# DeepSeek-R1 vs Gemini 1.5 Pro (May 2024)

> DeepSeek-R1 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-r1-vs-gemini-1-5-pro
- Last updated: 2026-10-10
- Shared benchmarks: 32

## Summary

- They share 32 benchmarks with published results for both. DeepSeek-R1 scores higher in 9 categories and Gemini 1.5 Pro (May 2024) in 0 categories; 9 gaps are clear of the uncertainty.
- The widest gap is in math, where DeepSeek-R1 leads 42.0 to 24.4.
- The biggest single-benchmark swing is OTIS Mock AIME 2024-2025: 66.4% for DeepSeek-R1 and 23.1% for Gemini 1.5 Pro (May 2024).

## Snapshot

| | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 42.0 | 31.9 |
| Rank | 110 | 253 |
| Context | 164K | — |
| Input $/M | $0.50 | — |
| Output $/M | $2.15 | — |
| Weights | Proprietary | Proprietary |

## Coding

- DeepSeek-R1: 45.9 (#63)
- Gemini 1.5 Pro (May 2024): 33.8 (#239)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| WeirdML | 41.6% | 22.2% |
| LMArena Coding | 1427 | 1294 |
| Aider Polyglot | 71.4% | — |
| SciCode | 35.7% | — |
| BigCodeBench Instruct | — | 43.8% |
| LiveBench Coding | 66.7% | — |
| BigCodeBench Complete | — | 57.5% |
| CadEval | — | 34% |
| ALE-Bench | 804.12 | — |
| AlgoTune | 1.7 | — |
| HumanEval+ | — | 79.3% |
| MBPP+ | — | 74.6% |

## Agentic & Tool Use

- DeepSeek-R1: 30.4 (#68)
- Gemini 1.5 Pro (May 2024): 17.8 (#137)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| BALROG | 34.9% | 21% |
| TheAgentCompany | — | 3.4% |
| Cybench | — | 7.5% |
| DeepResearch Bench | 35.1% | — |
| METR Time Horizons | 53.8% | — |

## Reasoning

- DeepSeek-R1: 18.7 (#253)
- Gemini 1.5 Pro (May 2024): 12.3 (#332)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| ARC-AGI-2 | 1.3% | 0.8% |
| SimpleBench | 40.8% | 27.1% |
| LMArena Hard Prompts | 1415 | 1296 |
| Epoch Capabilities Index | 141.3 | 131.73 |
| ForecastBench | 60 | 58.4 |
| Kagi LLM Benchmark | 69.4% | — |
| ARC-AGI-1 | 21.2% | — |
| CritPt | 1.1% | — |
| LiveBench Reasoning | 83.2% | — |
| DTBench | — | 59% |
| LiveBench Data Analysis | 69.8% | — |
| BIG-Bench Hard | — | 89.2% |
| LiveBench | 71.6% | — |

## Math

- DeepSeek-R1: 42.0 (#70)
- Gemini 1.5 Pro (May 2024): 24.4 (#260)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | 23.1% |
| Omni-MATH | 42.4% | 36.4% |
| LMArena Math | 1401 | 1315 |
| MATH Level 5 | 96.6% | 70.4% |
| LiveBench Math | 80.7% | — |

## Knowledge

- DeepSeek-R1: 44.3 (#81)
- Gemini 1.5 Pro (May 2024): 29.3 (#228)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| GPQA Diamond | 76.3% | 57.2% |
| MMLU-Pro | 79.3% | 73.7% |
| Confabulations | 12.7% | 13.5% |
| GPQA (HELM) | 66.6% | 53.4% |
| LMArena Expert | 1394 | 1279 |
| Humanity's Last Exam | — | 4.6% |
| Vectara Hallucination Rate | 11.3% | — |
| MMLU | — | 86.9% |

## Multimodal

- DeepSeek-R1: —
- Gemini 1.5 Pro (May 2024): 36.2 (#72)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Vision | — | 1161 |
| Video-MME | — | 75% |

## Multilingual

- DeepSeek-R1: 52.6 (#80)
- Gemini 1.5 Pro (May 2024): 45.5 (#169)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Non-English | 1412 | 1312 |
| LMArena Chinese | 1443 | 1331 |
| LMArena French | 1415 | 1301 |
| LMArena German | 1405 | 1286 |
| LMArena Japanese | 1394 | 1292 |
| LMArena Korean | 1359 | 1298 |
| LMArena Russian | 1423 | 1320 |
| LMArena Spanish | 1410 | 1310 |

## Instruction Following

- DeepSeek-R1: 72.2 (#138)
- Gemini 1.5 Pro (May 2024): 68.8 (#180)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| IFEval | 78.4% | 83.7% |
| LMArena Instruction Following | 1382 | 1297 |
| LiveBench Instruction Following | 80.5% | — |

## Long Context

- DeepSeek-R1: 45.4 (#36)
- Gemini 1.5 Pro (May 2024): 39.7 (#164)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Longer Query | 1391 | 1308 |
| Fiction.LiveBench | 75% | — |

## Writing & Preference

- DeepSeek-R1: 61.5 (#84)
- Gemini 1.5 Pro (May 2024): 52.5 (#167)

| Benchmark | DeepSeek-R1 | Gemini 1.5 Pro (May 2024) |
|---|---|---|
| LMArena Text | 1428 | 1319 |
| LMArena Creative Writing | 1406 | 1333 |
| WildBench | 82.8% | 81.3% |
| LMArena Multi-Turn | 1404 | 1296 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1500 | — |
| LiveBench Language | 48.5% | — |

## FAQ

### Is DeepSeek-R1 better than Gemini 1.5 Pro (May 2024)?

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 31.9 on the Noometry Index.

### Is DeepSeek-R1 or Gemini 1.5 Pro (May 2024) better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 33.8 in the Noometry coding category.

### How many benchmarks do DeepSeek-R1 and Gemini 1.5 Pro (May 2024) share?

32 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Gemini 1.5 Pro (May 2024) has 45.