# DeepSeek-R1 vs Gemini 1.0 Pro

> DeepSeek-R1 is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index.

- Canonical page: https://noometry.com/compare/deepseek-r1-vs-gemini-1-0-pro
- Last updated: 2026-10-10
- Shared benchmarks: 20

## Summary

- They share 20 benchmarks with published results for both. DeepSeek-R1 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 math, where DeepSeek-R1 leads 42.0 to 8.7.
- The biggest single-benchmark swing is MATH Level 5: 96.6% for DeepSeek-R1 and 11.2% for Gemini 1.0 Pro.

## Snapshot

| | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| Provider | DeepSeek | Google |
| Noometry Index | 42.0 | 27.1 |
| Rank | 110 | 327 |
| Context | 164K | — |
| Input $/M | $0.50 | — |
| Output $/M | $2.15 | — |
| Weights | Proprietary | Proprietary |

## Coding

- DeepSeek-R1: 45.9 (#63)
- Gemini 1.0 Pro: 31.6 (#270)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Coding | 1427 | 1108 |
| Aider Polyglot | 71.4% | — |
| SciCode | 35.7% | — |
| WeirdML | 41.6% | — |
| LiveBench Coding | 66.7% | — |
| ALE-Bench | 804.12 | — |
| AlgoTune | 1.7 | — |
| HumanEval+ | — | 55.5% |
| MBPP+ | — | 61.4% |

## Agentic & Tool Use

- DeepSeek-R1: 30.4 (#68)
- Gemini 1.0 Pro: —

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |

## Reasoning

- DeepSeek-R1: 18.7 (#253)
- Gemini 1.0 Pro: 16.4 (#292)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Hard Prompts | 1415 | 1109 |
| Epoch Capabilities Index | 141.3 | 116.97 |
| ARC-AGI-2 | 1.3% | — |
| SimpleBench | 40.8% | — |
| Kagi LLM Benchmark | 69.4% | — |
| ARC-AGI-1 | 21.2% | — |
| CritPt | 1.1% | — |
| LiveBench Reasoning | 83.2% | — |
| DTBench | — | 45.9% |
| LiveBench Data Analysis | 69.8% | — |
| ForecastBench | 60 | — |
| LiveBench | 71.6% | — |

## Math

- DeepSeek-R1: 42.0 (#70)
- Gemini 1.0 Pro: 8.7 (#315)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| OTIS Mock AIME 2024-2025 | 66.4% | 1.1% |
| LMArena Math | 1401 | 1132 |
| MATH Level 5 | 96.6% | 11.2% |
| Omni-MATH | 42.4% | — |
| LiveBench Math | 80.7% | — |

## Knowledge

- DeepSeek-R1: 44.3 (#81)
- Gemini 1.0 Pro: 15.5 (#286)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| GPQA Diamond | 76.3% | 34% |
| LMArena Expert | 1394 | 1059 |
| MMLU-Pro | 79.3% | — |
| Confabulations | 12.7% | — |
| Vectara Hallucination Rate | 11.3% | — |
| GPQA (HELM) | 66.6% | — |
| MMLU | — | 70% |

## Multilingual

- DeepSeek-R1: 52.6 (#80)
- Gemini 1.0 Pro: 33.5 (#247)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Non-English | 1412 | 1138 |
| LMArena Chinese | 1443 | 1124 |
| LMArena French | 1415 | 1144 |
| LMArena German | 1405 | 1125 |
| LMArena Japanese | 1394 | 1023 |
| LMArena Russian | 1423 | 1186 |
| LMArena Spanish | 1410 | 1118 |
| LMArena Korean | 1359 | — |

## Instruction Following

- DeepSeek-R1: 72.2 (#138)
- Gemini 1.0 Pro: 57.9 (#262)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Instruction Following | 1382 | 1114 |
| LiveBench Instruction Following | 80.5% | — |
| IFEval | 78.4% | — |

## Long Context

- DeepSeek-R1: 45.4 (#36)
- Gemini 1.0 Pro: 34.3 (#244)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Longer Query | 1391 | 1132 |
| Fiction.LiveBench | 75% | — |

## Writing & Preference

- DeepSeek-R1: 61.5 (#84)
- Gemini 1.0 Pro: 36.2 (#259)

| Benchmark | DeepSeek-R1 | Gemini 1.0 Pro |
|---|---|---|
| LMArena Text | 1428 | 1149 |
| LMArena Creative Writing | 1406 | 1130 |
| LMArena Multi-Turn | 1404 | 1139 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1500 | — |
| WildBench | 82.8% | — |
| LiveBench Language | 48.5% | — |

## FAQ

### Is DeepSeek-R1 better than Gemini 1.0 Pro?

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 27.1 on the Noometry Index.

### Is DeepSeek-R1 or Gemini 1.0 Pro better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 31.6 in the Noometry coding category.

### How many benchmarks do DeepSeek-R1 and Gemini 1.0 Pro share?

20 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Gemini 1.0 Pro has 24.