# GLM-4.6V vs Qwen3.5-9B

> GLM-4.6V is the stronger model overall, scoring 41.3 to 33.8 on the Noometry Index. Qwen3.5-9B costs 4.0× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

- Canonical page: https://noometry.com/compare/glm-4-6v-vs-qwen3-5-9b
- Last updated: 2026-10-12
- Shared benchmarks: 0

## Summary

- The widest gap is in knowledge, where Qwen3.5-9B leads 46.0 to 38.0.
- Qwen3.5-9B is cheaper at $0.10 / $0.15 per million input/output tokens, against $0.30 / $0.90 for GLM-4.6V.
- Qwen3.5-9B accepts more context: 262K tokens versus 128K.

## Snapshot

| | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| Provider | Z.ai (Zhipu) | Alibaba (Qwen) |
| Noometry Index | 41.3 | 33.8 |
| Rank | 137 | 236 |
| Context | 128K | 262K |
| Input $/M | $0.30 | $0.10 |
| Output $/M | $0.90 | $0.15 |
| Weights | Open | Open |

## Coding

- GLM-4.6V: 40.9 (#128)
- Qwen3.5-9B: 35.9 (#217)

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| SciCode | — | 27.5% |
| LMArena Coding | 1390 | — |

## Agentic & Tool Use

- GLM-4.6V: —
- Qwen3.5-9B: 14.5 (#151)

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| Terminal-Bench | — | 9.2% |

## Reasoning

- GLM-4.6V: 27.6 (#115)
- Qwen3.5-9B: 23.1 (#182)

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| CritPt | — | 0.3% |
| Chess Puzzles | — | 12% |
| LMArena Hard Prompts | 1368 | — |
| DTBench | — | 71.2% |
| LMCA | — | 24.5% |
| Epoch Capabilities Index | — | 139.46 |

## Math

- GLM-4.6V: —
- Qwen3.5-9B: 34.8 (#192)

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| MathArena Final-Answer Competitions | — | 48.5% |
| OTIS Mock AIME 2024-2025 | — | 61.7% |

## Knowledge

- GLM-4.6V: 38.0 (#149)
- Qwen3.5-9B: 46.0 (#84)

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| GPQA Diamond | — | 79% |
| LMArena Expert | 1371 | — |

## Multimodal

- GLM-4.6V: 34.8 (#90)
- Qwen3.5-9B: —

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Vision | 1164 | — |

## Multilingual

- GLM-4.6V: 48.6 (#141)
- Qwen3.5-9B: —

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Non-English | 1359 | — |
| LMArena Chinese | 1425 | — |
| LMArena Russian | 1340 | — |

## Instruction Following

- GLM-4.6V: 71.4 (#151)
- Qwen3.5-9B: —

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Instruction Following | 1352 | — |

## Long Context

- GLM-4.6V: 41.3 (#143)
- Qwen3.5-9B: —

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Longer Query | 1358 | — |

## Writing & Preference

- GLM-4.6V: 56.6 (#137)
- Qwen3.5-9B: —

| Benchmark | GLM-4.6V | Qwen3.5-9B |
|---|---|---|
| LMArena Text | 1377 | — |
| LMArena Creative Writing | 1347 | — |
| LMArena Multi-Turn | 1360 | — |

## FAQ

### Is GLM-4.6V better than Qwen3.5-9B?

GLM-4.6V is the stronger model overall, scoring 41.3 to 33.8 on the Noometry Index. Qwen3.5-9B costs 4.0× less per token, which makes it the better buy when GLM-4.6V's lead doesn't matter for your workload.

### Which is cheaper, GLM-4.6V or Qwen3.5-9B?

Qwen3.5-9B is cheaper. It lists at $0.10 per million input tokens and $0.15 per million output tokens; GLM-4.6V lists at $0.30 and $0.90.

### Is GLM-4.6V or Qwen3.5-9B better for coding?

GLM-4.6V scores higher on coding benchmarks: 40.9 versus 35.9 in the Noometry coding category.

### Which has the bigger context window?

Qwen3.5-9B does, with 262K tokens against 128K.

### How many benchmarks do GLM-4.6V and Qwen3.5-9B share?

0 benchmarks have published results for both models. GLM-4.6V has 12 scored results on Noometry and Qwen3.5-9B has 10.