# Amazon Nova Pro vs DeepSeek-R1

> DeepSeek-R1 is the stronger model overall, scoring 42.0 to 30.5 on the Noometry Index.

- Canonical page: https://noometry.com/compare/amazon-nova-pro-vs-deepseek-r1
- Last updated: 2026-10-10
- Shared benchmarks: 33

## Summary

- They share 33 benchmarks with published results for both. Amazon Nova Pro scores higher in 1 category and DeepSeek-R1 in 8 categories; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-R1 leads 61.5 to 44.1.
- The biggest single-benchmark swing is LiveBench Reasoning: 32.6% for Amazon Nova Pro and 83.2% for DeepSeek-R1.
- DeepSeek-R1 is cheaper at $0.50 / $2.15 per million input/output tokens, against $0.80 / $3.20 for Amazon Nova Pro.
- Amazon Nova Pro accepts more context: 300K tokens versus 164K.

## Snapshot

| | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 30.5 | 42.0 |
| Rank | 278 | 110 |
| Context | 300K | 164K |
| Input $/M | $0.80 | $0.50 |
| Output $/M | $3.20 | $2.15 |
| Weights | Proprietary | Proprietary |

## Coding

- Amazon Nova Pro: 34.6 (#224)
- DeepSeek-R1: 45.9 (#63)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LiveBench Coding | 38.1% | 66.7% |
| LMArena Coding | 1270 | 1427 |
| Aider Polyglot | — | 71.4% |
| SciCode | — | 35.7% |
| WeirdML | — | 41.6% |
| ALE-Bench | — | 804.12 |
| AlgoTune | — | 1.7 |

## Agentic & Tool Use

- Amazon Nova Pro: 16.6 (#139)
- DeepSeek-R1: 30.4 (#68)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| Berkeley Function Calling Leaderboard | 25% | — |
| TheAgentCompany | 1.7% | — |
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |

## Reasoning

- Amazon Nova Pro: 19.2 (#240)
- DeepSeek-R1: 18.7 (#253)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LiveBench Reasoning | 32.6% | 83.2% |
| LMArena Hard Prompts | 1246 | 1415 |
| LiveBench Data Analysis | 48.3% | 69.8% |
| Epoch Capabilities Index | 123.75 | 141.3 |
| LiveBench | 43.5% | 71.6% |
| ARC-AGI-2 | — | 1.3% |
| SimpleBench | — | 40.8% |
| Kagi LLM Benchmark | — | 69.4% |
| ARC-AGI-1 | — | 21.2% |
| CritPt | — | 1.1% |
| ForecastBench | — | 60 |

## Math

- Amazon Nova Pro: 26.4 (#240)
- DeepSeek-R1: 42.0 (#70)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| Omni-MATH | 24.2% | 42.4% |
| LiveBench Math | 38% | 80.7% |
| LMArena Math | 1252 | 1401 |
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| MATH Level 5 | — | 96.6% |

## Knowledge

- Amazon Nova Pro: 27.1 (#246)
- DeepSeek-R1: 44.3 (#81)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| MMLU-Pro | 67.3% | 79.3% |
| Confabulations | 30.1% | 12.7% |
| Vectara Hallucination Rate | 5.1% | 11.3% |
| GPQA (HELM) | 44.6% | 66.6% |
| LMArena Expert | 1211 | 1394 |
| GPQA Diamond | — | 76.3% |
| Humanity's Last Exam | 4.4% | — |
| MMLU | 82% | — |

## Multimodal

- Amazon Nova Pro: 24.5 (#121)
- DeepSeek-R1: —

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LMArena Vision | 980 | — |

## Multilingual

- Amazon Nova Pro: 39.9 (#218)
- DeepSeek-R1: 52.6 (#80)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1234 | 1412 |
| LMArena Chinese | 1244 | 1443 |
| LMArena French | 1270 | 1415 |
| LMArena German | 1243 | 1405 |
| LMArena Japanese | 1200 | 1394 |
| LMArena Korean | 1203 | 1359 |
| LMArena Russian | 1240 | 1423 |
| LMArena Spanish | 1182 | 1410 |

## Instruction Following

- Amazon Nova Pro: 65.1 (#221)
- DeepSeek-R1: 72.2 (#138)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LiveBench Instruction Following | 67.1% | 80.5% |
| IFEval | 81.5% | 78.4% |
| LMArena Instruction Following | 1235 | 1382 |

## Long Context

- Amazon Nova Pro: 38.1 (#199)
- DeepSeek-R1: 45.4 (#36)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1255 | 1391 |
| Fiction.LiveBench | — | 75% |

## Writing & Preference

- Amazon Nova Pro: 44.1 (#221)
- DeepSeek-R1: 61.5 (#84)

| Benchmark | Amazon Nova Pro | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1259 | 1428 |
| LMArena Creative Writing | 1212 | 1406 |
| Short-Story Creative Writing | 60.5% | 83% |
| WildBench | 77.7% | 82.8% |
| LMArena Multi-Turn | 1245 | 1404 |
| LiveBench Language | 37% | 48.5% |
| EQ-Bench Creative Writing | — | 1500 |

## FAQ

### Is Amazon Nova Pro better than DeepSeek-R1?

DeepSeek-R1 is the stronger model overall, scoring 42.0 to 30.5 on the Noometry Index.

### Which is cheaper, Amazon Nova Pro or DeepSeek-R1?

DeepSeek-R1 is cheaper. It lists at $0.50 per million input tokens and $2.15 per million output tokens; Amazon Nova Pro lists at $0.80 and $3.20.

### Is Amazon Nova Pro or DeepSeek-R1 better for coding?

DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 34.6 in the Noometry coding category.

### Which has the bigger context window?

Amazon Nova Pro does, with 300K tokens against 164K.

### How many benchmarks do Amazon Nova Pro and DeepSeek-R1 share?

33 benchmarks have published results for both models. Amazon Nova Pro has 38 scored results on Noometry and DeepSeek-R1 has 52.