# DeepSeek-V3.1 vs Gemini 1.5 Pro (May 2024)

> DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-1-vs-gemini-1-5-pro
- Last updated: 2026-10-10
- Shared benchmarks: 22

## Summary

- They share 22 benchmarks with published results for both. DeepSeek-V3.1 scores higher in 7 categories and Gemini 1.5 Pro (May 2024) in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where DeepSeek-V3.1 leads 27.3 to 12.3.
- The biggest single-benchmark swing is DTBench: 82.7% for DeepSeek-V3.1 and 59% for Gemini 1.5 Pro (May 2024).
- DeepSeek-V3.1 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 42.2 | 31.9 |
| Rank | 106 | 253 |
| Context | 164K | — |
| Input $/M | $0.25 | — |
| Output $/M | $0.95 | — |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3.1: 39.8 (#140)
- Gemini 1.5 Pro (May 2024): 33.8 (#239)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| WeirdML | 38.4% | 22.2% |
| LMArena Coding | 1417 | 1294 |
| BigCodeBench Instruct | — | 43.8% |
| BigCodeBench Complete | — | 57.5% |
| CadEval | — | 34% |
| HumanEval+ | — | 79.3% |
| MBPP+ | — | 74.6% |

## Agentic & Tool Use

- DeepSeek-V3.1: —
- Gemini 1.5 Pro (May 2024): 17.8 (#137)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| TheAgentCompany | — | 3.4% |
| Cybench | — | 7.5% |
| BALROG | — | 21% |

## Reasoning

- DeepSeek-V3.1: 27.3 (#109)
- Gemini 1.5 Pro (May 2024): 12.3 (#332)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| SimpleBench | 40% | 27.1% |
| LMArena Hard Prompts | 1417 | 1296 |
| DTBench | 82.7% | 59% |
| Epoch Capabilities Index | 139.92 | 131.73 |
| ForecastBench | 58 | 58.4 |
| ARC-AGI-2 | — | 0.8% |
| Kagi LLM Benchmark | 53.2% | — |
| LMCA | 24.3% | — |
| BIG-Bench Hard | — | 89.2% |

## Math

- DeepSeek-V3.1: 36.1 (#125)
- Gemini 1.5 Pro (May 2024): 24.4 (#260)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Math | 1420 | 1315 |
| OTIS Mock AIME 2024-2025 | — | 23.1% |
| Omni-MATH | — | 36.4% |
| MATH Level 5 | — | 70.4% |

## Knowledge

- DeepSeek-V3.1: 43.0 (#86)
- Gemini 1.5 Pro (May 2024): 29.3 (#228)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Expert | 1403 | 1279 |
| GPQA Diamond | — | 57.2% |
| Humanity's Last Exam | — | 4.6% |
| MMLU-Pro | — | 73.7% |
| Confabulations | — | 13.5% |
| Vectara Hallucination Rate | 5.5% | — |
| GPQA (HELM) | — | 53.4% |
| MMLU | — | 86.9% |

## Multimodal

- DeepSeek-V3.1: —
- Gemini 1.5 Pro (May 2024): 36.2 (#72)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Vision | — | 1161 |
| Video-MME | — | 75% |

## Multilingual

- DeepSeek-V3.1: 51.8 (#100)
- Gemini 1.5 Pro (May 2024): 45.5 (#169)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Non-English | 1400 | 1312 |
| LMArena Chinese | 1470 | 1331 |
| LMArena French | 1447 | 1301 |
| LMArena German | 1412 | 1286 |
| LMArena Japanese | 1374 | 1292 |
| LMArena Korean | 1337 | 1298 |
| LMArena Russian | 1405 | 1320 |
| LMArena Spanish | 1429 | 1310 |

## Instruction Following

- DeepSeek-V3.1: 74.1 (#105)
- Gemini 1.5 Pro (May 2024): 68.8 (#180)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Instruction Following | 1400 | 1297 |
| IFEval | — | 83.7% |

## Long Context

- DeepSeek-V3.1: 36.3 (#227)
- Gemini 1.5 Pro (May 2024): 39.7 (#164)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Longer Query | 1422 | 1308 |
| Fiction.LiveBench | 52.8% | — |

## Writing & Preference

- DeepSeek-V3.1: 60.5 (#93)
- Gemini 1.5 Pro (May 2024): 52.5 (#167)

| Benchmark | DeepSeek-V3.1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Text | 1420 | 1319 |
| LMArena Creative Writing | 1401 | 1333 |
| LMArena Multi-Turn | 1408 | 1296 |
| EQ-Bench Creative Writing | 1436 | — |
| WildBench | — | 81.3% |

## FAQ

### Is DeepSeek-V3.1 better than Gemini 1.5 Pro (May 2024)?

DeepSeek-V3.1 is the stronger model overall, scoring 42.2 to 31.9 on the Noometry Index.

### Is DeepSeek-V3.1 or Gemini 1.5 Pro (May 2024) better for coding?

DeepSeek-V3.1 scores higher on coding benchmarks: 39.8 versus 33.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-V3.1 and Gemini 1.5 Pro (May 2024) share?

22 benchmarks have published results for both models. DeepSeek-V3.1 has 27 scored results on Noometry and Gemini 1.5 Pro (May 2024) has 45.