Model comparison
DeepSeek-V3.2-Speciale vs Yi-1.5-34B
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 30.2 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeekSummary
- The widest gap is in reasoning, where DeepSeek-V3.2-Speciale leads 32.1 to 21.5.
Side by side
| DeepSeek-V3.2-Speciale | Yi-1.5-34B | |
|---|---|---|
| Provider | DeepSeek | 01.AI |
| Noometry Index | 39.1 | 30.2 |
| Released | 2025-12-01 | 2024-05-13 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 21 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 39.9 (#136), Yi-1.5-34B: 31.9 (#267)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| WeirdML | 46.7% | — |
| BigCodeBench Instruct | — | 33.9% |
| LMArena Coding | — | 1169 |
| BigCodeBench Complete | — | 43.8% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.1 (#65), Yi-1.5-34B: 21.5 (#195)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1160 |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Yi-1.5-34B: 25.3 (#248)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| LMArena Math | — | 1182 |
| MATH Level 5 | — | 25.5% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Yi-1.5-34B: 14.8 (#290)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| GPQA Diamond | — | 32% |
| LMArena Expert | — | 1144 |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Yi-1.5-34B: 32.5 (#251)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| LMArena Non-English | — | 1121 |
| LMArena Chinese | — | 1213 |
| LMArena French | — | 1155 |
| LMArena German | — | 1111 |
| LMArena Japanese | — | 1021 |
| LMArena Korean | — | 1005 |
| LMArena Russian | — | 1091 |
| LMArena Spanish | — | 1120 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Yi-1.5-34B: 59.4 (#252)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| LMArena Instruction Following | — | 1139 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Yi-1.5-34B: 34.6 (#243)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| LMArena Longer Query | — | 1144 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.1 (#217), Yi-1.5-34B: 37.6 (#252)
| Benchmark | DeepSeek-V3.2-Speciale | Yi-1.5-34B |
|---|---|---|
| LMArena Text | — | 1173 |
| LMArena Creative Writing | — | 1135 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 1153 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Yi-1.5-34B?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 30.2 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Yi-1.5-34B better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 31.9 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Yi-1.5-34B share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Yi-1.5-34B has 21.