# DeepSeek-V3.2-Speciale vs GLM-4.5V

> DeepSeek-V3.2-Speciale and GLM-4.5V score almost the same on the Noometry Index (39.1 vs 39.2), so choose on price, context window or the category you care about most.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-glm-4-5v
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where GLM-4.5V leads 52.7 to 46.1.
- Both cost about the same: $0.58 input and $1.68 output per million tokens.
- DeepSeek-V3.2-Speciale accepts more context: 128K tokens versus 64K.

## Snapshot

| | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| Provider | DeepSeek | Z.ai (Zhipu) |
| Noometry Index | 39.1 | 39.2 |
| Rank | 159 | 158 |
| Context | 128K | 64K |
| Input $/M | $0.58 | $0.60 |
| Output $/M | $1.68 | $1.80 |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- GLM-4.5V: 38.9 (#152)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1347 |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- GLM-4.5V: 26.5 (#118)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 59.8% |
| LMArena Hard Prompts | — | 1335 |

## Math

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 34.7 (#157)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Math | — | 1353 |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 36.8 (#155)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Expert | — | 1353 |

## Multimodal

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 33.6 (#86)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Vision | — | 1154 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 44.9 (#172)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Non-English | — | 1304 |
| LMArena Chinese | — | 1338 |
| LMArena Russian | — | 1299 |
| LMArena Spanish | — | 1335 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 69.4 (#170)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Instruction Following | — | 1311 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- GLM-4.5V: 39.6 (#166)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Longer Query | — | 1305 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- GLM-4.5V: 52.7 (#162)

| Benchmark | DeepSeek-V3.2-Speciale | GLM-4.5V |
|---|---|---|
| LMArena Text | — | 1333 |
| LMArena Creative Writing | — | 1295 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1333 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than GLM-4.5V?

DeepSeek-V3.2-Speciale and GLM-4.5V score almost the same on the Noometry Index (39.1 vs 39.2), so choose on price, context window or the category you care about most.

### Which is cheaper, DeepSeek-V3.2-Speciale or GLM-4.5V?

DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; GLM-4.5V lists at $0.60 and $1.80.

### Is DeepSeek-V3.2-Speciale or GLM-4.5V better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 38.9 in the Noometry coding category.

### Which has the bigger context window?

DeepSeek-V3.2-Speciale does, with 128K tokens against 64K.

### How many benchmarks do DeepSeek-V3.2-Speciale and GLM-4.5V share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and GLM-4.5V has 15.