Model comparison
Amazon Nova Experimental Chat 26 02 10 vs DeepSeek-R1
Amazon Nova Experimental Chat 26 02 10 is the stronger model overall, scoring 43.8 to 42.0 on the Noometry Index.
Last verified . 12 shared benchmarks.
DeepSeekSummary
- They share 12 benchmarks with published results for both. Amazon Nova Experimental Chat 26 02 10 scores higher in 4 categories and DeepSeek-R1 in 4 categories; 7 gaps are clear of the uncertainty.
- The widest gap is in reasoning, where Amazon Nova Experimental Chat 26 02 10 leads 28.9 to 18.7.
Side by side
| Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 | |
|---|---|---|
| Provider | Amazon | DeepSeek |
| Noometry Index | 43.8 | 42.0 |
| 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 | 12 | 52 |
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Category by category
Coding DeepSeek-R1 leads
Amazon Nova Experimental Chat 26 02 10: 43.2 (#81), DeepSeek-R1: 45.9 (#63)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Coding | 1483 | 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 26 02 10: —, DeepSeek-R1: 30.4 (#68)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| DeepResearch Bench | — | 35.1% |
| BALROG | — | 34.9% |
| METR Time Horizons | — | 53.8% |
Reasoning Amazon Nova Experimental Chat 26 02 10 leads
Amazon Nova Experimental Chat 26 02 10: 28.9 (#84), DeepSeek-R1: 18.7 (#253)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Hard Prompts | 1458 | 1415 |
| 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 | — | 141.3 |
| ForecastBench | — | 60 |
| LiveBench | — | 71.6% |
Math DeepSeek-R1 leads
Amazon Nova Experimental Chat 26 02 10: 36.6 (#108), DeepSeek-R1: 42.0 (#70)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Math | 1440 | 1401 |
| 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 26 02 10: 41.6 (#98), DeepSeek-R1: 44.3 (#81)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Expert | 1505 | 1394 |
| GPQA Diamond | — | 76.3% |
| MMLU-Pro | — | 79.3% |
| Confabulations | — | 12.7% |
| Vectara Hallucination Rate | — | 11.3% |
| GPQA (HELM) | — | 66.6% |
Multilingual Amazon Nova Experimental Chat 26 02 10 leads
Amazon Nova Experimental Chat 26 02 10: 54.3 (#48), DeepSeek-R1: 52.6 (#80)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Non-English | 1435 | 1412 |
| LMArena Chinese | 1465 | 1443 |
| LMArena Russian | 1423 | 1423 |
| LMArena French | — | 1415 |
| LMArena German | — | 1405 |
| LMArena Japanese | — | 1394 |
| LMArena Korean | — | 1359 |
| LMArena Spanish | — | 1410 |
Instruction Following Amazon Nova Experimental Chat 26 02 10 leads
Amazon Nova Experimental Chat 26 02 10: 75.3 (#66), DeepSeek-R1: 72.2 (#138)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Instruction Following | 1426 | 1382 |
| LiveBench Instruction Following | — | 80.5% |
| IFEval | — | 78.4% |
Long Context DeepSeek-R1 leads
Amazon Nova Experimental Chat 26 02 10: 44.0 (#73), DeepSeek-R1: 45.4 (#36)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Longer Query | 1441 | 1391 |
| Fiction.LiveBench | — | 75% |
Writing & Preference Too close to call
Amazon Nova Experimental Chat 26 02 10: 62.0 (#80), DeepSeek-R1: 61.5 (#84)
| Benchmark | Amazon Nova Experimental Chat 26 02 10 | DeepSeek-R1 |
|---|---|---|
| LMArena Text | 1449 | 1428 |
| LMArena Creative Writing | 1369 | 1406 |
| LMArena Multi-Turn | 1442 | 1404 |
| 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 26 02 10 better than DeepSeek-R1?
Amazon Nova Experimental Chat 26 02 10 is the stronger model overall, scoring 43.8 to 42.0 on the Noometry Index.
Is Amazon Nova Experimental Chat 26 02 10 or DeepSeek-R1 better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 45.9 versus 43.2 in the Noometry coding category.
How many benchmarks do Amazon Nova Experimental Chat 26 02 10 and DeepSeek-R1 share?
12 benchmarks have published results for both models. Amazon Nova Experimental Chat 26 02 10 has 12 scored results on Noometry and DeepSeek-R1 has 52.