# GLM-4.6V vs Qwen3 32B

> GLM-4.6V is the stronger model overall, scoring 40.9 to 38.8 on the Noometry Index.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-qwen3-32b
- Last updated: 2026-10-10
- Shared benchmarks: 11

## Summary

- They share 11 benchmarks with published results for both. GLM-4.6V scores higher in 5 categories and Qwen3 32B in 2 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where GLM-4.6V leads 26.5 to 19.6.
- GLM-4.6V is cheaper at $0.30 / $0.90 per million input/output tokens, against $0.70 / $2.80 for Qwen3 32B.
- Qwen3 32B accepts more context: 131K tokens versus 128K.

## Snapshot

| | GLM-4.6V | Qwen3 32B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 40.9 | 38.8 |
| Rank | 133 | 166 |
| Context | 128K | 131K |
| Input $/M | $0.30 | $0.70 |
| Output $/M | $0.90 | $2.80 |
| Weights | Open | Open |

## Coding

- GLM-4.6V: 40.2 (#128)
- Qwen3 32B: 37.3 (#184)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Coding | 1390 | 1358 |
| Aider Polyglot | — | 40% |
| SciCode | — | 35.4% |

## Agentic & Tool Use

- GLM-4.6V: —
- Qwen3 32B: 32.3 (#58)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| Berkeley Function Calling Leaderboard | — | 48.7% |

## Reasoning

- GLM-4.6V: 26.5 (#117)
- Qwen3 32B: 19.6 (#233)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Hard Prompts | 1368 | 1335 |
| Kagi LLM Benchmark | — | 54.9% |
| CritPt | — | 0.3% |
| Chess Puzzles | — | 5% |
| DTBench | — | 67.5% |
| LMCA | — | 17.3% |
| Epoch Capabilities Index | — | 138.51 |

## Math

- GLM-4.6V: —
- Qwen3 32B: 37.9 (#89)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.9% |
| LMArena Math | — | 1399 |

## Knowledge

- GLM-4.6V: 37.4 (#148)
- Qwen3 32B: 40.0 (#112)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Expert | 1372 | 1362 |
| GPQA Diamond | — | 65.7% |
| Vectara Hallucination Rate | — | 5.9% |

## Multimodal

- GLM-4.6V: 34.2 (#83)
- Qwen3 32B: —

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Vision | 1164 | — |

## Multilingual

- GLM-4.6V: 48.8 (#135)
- Qwen3 32B: 45.8 (#162)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Non-English | 1359 | 1317 |
| LMArena Chinese | 1426 | 1357 |
| LMArena Russian | 1341 | 1311 |
| LMArena German | — | 1341 |

## Instruction Following

- GLM-4.6V: 71.6 (#145)
- Qwen3 32B: 69.1 (#174)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Instruction Following | 1351 | 1305 |

## Long Context

- GLM-4.6V: 41.3 (#138)
- Qwen3 32B: 43.7 (#83)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Longer Query | 1358 | 1327 |
| Fiction.LiveBench | — | 74.2% |

## Writing & Preference

- GLM-4.6V: 56.8 (#132)
- Qwen3 32B: 53.1 (#158)

| Benchmark | GLM-4.6V | Qwen3 32B |
|---|---|---|
| LMArena Text | 1377 | 1340 |
| LMArena Creative Writing | 1347 | 1297 |
| LMArena Multi-Turn | 1359 | 1331 |

## FAQ

### Is GLM-4.6V better than Qwen3 32B?

GLM-4.6V is the stronger model overall, scoring 40.9 to 38.8 on the Noometry Index.

### Which is cheaper, GLM-4.6V or Qwen3 32B?

GLM-4.6V is cheaper. It lists at $0.30 per million input tokens and $0.90 per million output tokens; Qwen3 32B lists at $0.70 and $2.80.

### Is GLM-4.6V or Qwen3 32B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.2 versus 37.3 in the Noometry coding category.

### Which has the bigger context window?

Qwen3 32B does, with 131K tokens against 128K.

### How many benchmarks do GLM-4.6V and Qwen3 32B share?

11 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3 32B has 26.