# DeepSeek-V3.2-Speciale vs Qwen Plus

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 36.7 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-qwen-plus
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where Qwen Plus leads 52.4 to 46.1.
- Qwen Plus is cheaper at $0.40 / $1.20 per million input/output tokens, against $0.58 / $1.68 for DeepSeek-V3.2-Speciale.
- Qwen Plus accepts more context: 1M tokens versus 128K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 39.1 | 36.7 |
| Rank | 159 | 204 |
| Context | 128K | 1M |
| Input $/M | $0.58 | $0.40 |
| Output $/M | $1.68 | $1.20 |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- Qwen Plus: 38.3 (#163)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1328 |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- Qwen Plus: 27.6 (#101)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| SimpleBench | 52.6% | — |
| Kagi LLM Benchmark | — | 63.3% |
| LMArena Hard Prompts | — | 1317 |
| DTBench | — | 81.1% |
| LMCA | — | 24% |

## Math

- DeepSeek-V3.2-Speciale: —
- Qwen Plus: 22.0 (#266)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 17.8% |
| LMArena Math | — | 1326 |
| MATH Level 5 | — | 65.3% |
| FrontierMath (Feb 2025 set) | — | 1.7% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Qwen Plus: 27.4 (#245)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| GPQA Diamond | — | 48.1% |
| LMArena Expert | — | 1328 |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Qwen Plus: 45.3 (#170)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| LMArena Non-English | — | 1310 |
| LMArena Chinese | — | 1347 |
| LMArena Japanese | — | 1251 |
| LMArena Russian | — | 1323 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Qwen Plus: 69.0 (#176)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| LMArena Instruction Following | — | 1303 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Qwen Plus: 40.3 (#153)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| LMArena Longer Query | — | 1325 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- Qwen Plus: 52.4 (#171)

| Benchmark | DeepSeek-V3.2-Speciale | Qwen Plus |
|---|---|---|
| LMArena Text | — | 1326 |
| LMArena Creative Writing | — | 1293 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1336 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Qwen Plus?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 36.7 on the Noometry Index.

### Which is cheaper, DeepSeek-V3.2-Speciale or Qwen Plus?

Qwen Plus is cheaper. It lists at $0.40 per million input tokens and $1.20 per million output tokens; DeepSeek-V3.2-Speciale lists at $0.58 and $1.68.

### Is DeepSeek-V3.2-Speciale or Qwen Plus better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 38.3 in the Noometry coding category.

### Which has the bigger context window?

Qwen Plus does, with 1M tokens against 128K.

### How many benchmarks do DeepSeek-V3.2-Speciale and Qwen Plus share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Qwen Plus has 20.