Model comparison
Amazon Nova Experimental Chat 10 09 vs DeepSeek-R1
Amazon Nova Experimental Chat 10 09 and DeepSeek-R1 score almost the same on the Noometry Index (41.9 vs 42.3), so choose on price, context window or the category you care about most.
Last verified . 9 shared benchmarks.
DeepSeekSummary
- They share 9 benchmarks with published results for both. Amazon Nova Experimental Chat 10 09 scores higher in 1 category and DeepSeek-R1 in 5 categories; 6 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Amazon Nova Experimental Chat 10 09 leads 27.3 to 18.6.
Side by side
| Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 41.9 | 42.3 |
| Released | — | 2025-01-20 |
| Weights | Proprietary | Proprietary |
| Context window | — | 164K |
| Max output | — | 64K |
| Input $ / M tokens | — | $0.50 |
| Output $ / M tokens | — | $2.15 |
| Results tracked | 9 | 52 |
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Category by category
Coding DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 09: 40.2 (#145), DeepSeek-R1: 46.3 (#68)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Coding | 1370 | 1427 |
| Aider Polyglot | — | 71.4% |
| SciCode | — | 35.7% |
| WeirdML | — | 41.6% |
| LiveBench Coding | — | 66.7% |
| ALE-Bench | — | 804.12 |
| AlgoTune | — | 1.7 |
Agentic & Tool Use Not comparable
Amazon Nova Experimental Chat 10 09: —, DeepSeek-R1: 30.7 (#75)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |
Reasoning Amazon Nova Experimental Chat 10 09 leads
Amazon Nova Experimental Chat 10 09: 27.3 (#120), DeepSeek-R1: 18.6 (#278)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Hard Prompts | 1356 | 1416 |
| 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% |
| LiveBench Data Analysis | — | 69.8% |
| Epoch Capabilities Index | — | 141.29 |
| ForecastBench | — | 60 |
| LiveBench | — | 71.6% |
Math Not comparable
Amazon Nova Experimental Chat 10 09: —, DeepSeek-R1: 43.8 (#79)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| Omni-MATH | — | 42.4% |
| LiveBench Math | — | 80.7% |
| LMArena Math | — | 1400 |
| MATH Level 5 | — | 96.6% |
Knowledge Not comparable
Amazon Nova Experimental Chat 10 09: —, DeepSeek-R1: 44.5 (#87)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| GPQA Diamond | — | 76.3% |
| MMLU-Pro | — | 79.3% |
| Confabulations | — | 12.7% |
| Vectara Hallucination Rate | — | 11.3% |
| GPQA (HELM) | — | 66.6% |
| LMArena Expert | — | 1394 |
Multilingual DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 09: 47.3 (#150), DeepSeek-R1: 52.4 (#85)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1340 | 1412 |
| LMArena Chinese | 1341 | 1442 |
| LMArena French | — | 1417 |
| LMArena German | — | 1404 |
| LMArena Japanese | — | 1391 |
| LMArena Korean | — | 1360 |
| LMArena Russian | — | 1423 |
| LMArena Spanish | — | 1411 |
Instruction Following DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 09: 69.4 (#172), DeepSeek-R1: 72.0 (#143)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Instruction Following | 1315 | 1382 |
| LiveBench Instruction Following | — | 80.5% |
| IFEval | — | 78.4% |
Long Context DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 09: 40.5 (#152), DeepSeek-R1: 45.4 (#36)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1333 | 1391 |
| Fiction.LiveBench | — | 75% |
Writing & Preference DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 09: 54.7 (#149), DeepSeek-R1: 61.4 (#88)
| Benchmark | Amazon Nova Experimental Chat 10 09 | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1364 | 1428 |
| LMArena Creative Writing | 1307 | 1405 |
| LMArena Multi-Turn | 1355 | 1405 |
| Short-Story Creative Writing | — | 83% |
| EQ-Bench Creative Writing | — | 1500 |
| WildBench | — | 82.8% |
| LiveBench Language | — | 48.5% |
Frequently asked questions
Is Amazon Nova Experimental Chat 10 09 better than DeepSeek-R1?
Amazon Nova Experimental Chat 10 09 and DeepSeek-R1 score almost the same on the Noometry Index (41.9 vs 42.3), so choose on price, context window or the category you care about most.
Is Amazon Nova Experimental Chat 10 09 or DeepSeek-R1 better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 40.2 in the Noometry coding category.
How many benchmarks do Amazon Nova Experimental Chat 10 09 and DeepSeek-R1 share?
9 benchmarks have published results for both models. Amazon Nova Experimental Chat 10 09 has 9 scored results on Noometry and DeepSeek-R1 has 52.