Back to GalleryBack
Model Comparison
Model Comparison
Compare performance, benchmarks, and characteristics
Loading comparison...
Model Comparison
| Metric |  |  |
|---|---|---|
Pricing | ||
| Input Price | _ | $2 / 1M tokens |
| Output Price | _ | $8 / 1M tokens |
Capabilities | ||
| Context Window | 128K tokens | 1047576 tokens |
| Capabilities | tools | tools |
| Input type | text | text, image |
Category Scores | ||
| Overall Average | 38.7 | 56.8 |
| Academia | 46.9 | 54.9 |
| Marketing | 26.7 | 54.4 |
| Programming | 45.5 | 41.9 |
| Science | 55.7 | 66.5 |
| Writing | 18.9 | 39.2 |
| Finance | N/A | 55.5 |
| Maths | N/A | 67.5 |
| Vision | N/A | 74.8 |
Benchmark Tests | ||
| AIME | _ | 43.7 |
| AA Coding Index | 45.5 | 41.9 |
| AAII | 38.1 | 43.4 |
| AA Math Index | _ | 67.5 |
| 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 (_ vs $2 / 1M tokens)
gpt-4.1 Advantages
- • Higher benchmark scores (56.8 vs 38.7)
- • Larger context window (1047576 tokens vs 128K tokens)