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Model Comparison
Model Comparison
Compare performance, benchmarks, and characteristics
nemotron-nano-9b-v2
deepinfra
Context128K tokens
Input Price$0.04 / 1M tokens
Output Price$0.16 / 1M tokens
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Model Comparison
| Metric |  |  |
|---|---|---|
Pricing | ||
| Input Price | $0.04 / 1M tokens | $2 / 1M tokens |
| Output Price | $0.16 / 1M tokens | $8 / 1M tokens |
Capabilities | ||
| Context Window | 128K tokens | 1047576 tokens |
| Capabilities | tools | tools |
| Input type | text | text, image |
Category Scores | ||
| Overall Average | 46.4 | 52.2 |
| Academia | 45.9 | 54.9 |
| Finance | 49.2 | 39.0 |
| Marketing | 39.8 | 59.0 |
| Maths | 62.3 | 34.7 |
| Programming | 30.6 | 32.2 |
| Science | 57.0 | 66.1 |
| Writing | 39.7 | 56.6 |
| Vision | N/A | 74.8 |
Benchmark Tests | ||
| AIME | _ | 43.7 |
| AA Coding Index | 30.6 | 32.2 |
| AAII | 36.1 | 43.4 |
| AA Math Index | 62.3 | 34.7 |
| GPQA | 55.7 | 66.5 |
| HLE | 4.0 | 4.6 |
| LiveCodeBench | 70.1 | 45.7 |
| MATH-500 | _ | 91.3 |
| MMLU | _ | 90.2 |
| MMLU-Pro | 73.9 | 80.6 |
| MMMU | _ | 74.8 |
| SciCode | 20.9 | 38.1 |
nemotron-nano-9b-v2 Advantages
- • Lower input token cost ($0.04 / 1M tokens vs $2 / 1M tokens)
gpt-4.1 Advantages
- • Higher benchmark scores (52.2 vs 46.4)
- • Larger context window (1047576 tokens vs 128K tokens)