# DeepSeek-V3.1 vs Gemma 7B

> DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 30.0 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-gemma-7b
- Last updated: 2026-10-11
- Shared benchmarks: 14

## Summary

- They share 14 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Gemma 7B in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-V3.1 leads 60.3 to 27.1.

## Snapshot

| | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 42.8 | 30.0 |
| Rank | 108 | 299 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Open |

## Coding

- DeepSeek-V3.1: 40.3 (#144)
- Gemma 7B: 30.5 (#294)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Coding | 1417 | 1048 |
| WeirdML | 38.4% | — |
| HumanEval+ | — | 28.7% |
| MBPP+ | — | 43.4% |

## Reasoning

- DeepSeek-V3.1: 27.9 (#110)
- Gemma 7B: 19.9 (#249)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1042 |
| Epoch Capabilities Index | 139.92 | 111.99 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| DTBench | 82.7% | — |
| LMCA | 24.3% | — |
| Adversarial NLI | — | 48.7% |
| BIG-Bench Hard | — | 55.1% |
| ForecastBench | 58 | — |
| HellaSwag | — | 82.2% |
| PIQA | — | 81.2% |
| WinoGrande | — | 79% |

## Math

- DeepSeek-V3.1: 38.9 (#122)
- Gemma 7B: 31.2 (#228)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Math | 1420 | 1066 |
| GSM8K | — | 46.4% |

## Knowledge

- DeepSeek-V3.1: 43.7 (#90)
- Gemma 7B: 27.3 (#252)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Expert | 1405 | 1001 |
| Vectara Hallucination Rate | 5.5% | — |
| ARC (AI2) Challenge | — | 78.3% |
| BoolQ | — | 83.2% |
| MMLU | — | 66.1% |
| OpenBookQA | — | 78.6% |
| TriviaQA | — | 72.3% |

## Multilingual

- DeepSeek-V3.1: 51.6 (#106)
- Gemma 7B: 25.1 (#287)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Non-English | 1400 | 999 |
| LMArena Chinese | 1469 | 1035 |
| LMArena French | 1447 | 1025 |
| LMArena Russian | 1405 | 993 |
| LMArena German | 1411 | — |
| LMArena Japanese | 1378 | — |
| LMArena Korean | 1337 | — |
| LMArena Spanish | 1431 | — |

## Instruction Following

- DeepSeek-V3.1: 73.9 (#110)
- Gemma 7B: 51.5 (#295)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Instruction Following | 1400 | 1017 |

## Long Context

- DeepSeek-V3.1: 36.3 (#232)
- Gemma 7B: 31.1 (#282)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Longer Query | 1422 | 1022 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.3 (#98)
- Gemma 7B: 27.1 (#302)

| Benchmark | DeepSeek-V3.1 | Gemma 7B |
|---|---|---|
| LMArena Text | 1420 | 1056 |
| LMArena Creative Writing | 1401 | 1024 |
| LMArena Multi-Turn | 1408 | 963 |
| EQ-Bench Creative Writing | 1436 | — |

## FAQ

### Is DeepSeek-V3.1 better than Gemma 7B?

DeepSeek-V3.1 is the stronger model overall, scoring 42.8 to 30.0 on the Noometry Index.

### Is DeepSeek-V3.1 or Gemma 7B better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 40.3 versus 30.5 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and Gemma 7B share?

14 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemma 7B has 27.