# DeepSeek-V3.1 vs Gemini 1.0 Pro

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 27.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-gemini-1-0-pro
- Last updated: 2026-10-10
- Shared benchmarks: 18

## Summary

- They share 18 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 8 categories and Gemini 1.0 Pro in 0 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in knowledge, where DeepSeek-V3.1 leads 43.0 to 15.5.
- The biggest single-benchmark swing is DTBench: 82.7% for DeepSeek-V3.1 and 45.9% for Gemini 1.0 Pro.
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 42.2 | 27.1 |
| Rank | 106 | 327 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Gemini 1.0 Pro: 31.6 (#270)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Coding | 1417 | 1108 |
| WeirdML | 38.4% | — |
| HumanEval+ | — | 55.5% |
| MBPP+ | — | 61.4% |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Gemini 1.0 Pro: 16.4 (#292)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Hard Prompts | 1417 | 1109 |
| DTBench | 82.7% | 45.9% |
| Epoch Capabilities Index | 139.92 | 116.97 |
| SimpleBench | 40% | — |
| Kagi LLM Benchmark | 53.2% | — |
| LMCA | 24.3% | — |
| ForecastBench | 58 | — |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Gemini 1.0 Pro: 8.7 (#315)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Math | 1420 | 1132 |
| OTIS Mock AIME 2024-2025 | — | 1.1% |
| MATH Level 5 | — | 11.2% |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Gemini 1.0 Pro: 15.5 (#286)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Expert | 1403 | 1059 |
| GPQA Diamond | — | 34% |
| Vectara Hallucination Rate | 5.5% | — |
| MMLU | — | 70% |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Gemini 1.0 Pro: 33.5 (#247)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Non-English | 1400 | 1138 |
| LMArena Chinese | 1470 | 1124 |
| LMArena French | 1447 | 1144 |
| LMArena German | 1412 | 1125 |
| LMArena Japanese | 1374 | 1023 |
| LMArena Russian | 1405 | 1186 |
| LMArena Spanish | 1429 | 1118 |
| LMArena Korean | 1337 | — |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Gemini 1.0 Pro: 57.9 (#262)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Instruction Following | 1400 | 1114 |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Gemini 1.0 Pro: 34.3 (#244)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Longer Query | 1422 | 1132 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Gemini 1.0 Pro: 36.2 (#259)

| Benchmark | DeepSeek-V3.1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Text | 1420 | 1149 |
| LMArena Creative Writing | 1401 | 1130 |
| LMArena Multi-Turn | 1408 | 1139 |
| EQ-Bench Creative Writing | 1436 | — |

## FAQ

### Is DeepSeek-V3.1 better than Gemini 1.0 Pro?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 27.1 on the Noometry Index.

### Is DeepSeek-V3.1 or Gemini 1.0 Pro better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 31.6 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and Gemini 1.0 Pro share?

18 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemini 1.0 Pro has 24.