# GLM-5.3 vs Qwen3 Coder Next

> GLM-5.3 is the stronger model overall, scoring 54.6 to 33.8 on the Noometry Index. Qwen3 Coder Next costs 7.4× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

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

## Summary

- They share 3 benchmarks with published results for both. GLM-5.3 scores higher in 2 categories and Qwen3 Coder Next in 0 categories; 2 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-5.3 leads 45.2 to 21.7.
- The biggest single-benchmark swing is WeirdML: 75.4% for GLM-5.3 and 34.4% for Qwen3 Coder Next.
- Qwen3 Coder Next is cheaper at $0.12 / $0.80 per million input/output tokens, against $1.40 / $4.40 for GLM-5.3.
- GLM-5.3 accepts more context: 1M tokens versus 262K.

## Snapshot

| | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 54.6 | 33.8 |
| Rank | 25 | 229 |
| Context | 1M | 262K |
| Input $/M | $1.40 | $0.12 |
| Output $/M | $4.40 | $0.80 |
| Weights | Open | Open |

## Coding

- GLM-5.3: 59.0 (#12)
- Qwen3 Coder Next: 35.8 (#206)

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| SciCode | 59% | 32.3% |
| WeirdML | 75.4% | 34.4% |
| DeepSWE | 69% | — |
| FrontierCode | 40.1% | — |
| LMArena WebDev | 1623 | — |
| FrontierSWE | 30.2% | — |
| LMArena Coding | 1499 | — |
| ALE-Bench | 1,317 | — |

## Agentic & Tool Use

- GLM-5.3: 36.3 (#34)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| APEX-Agents | 56.6% | — |
| Vending-Bench 2 | 8,164 | — |

## Reasoning

- GLM-5.3: 45.2 (#42)
- Qwen3 Coder Next: 21.7 (#191)

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| CritPt | 19.1% | 0% |
| NYT Connections (extended) | 74.2% | — |
| Chess Puzzles | 21% | — |
| LMArena Hard Prompts | 1491 | — |
| 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)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| FrontierMath (Tiers 1-3) | 68.8% | — |
| FrontierMath Tier 4 | 29.3% | — |
| OTIS Mock AIME 2024-2025 | 91.1% | — |
| ProofBench | 49% | — |
| LMArena Math | 1493 | — |

## Knowledge

- GLM-5.3: 58.3 (#34)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| GPQA Diamond | 90.9% | — |
| SimpleQA Verified | 41% | — |
| LMArena Expert | 1512 | — |

## Multilingual

- GLM-5.3: 55.9 (#27)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Non-English | 1457 | — |
| LMArena Chinese | 1523 | — |
| LMArena French | 1499 | — |
| LMArena German | 1505 | — |
| LMArena Japanese | 1438 | — |
| LMArena Korean | 1478 | — |
| LMArena Russian | 1460 | — |
| LMArena Spanish | 1444 | — |

## Instruction Following

- GLM-5.3: 77.8 (#15)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Instruction Following | 1481 | — |

## Long Context

- GLM-5.3: 45.5 (#32)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Longer Query | 1485 | — |

## Writing & Preference

- GLM-5.3: 75.9 (#6)
- Qwen3 Coder Next: —

| Benchmark | GLM-5.3 | Qwen3 Coder Next |
|---|---|---|
| LMArena Text | 1473 | — |
| LMArena Creative Writing | 1459 | — |
| EQ-Bench Creative Writing | 2075 | — |
| LMArena Multi-Turn | 1473 | — |

## FAQ

### Is GLM-5.3 better than Qwen3 Coder Next?

GLM-5.3 is the stronger model overall, scoring 54.6 to 33.8 on the Noometry Index. Qwen3 Coder Next costs 7.4× less per token, which makes it the better buy when GLM-5.3's lead doesn't matter for your workload.

### Which is cheaper, GLM-5.3 or Qwen3 Coder Next?

Qwen3 Coder Next is cheaper. It lists at $0.12 per million input tokens and $0.80 per million output tokens; GLM-5.3 lists at $1.40 and $4.40.

### Is GLM-5.3 or Qwen3 Coder Next better for coding?

GLM-5.3 scores higher on coding benchmarks: 59.0 versus 35.8 in the Noometry coding category.

### Which has the bigger context window?

GLM-5.3 does, with 1M tokens against 262K.

### How many benchmarks do GLM-5.3 and Qwen3 Coder Next share?

3 benchmarks have published results for both models. GLM-5.3 has 41 scored results on Noometry and Qwen3 Coder Next has 3.