Model comparison
DeepSeek-R1 vs Nemotron 3 Nano 30B A3B
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 40.6 on the Noometry Index. Nemotron 3 Nano 30B A3B costs 10× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.
Last verified . 18 shared benchmarks.
DeepSeek
NVIDIASummary
- They share 18 benchmarks with published results for both. DeepSeek-R1 scores higher in 7 categories and Nemotron 3 Nano 30B A3B in 1 category; 8 gaps are clear of the uncertainty.
- The widest gap is in writing & preference, where DeepSeek-R1 leads 61.4 to 52.3.
- Nemotron 3 Nano 30B A3B is cheaper at $0.05 / $0.20 per million input/output tokens, against $0.50 / $2.15 for DeepSeek-R1.
- Nemotron 3 Nano 30B A3B accepts more context: 262K tokens versus 164K.
- Nemotron 3 Nano 30B A3B has downloadable open weights; the other is API-only.
Side by side
| DeepSeek-R1 | Nemotron 3 Nano 30B A3B | |
|---|---|---|
| Provider | DeepSeek | NVIDIA |
| Noometry Index | 42.3 | 40.6 |
| Released | 2025-01-20 | 2025-12-15 |
| Weights | Proprietary | Open |
| Context window | 164K | 262K |
| Max output | 64K | 262K |
| Input $ / M tokens | $0.50 | $0.05 |
| Output $ / M tokens | $2.15 | $0.20 |
| Results tracked | 52 | 18 |
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Category by category
Coding DeepSeek-R1 leads
DeepSeek-R1: 46.3 (#68), Nemotron 3 Nano 30B A3B: 40.5 (#138)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Coding | 1427 | 1378 |
| 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
DeepSeek-R1: 30.7 (#75), Nemotron 3 Nano 30B A3B: —
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| DeepResearch Bench | 35.1% | — |
| BALROG | 34.9% | — |
| METR Time Horizons | 53.8% | — |
Reasoning Nemotron 3 Nano 30B A3B leads
DeepSeek-R1: 18.6 (#278), Nemotron 3 Nano 30B A3B: 27.1 (#124)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Hard Prompts | 1416 | 1348 |
| 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
DeepSeek-R1: 43.8 (#79), Nemotron 3 Nano 30B A3B: 37.8 (#147)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Math | 1400 | 1371 |
| OTIS Mock AIME 2024-2025 | 66.4% | — |
| Omni-MATH | 42.4% | — |
| LiveBench Math | 80.7% | — |
| MATH Level 5 | 96.6% | — |
Knowledge DeepSeek-R1 leads
DeepSeek-R1: 44.5 (#87), Nemotron 3 Nano 30B A3B: 38.2 (#148)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| Vectara Hallucination Rate | 11.3% | 9.6% |
| LMArena Expert | 1394 | 1355 |
| GPQA Diamond | 76.3% | — |
| MMLU-Pro | 79.3% | — |
| Confabulations | 12.7% | — |
| GPQA (HELM) | 66.6% | — |
Multilingual DeepSeek-R1 leads
DeepSeek-R1: 52.4 (#85), Nemotron 3 Nano 30B A3B: 45.8 (#162)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Non-English | 1412 | 1320 |
| LMArena Chinese | 1442 | 1382 |
| LMArena French | 1417 | 1396 |
| LMArena German | 1404 | 1348 |
| LMArena Japanese | 1391 | 1268 |
| LMArena Korean | 1360 | 1269 |
| LMArena Russian | 1423 | 1303 |
| LMArena Spanish | 1411 | 1376 |
Instruction Following DeepSeek-R1 leads
DeepSeek-R1: 72.0 (#143), Nemotron 3 Nano 30B A3B: 68.8 (#180)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Instruction Following | 1382 | 1304 |
| LiveBench Instruction Following | 80.5% | — |
| IFEval | 78.4% | — |
Long Context DeepSeek-R1 leads
DeepSeek-R1: 45.4 (#36), Nemotron 3 Nano 30B A3B: 39.5 (#175)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Longer Query | 1391 | 1300 |
| Fiction.LiveBench | 75% | — |
Writing & Preference DeepSeek-R1 leads
DeepSeek-R1: 61.4 (#88), Nemotron 3 Nano 30B A3B: 52.3 (#174)
| Benchmark | DeepSeek-R1 | Nemotron 3 Nano 30B A3B |
|---|---|---|
| LMArena Text | 1428 | 1348 |
| LMArena Creative Writing | 1405 | 1269 |
| LMArena Multi-Turn | 1405 | 1319 |
| Short-Story Creative Writing | 83% | — |
| EQ-Bench Creative Writing | 1500 | — |
| WildBench | 82.8% | — |
| LiveBench Language | 48.5% | — |
Frequently asked questions
Is DeepSeek-R1 better than Nemotron 3 Nano 30B A3B?
DeepSeek-R1 is the stronger model overall, scoring 42.3 to 40.6 on the Noometry Index. Nemotron 3 Nano 30B A3B costs 10× less per token, which makes it the better buy when DeepSeek-R1's lead doesn't matter for your workload.
Which is cheaper, DeepSeek-R1 or Nemotron 3 Nano 30B A3B?
Nemotron 3 Nano 30B A3B is cheaper. It lists at $0.05 per million input tokens and $0.20 per million output tokens; DeepSeek-R1 lists at $0.50 and $2.15.
Is DeepSeek-R1 or Nemotron 3 Nano 30B A3B better for coding?
DeepSeek-R1 scores higher on coding benchmarks: 46.3 versus 40.5 in the Noometry coding category.
Which has the bigger context window?
Nemotron 3 Nano 30B A3B does, with 262K tokens against 164K.
How many benchmarks do DeepSeek-R1 and Nemotron 3 Nano 30B A3B share?
18 benchmarks have published results for both models. DeepSeek-R1 has 52 scored results on Noometry and Nemotron 3 Nano 30B A3B has 18.