Model comparison
Amazon Nova Experimental Chat 10 20 vs DeepSeek-R1
Amazon Nova Experimental Chat 10 20 and DeepSeek-R1 score almost the same on the Noometry Index (42.1 vs 42.3), so choose on price, context window or the category you care about most.
Last verified . 17 shared benchmarks.
DeepSeekSummary
- They share 17 benchmarks with published results for both. Amazon Nova Experimental Chat 10 20 scores higher in 2 categories and DeepSeek-R1 in 6 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Amazon Nova Experimental Chat 10 20 leads 28.4 to 18.6.
Side by side
| Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 42.1 | 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 | 17 | 52 |
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Category by category
Coding DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 41.6 (#123), DeepSeek-R1: 46.3 (#68)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Coding | 1412 | 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 20: —, DeepSeek-R1: 30.7 (#75)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |
Reasoning Amazon Nova Experimental Chat 10 20 leads
Amazon Nova Experimental Chat 10 20: 28.4 (#106), DeepSeek-R1: 18.6 (#278)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Hard Prompts | 1396 | 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 DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 39.0 (#119), DeepSeek-R1: 43.8 (#79)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Math | 1425 | 1400 |
| OTIS Mock AIME 2024-2025 | — | 66.4% |
| Omni-MATH | — | 42.4% |
| LiveBench Math | — | 80.7% |
| MATH Level 5 | — | 96.6% |
Knowledge DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 38.5 (#144), DeepSeek-R1: 44.5 (#87)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Expert | 1386 | 1394 |
| GPQA Diamond | — | 76.3% |
| MMLU-Pro | — | 79.3% |
| Confabulations | — | 12.7% |
| Vectara Hallucination Rate | — | 11.3% |
| GPQA (HELM) | — | 66.6% |
Multilingual DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 49.5 (#131), DeepSeek-R1: 52.4 (#85)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1372 | 1412 |
| LMArena Chinese | 1404 | 1442 |
| LMArena French | 1425 | 1417 |
| LMArena German | 1391 | 1404 |
| LMArena Japanese | 1360 | 1391 |
| LMArena Korean | 1324 | 1360 |
| LMArena Russian | 1371 | 1423 |
| LMArena Spanish | 1382 | 1411 |
Instruction Following Too close to call
Amazon Nova Experimental Chat 10 20: 72.1 (#141), DeepSeek-R1: 72.0 (#143)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Instruction Following | 1365 | 1382 |
| LiveBench Instruction Following | — | 80.5% |
| IFEval | — | 78.4% |
Long Context DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 41.7 (#133), DeepSeek-R1: 45.4 (#36)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1370 | 1391 |
| Fiction.LiveBench | — | 75% |
Writing & Preference DeepSeek-R1 leads
Amazon Nova Experimental Chat 10 20: 56.6 (#136), DeepSeek-R1: 61.4 (#88)
| Benchmark | Amazon Nova Experimental Chat 10 20 | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1394 | 1428 |
| LMArena Creative Writing | 1318 | 1405 |
| LMArena Multi-Turn | 1364 | 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 20 better than DeepSeek-R1?
Amazon Nova Experimental Chat 10 20 and DeepSeek-R1 score almost the same on the Noometry Index (42.1 vs 42.3), so choose on price, context window or the category you care about most.
Is Amazon Nova Experimental Chat 10 20 or DeepSeek-R1 better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 41.6 in the Noometry coding category.
How many benchmarks do Amazon Nova Experimental Chat 10 20 and DeepSeek-R1 share?
17 benchmarks have published results for both models. Amazon Nova Experimental Chat 10 20 has 17 scored results on Noometry and DeepSeek-R1 has 52.