Model comparison
DeepSeek-V3.2-Speciale vs Gemma 2B
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.6 on the Noometry Index.
Last verified . 0 shared benchmarks.
DeepSeek
GoogleSummary
- The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.0 to 24.0.
Side by side
| DeepSeek-V3.2-Speciale | Gemma 2B | |
|---|---|---|
| Provider | DeepSeek | |
| Noometry Index | 39.7 | 29.6 |
| Released | 2025-12-01 | 2024-02-21 |
| Weights | Open | Open |
| Context window | 128K | — |
| Max output | 128K | — |
| Input $ / M tokens | $0.58 | — |
| Output $ / M tokens | $1.68 | — |
| Results tracked | 3 | 23 |
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Category by category
Coding DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 40.4 (#140), Gemma 2B: 29.4 (#305)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1010 |
| HumanEval+ | — | 20.7% |
| MBPP+ | — | 34.1% |
Reasoning DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 32.9 (#73), Gemma 2B: 18.8 (#275)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 989 |
| BIG-Bench Hard | — | 35.2% |
| Epoch Capabilities Index | — | 94.2 |
| HellaSwag | — | 71.4% |
| PIQA | — | 77.3% |
| WinoGrande | — | 65.4% |
Math Not comparable
DeepSeek-V3.2-Speciale: —, Gemma 2B: 30.0 (#239)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| LMArena Math | — | 1009 |
| GSM8K | — | 17.7% |
Knowledge Not comparable
DeepSeek-V3.2-Speciale: —, Gemma 2B: —
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| ARC (AI2) Challenge | — | 42.1% |
| BoolQ | — | 69.4% |
| MMLU | — | 42.3% |
| TriviaQA | — | 53.2% |
Multilingual Not comparable
DeepSeek-V3.2-Speciale: —, Gemma 2B: 23.0 (#294)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| LMArena Non-English | — | 958 |
| LMArena Chinese | — | 986 |
| LMArena Russian | — | 937 |
Instruction Following Not comparable
DeepSeek-V3.2-Speciale: —, Gemma 2B: 48.5 (#302)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| LMArena Instruction Following | — | 970 |
Long Context Not comparable
DeepSeek-V3.2-Speciale: —, Gemma 2B: 29.9 (#291)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| LMArena Longer Query | — | 981 |
Writing & Preference DeepSeek-V3.2-Speciale leads
DeepSeek-V3.2-Speciale: 46.0 (#222), Gemma 2B: 24.0 (#308)
| Benchmark | DeepSeek-V3.2-Speciale | Gemma 2B |
|---|---|---|
| LMArena Text | — | 1002 |
| LMArena Creative Writing | — | 987 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 945 |
Frequently asked questions
Is DeepSeek-V3.2-Speciale better than Gemma 2B?
DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.7 to 29.6 on the Noometry Index.
Is DeepSeek-V3.2-Speciale or Gemma 2B better for coding?
DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 40.4 versus 29.4 in the Noometry coding category.
How many benchmarks do DeepSeek-V3.2-Speciale and Gemma 2B share?
0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemma 2B has 23.