Model comparison
DeepSeek-V3.2-Speciale vs Qwen1.5-14B
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 32.7 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
Alibaba (Qwen)Summary
- The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.0 to 33.6.
Side by side
| DeepSeek-V3.2-Speciale | Qwen1.5-14B | |
|---|---|---|
| Provider | DeepSeek | Alibaba (Qwen) |
| Noometry Index | 39.7 | 32.7 |
| Released | 2025-12-01 | 2024-02-04 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 17 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Qwen1.5-14B: 33.1 (#263)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1138 |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Qwen1.5-14B: 21.4 (#223)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1113 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Qwen1.5-14B: 32.4 (#215)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Math | — | 1125 |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Qwen1.5-14B: 29.8 (#232)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Expert | — | 1094 |
| MMLU | — | 68.6% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Qwen1.5-14B: 30.7 (#262)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Non-English | — | 1095 |
| LMArena Chinese | — | 1147 |
| LMArena French | — | 1116 |
| LMArena German | — | 1043 |
| LMArena Japanese | — | 1019 |
| LMArena Russian | — | 1046 |
| LMArena Spanish | — | 1085 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Qwen1.5-14B: 56.8 (#271)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Instruction Following | — | 1102 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Qwen1.5-14B: 33.7 (#257)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Longer Query | — | 1113 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Qwen1.5-14B: 33.6 (#276)
| Benchmark | DeepSeek-V3.2-Speciale | Qwen1.5-14B |
|---|---|---|
| LMArena Text | — | 1128 |
| LMArena Creative Writing | — | 1091 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1110 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Qwen1.5-14B?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 32.7 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Qwen1.5-14B better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 33.1 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Qwen1.5-14B share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Qwen1.5-14B has 17.