- GLM-5.3-Flash has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 49.6 | 39.5 |
| Rank | 45 | 152 |
| Context | 1M | 1M |
| Input $/M | $0.15 | $0.03 |
| Output $/M | $0.50 | $0.13 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.3-Flash: 53.7 (#26)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| DeepSWE | 63.4% | — |
| FrontierCode | 31.8% | — |
| LMArena WebDev | 1614 | — |
| SciCode | 51.6% | — |
| LMArena Coding | 1506 | — |
| ALE-Bench | 303.55 | — |

## Agentic & Tool Use

- GLM-5.3-Flash: 34.3 (#41)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| APEX-Agents | 52.8% | — |
| GDP.pdf | 14% | — |

## Reasoning

- GLM-5.3-Flash: 31.7 (#69)
- Qwen3.7 Flash: 27.3 (#108)

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| Chess Puzzles | 14% | 23% |
| Mystery Game Puzzles | 8% | 15% |
| Epoch Capabilities Index | 151.9 | 144.62 |
| NYT Connections (extended) | — | 43.8% |
| CritPt | 15.4% | — |
| LMArena Hard Prompts | 1490 | — |
| Surface Evolver Bench | 52.5% | — |
| Bench to the Future 3 | 0.15 | — |

## Math

- GLM-5.3-Flash: 53.1 (#38)
- Qwen3.7 Flash: 37.3 (#100)

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| FrontierMath (Tiers 1-3) | 55.8% | 19.3% |
| OTIS Mock AIME 2024-2025 | 93.9% | 86.7% |
| FrontierMath Tier 4 | 17.1% | — |
| ProofBench | 21% | — |
| LMArena Math | 1499 | — |

## Knowledge

- GLM-5.3-Flash: 58.4 (#33)
- Qwen3.7 Flash: 48.9 (#69)

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| GPQA Diamond | 90.2% | 82.3% |
| LMArena Expert | 1512 | — |

## Multimodal

- GLM-5.3-Flash: 42.6 (#25)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| LMArena Vision | 1304 | — |

## Multilingual

- GLM-5.3-Flash: 56.2 (#24)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| LMArena Non-English | 1462 | — |
| LMArena Chinese | 1529 | — |
| LMArena French | 1495 | — |
| LMArena German | 1457 | — |
| LMArena Japanese | 1420 | — |
| LMArena Korean | 1443 | — |
| LMArena Russian | 1472 | — |
| LMArena Spanish | 1471 | — |

## Instruction Following

- GLM-5.3-Flash: 77.8 (#17)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| LMArena Instruction Following | 1480 | — |

## Long Context

- GLM-5.3-Flash: 45.3 (#41)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| LMArena Longer Query | 1479 | — |

## Writing & Preference

- GLM-5.3-Flash: 65.4 (#49)
- Qwen3.7 Flash: —

| Benchmark | GLM-5.3-Flash | Qwen3.7 Flash |
|---|---|---|
| LMArena Text | 1471 | — |
| LMArena Creative Writing | 1440 | — |
| LMArena Multi-Turn | 1471 | — |

## FAQ

### Is GLM-5.3-Flash better than Qwen3.7 Flash?

GLM-5.3-Flash is the stronger model overall, scoring 49.6 to 39.5 on the Noometry Index. Qwen3.7 Flash costs 4.3× less per token, which makes it the better buy when GLM-5.3-Flash's lead doesn't matter for your workload.

### Which is cheaper, GLM-5.3-Flash or Qwen3.7 Flash?

Qwen3.7 Flash is cheaper. It lists at $0.03 per million input tokens and $0.13 per million output tokens; GLM-5.3-Flash lists at $0.15 and $0.50.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do GLM-5.3-Flash and Qwen3.7 Flash share?

6 benchmarks have published results for both models. GLM-5.3-Flash has 36 scored results on Noometry and Qwen3.7 Flash has 7.