Model comparison
DeepSeek-V3.2-Speciale vs Qwen Max
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 34.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in coding, where DeepSeek-V3.2-Speciale leads 40.4 to 30.7.
- DeepSeek-V3.2-Speciale is cheaper at $0.58 / $1.68 per million input/output tokens, against $1.60 / $6.40 for Qwen Max.
- DeepSeek-V3.2-Speciale accepts more context: 128K tokens versus 33K.
- DeepSeek-V3.2-Speciale has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-V3.2-Speciale | Qwen Max | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 39.7 | 34.7 |
| Released | 2025-12-01 | 2024-04-03 |
| Weights | Open | Proprietary |
| Context window | 128K | 33K |
| Max output | 128K | 8K |
| Input $ / M tokens | $0.58 | $1.60 |
| Output $ / M tokens | $1.68 | $6.40 |
| Results tracked | 3 | 23 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Qwen Max: 30.7 (#292)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| Aider Polyglot | — | 21.8% |
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1288 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Qwen Max: 25.1 (#151)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1269 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Qwen Max: 22.3 (#276)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 16.1% |
| LMArena Math | — | 1275 |
| MATH Level 5 | — | 67.2% |
| FrontierMath (Feb 2025 set) | — | 1% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Qwen Max: 30.3 (#228)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| GPQA Diamond | — | 56.1% |
| LMArena Expert | — | 1248 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Qwen Max: 41.8 (#202)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| LMArena Non-English | — | 1263 |
| LMArena Chinese | — | 1254 |
| LMArena French | — | 1330 |
| LMArena German | — | 1254 |
| LMArena Japanese | — | 1205 |
| LMArena Korean | — | 1142 |
| LMArena Russian | — | 1274 |
| LMArena Spanish | — | 1290 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Qwen Max: 66.5 (#208)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| LMArena Instruction Following | — | 1262 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Qwen Max: 39.4 (#180)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| Fiction.LiveBench | — | 66.7% |
| LMArena Longer Query | — | 1288 |
Writing & Preference Qwen Max leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Qwen Max: 47.8 (#205)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen Max |
|---|---|---|
| LMArena Text | — | 1282 |
| LMArena Creative Writing | — | 1248 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1277 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Qwen Max?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 34.7 on the Noometry Index.
Which is cheaper, DeepSeek-V3.2-Speciale or Qwen Max?
DeepSeek-V3.2-Speciale is cheaper. It lists at $0.58 per million input tokens and $1.68 per million output tokens; Qwen Max lists at $1.60 and $6.40.
Is DeepSeek-V3.2-Speciale or Qwen Max better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 30.7 in the Noometry coding category.
Which has the bigger context window?
DeepSeek-V3.2-Speciale does, with 128K tokens against 33K.
How many benchmarks do DeepSeek-V3.2-Speciale and Qwen Max share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Qwen Max has 23.