# GLM-5.3 vs Qwen3.8 Max

> Qwen3.8 Max is the stronger model overall, scoring 56.0 to 54.6 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-5-3-vs-qwen3-8-max
- Last updated: 2026-10-10
- Shared benchmarks: 34

## Summary

- They share 34 benchmarks with published results for both. GLM-5.3 scores higher in 3 categories and Qwen3.8 Max in 6 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in math, where Qwen3.8 Max leads 73.1 to 62.1.
- The biggest single-benchmark swing is Chess Puzzles: 21% for GLM-5.3 and 40% for Qwen3.8 Max.
- GLM-5.3 is cheaper at $1.40 / $4.40 per million input/output tokens, against $2 / $6 for Qwen3.8 Max.
- GLM-5.3 has downloadable open weights; the other is API-only.

## Snapshot

| | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 54.6 | 56.0 |
| Rank | 25 | 21 |
| Context | 1M | 1M |
| Input $/M | $1.40 | $2 |
| Output $/M | $4.40 | $6 |
| Weights | Open | Proprietary |

## Coding

- GLM-5.3: 59.0 (#12)
- Qwen3.8 Max: 52.3 (#30)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| DeepSWE | 69% | 57.5% |
| LMArena WebDev | 1623 | 1671 |
| FrontierSWE | 30.2% | 15.8% |
| SciCode | 59% | 52.9% |
| LMArena Coding | 1499 | 1499 |
| FrontierCode | 40.1% | — |
| WeirdML | 75.4% | — |
| ALE-Bench | 1,317 | — |

## Agentic & Tool Use

- GLM-5.3: 36.3 (#34)
- Qwen3.8 Max: 42.6 (#17)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| APEX-Agents | 56.6% | — |
| τ²-bench Banking | — | 55.1% |
| GDP.pdf | — | 23.2% |
| Vending-Bench 2 | 8,164 | — |

## Reasoning

- GLM-5.3: 45.2 (#42)
- Qwen3.8 Max: 53.4 (#26)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| NYT Connections (extended) | 74.2% | 88.3% |
| CritPt | 19.1% | 20% |
| Chess Puzzles | 21% | 40% |
| LMArena Hard Prompts | 1491 | 1493 |
| Mystery Game Puzzles | 33% | 38% |
| DTBench | 87.7% | 92% |
| LMCA | 55.5% | 46.2% |
| Epoch Capabilities Index | 155.56 | 156.69 |
| Bench to the Future 3 | 0.15 | — |

## Math

- GLM-5.3: 62.1 (#27)
- Qwen3.8 Max: 73.1 (#15)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| FrontierMath (Tiers 1-3) | 68.8% | 74.7% |
| FrontierMath Tier 4 | 29.3% | 46.3% |
| OTIS Mock AIME 2024-2025 | 91.1% | 100% |
| ProofBench | 49% | 58% |
| LMArena Math | 1493 | 1498 |

## Knowledge

- GLM-5.3: 58.3 (#34)
- Qwen3.8 Max: 61.7 (#25)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| GPQA Diamond | 90.9% | 92.7% |
| SimpleQA Verified | 41% | 47.3% |
| LMArena Expert | 1512 | 1504 |

## Multimodal

- GLM-5.3: —
- Qwen3.8 Max: 36.9 (#70)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| LMArena Vision | — | 1314 |
| Furniture Assembly | — | 20% |

## Multilingual

- GLM-5.3: 55.9 (#27)
- Qwen3.8 Max: 56.6 (#18)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| LMArena Non-English | 1457 | 1468 |
| LMArena Chinese | 1523 | 1537 |
| LMArena French | 1499 | 1502 |
| LMArena German | 1505 | 1489 |
| LMArena Japanese | 1438 | 1466 |
| LMArena Korean | 1478 | 1467 |
| LMArena Russian | 1460 | 1478 |
| LMArena Spanish | 1444 | 1495 |

## Instruction Following

- GLM-5.3: 77.8 (#15)
- Qwen3.8 Max: 77.7 (#19)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| LMArena Instruction Following | 1481 | 1478 |

## Long Context

- GLM-5.3: 45.5 (#32)
- Qwen3.8 Max: 45.5 (#30)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| LMArena Longer Query | 1485 | 1486 |

## Writing & Preference

- GLM-5.3: 75.9 (#6)
- Qwen3.8 Max: 67.0 (#31)

| Benchmark | GLM-5.3 | Qwen3.8 Max |
|---|---|---|
| LMArena Text | 1473 | 1480 |
| LMArena Creative Writing | 1459 | 1478 |
| LMArena Multi-Turn | 1473 | 1487 |
| EQ-Bench Creative Writing | 2075 | — |

## FAQ

### Is GLM-5.3 better than Qwen3.8 Max?

Qwen3.8 Max is the stronger model overall, scoring 56.0 to 54.6 on the Noometry Index.

### Which is cheaper, GLM-5.3 or Qwen3.8 Max?

GLM-5.3 is cheaper. It lists at $1.40 per million input tokens and $4.40 per million output tokens; Qwen3.8 Max lists at $2 and $6.

### Is GLM-5.3 or Qwen3.8 Max better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 52.3 in the Noometry coding category.

### Which has the bigger context window?

Both accept 1M tokens.

### How many benchmarks do GLM-5.3 and Qwen3.8 Max share?

34 benchmarks have published results for both models. GLM-5.3 has 41 scored results on Noometry and Qwen3.8 Max has 38.