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

> DeepSeek-V3 is the stronger model overall, scoring 39.2 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-v3-vs-gemini-1-5-pro
- Last updated: 2026-10-10
- Shared benchmarks: 37

## Summary

- They share 37 benchmarks with published results for both. DeepSeek-V3 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 knowledge, where DeepSeek-V3 leads 37.5 to 29.3.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 37.8% for DeepSeek-V3 and 23.1% for Gemini 1.5 Pro (May 2024).
- DeepSeek-V3 has downloadable open weights; the other is API-only.

## Snapshot

| | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 39.2 | 31.9 |
| Rank | 157 | 253 |
| Context | 164K | — |
| Input $/M | $0.24 | — |
| Output $/M | $0.90 | — |
| Weights | Open | Proprietary |

## Coding

- DeepSeek-V3: 41.9 (#99)
- Gemini 1.5 Pro (May 2024): 33.8 (#239)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| WeirdML | 36.1% | 22.2% |
| BigCodeBench Instruct | 50% | 43.8% |
| LMArena Coding | 1368 | 1294 |
| BigCodeBench Complete | 62.2% | 57.5% |
| HumanEval+ | 86.6% | 79.3% |
| MBPP+ | 73% | 74.6% |
| Aider Polyglot | 55.1% | — |
| SciCode | 35.8% | — |
| LiveBench Coding | 70.9% | — |
| CadEval | — | 34% |

## Agentic & Tool Use

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

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| TheAgentCompany | — | 3.4% |
| Cybench | — | 7.5% |
| BALROG | — | 21% |
| METR Time Horizons | 49.6% | — |

## Reasoning

- DeepSeek-V3: 20.0 (#226)
- Gemini 1.5 Pro (May 2024): 12.3 (#332)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| SimpleBench | 27.2% | 27.1% |
| LMArena Hard Prompts | 1365 | 1296 |
| DTBench | 64.8% | 59% |
| BIG-Bench Hard | 87.5% | 89.2% |
| Epoch Capabilities Index | 135.95 | 131.73 |
| ForecastBench | 59.1 | 58.4 |
| ARC-AGI-2 | — | 0.8% |
| Kagi LLM Benchmark | 52.3% | — |
| CritPt | 0% | — |
| LiveBench Reasoning | 65.8% | — |
| LiveBench Data Analysis | 60.9% | — |
| LMCA | 15.5% | — |
| HellaSwag | 88.9% | — |
| LiveBench | 66.9% | — |
| PIQA | 84.7% | — |
| WinoGrande | 85.2% | — |

## Math

- DeepSeek-V3: 30.4 (#208)
- Gemini 1.5 Pro (May 2024): 24.4 (#260)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 37.8% | 23.1% |
| Omni-MATH | 40.3% | 36.4% |
| LMArena Math | 1373 | 1315 |
| MATH Level 5 | 75.5% | 70.4% |
| LiveBench Math | 73.5% | — |
| FrontierMath (Feb 2025 set) | 1.7% | — |

## Knowledge

- DeepSeek-V3: 37.5 (#147)
- Gemini 1.5 Pro (May 2024): 29.3 (#228)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| GPQA Diamond | 67.6% | 57.2% |
| MMLU-Pro | 72.3% | 73.7% |
| Confabulations | 26.1% | 13.5% |
| GPQA (HELM) | 53.8% | 53.4% |
| LMArena Expert | 1352 | 1279 |
| MMLU | 87.2% | 86.9% |
| Humanity's Last Exam | — | 4.6% |
| Vectara Hallucination Rate | 6.1% | — |
| ARC (AI2) Challenge | 95.3% | — |
| TriviaQA | 82.9% | — |

## Multimodal

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

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

## Multilingual

- DeepSeek-V3: 48.8 (#138)
- Gemini 1.5 Pro (May 2024): 45.5 (#169)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Non-English | 1358 | 1312 |
| LMArena Chinese | 1390 | 1331 |
| LMArena French | 1386 | 1301 |
| LMArena German | 1374 | 1286 |
| LMArena Japanese | 1333 | 1292 |
| LMArena Korean | 1321 | 1298 |
| LMArena Russian | 1372 | 1320 |
| LMArena Spanish | 1358 | 1310 |

## Instruction Following

- DeepSeek-V3: 73.0 (#125)
- Gemini 1.5 Pro (May 2024): 68.8 (#180)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| IFEval | 83.2% | 83.7% |
| LMArena Instruction Following | 1345 | 1297 |
| LiveBench Instruction Following | 81.5% | — |

## Long Context

- DeepSeek-V3: 34.0 (#248)
- Gemini 1.5 Pro (May 2024): 39.7 (#164)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Longer Query | 1353 | 1308 |
| Fiction.LiveBench | 50% | — |

## Writing & Preference

- DeepSeek-V3: 57.6 (#124)
- Gemini 1.5 Pro (May 2024): 52.5 (#167)

| Benchmark | DeepSeek-V3 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Text | 1375 | 1319 |
| LMArena Creative Writing | 1364 | 1333 |
| WildBench | 83% | 81.3% |
| LMArena Multi-Turn | 1389 | 1296 |
| Short-Story Creative Writing | 77% | — |
| EQ-Bench Creative Writing | 1472 | — |
| LiveBench Language | 49.1% | — |

## FAQ

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

DeepSeek-V3 is the stronger model overall, scoring 39.2 to 31.9 on the Noometry Index.

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

DeepSeek-V3 scores higher on coding benchmarks: 41.9 versus 33.8 in the Noometry coding category.

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

37 benchmarks have published results for both models. DeepSeek-V3 has 60 scored results on Noometry and Gemini 1.5 Pro (May 2024) has 45.