# DeepSeek-V3.2-Speciale vs Gemma 7B

> DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 29.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-2-speciale-vs-gemma-7b
- Last updated: 2026-10-10
- Shared benchmarks: 0

## Summary

- The widest gap is in writing & preference, where DeepSeek-V3.2-Speciale leads 46.1 to 27.2.

## Snapshot

| | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 39.1 | 29.5 |
| Rank | 159 | 295 |
| Context | 128K | — |
| Input $/M | $0.58 | — |
| Output $/M | $1.68 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.2-Speciale: 39.9 (#136)
- Gemma 7B: 29.9 (#290)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| WeirdML | 46.7% | — |
| LMArena Coding | — | 1048 |
| HumanEval+ | — | 28.7% |
| MBPP+ | — | 43.4% |

## Reasoning

- DeepSeek-V3.2-Speciale: 32.1 (#65)
- Gemma 7B: 19.0 (#247)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| SimpleBench | 52.6% | — |
| LMArena Hard Prompts | — | 1042 |
| Adversarial NLI | — | 48.7% |
| BIG-Bench Hard | — | 55.1% |
| Epoch Capabilities Index | — | 111.74 |
| HellaSwag | — | 82.2% |
| PIQA | — | 81.2% |
| WinoGrande | — | 79% |

## Math

- DeepSeek-V3.2-Speciale: —
- Gemma 7B: 28.7 (#225)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Math | — | 1066 |
| GSM8K | — | 46.4% |

## Knowledge

- DeepSeek-V3.2-Speciale: —
- Gemma 7B: 26.8 (#248)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Expert | — | 1002 |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 83.2% |
| MMLU | — | 66.1% |
| OpenBookQA | — | 78.6% |
| TriviaQA | — | 72.3% |

## Multilingual

- DeepSeek-V3.2-Speciale: —
- Gemma 7B: 25.3 (#282)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Non-English | — | 999 |
| LMArena Chinese | — | 1035 |
| LMArena French | — | 1024 |
| LMArena Russian | — | 993 |

## Instruction Following

- DeepSeek-V3.2-Speciale: —
- Gemma 7B: 51.7 (#290)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Instruction Following | — | 1017 |

## Long Context

- DeepSeek-V3.2-Speciale: —
- Gemma 7B: 31.1 (#277)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Longer Query | — | 1022 |

## Writing & Preference

- DeepSeek-V3.2-Speciale: 46.1 (#217)
- Gemma 7B: 27.2 (#297)

| Benchmark | DeepSeek-V3.2-Speciale | Gemma 7B |
|---|---|---|
| LMArena Text | — | 1056 |
| LMArena Creative Writing | — | 1024 |
| EQ-Bench Creative Writing | 1276 | — |
| LMArena Multi-Turn | — | 963 |

## FAQ

### Is DeepSeek-V3.2-Speciale better than Gemma 7B?

DeepSeek-V3.2-Speciale is the stronger model overall, scoring 39.1 to 29.5 on the Noometry Index.

### Is DeepSeek-V3.2-Speciale or Gemma 7B better for coding?

DeepSeek-V3.2-Speciale scores higher on coding benchmarks: 39.9 versus 29.9 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.2-Speciale and Gemma 7B share?

0 benchmarks have published results for both models. DeepSeek-V3.2-Speciale has 3 scored results on Noometry and Gemma 7B has 27.