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Model Comparison
Model Comparison
Compare performance, benchmarks, and characteristics
nova-pro-v1
openrouter
Context300K tokens
Input Price$0.8 / 1M tokens
Output Price$3.2 / 1M tokens
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Model Comparison
| Metric |  |  |
|---|---|---|
Pricing | ||
| Input Price | $0.8 / 1M tokens | $2 / 1M tokens |
| Output Price | $3.2 / 1M tokens | $8 / 1M tokens |
Capabilities | ||
| Context Window | 300K tokens | 1047576 tokens |
| Capabilities | tools | tools |
| Input type | text, image | text, image |
Category Scores | ||
| Overall Average | 36.1 | 52.2 |
| Academia | 37.0 | 54.9 |
| Finance | 16.3 | 39.0 |
| Marketing | 39.4 | 59.0 |
| Maths | 7.0 | 34.7 |
| Science | 52.5 | 66.1 |
| Vision | 61.7 | 74.8 |
| Writing | 39.1 | 56.6 |
| Programming | N/A | 32.2 |
Benchmark Tests | ||
| AIME | 10.7 | 43.7 |
| AA Coding Index | _ | 32.2 |
| AAII | 25.5 | 43.4 |
| AA Math Index | 7.0 | 34.7 |
| DROP | 85.4 | _ |
| GPQA | 48.4 | 66.5 |
| HLE | 3.4 | 4.6 |
| HumanEval | 89.0 | _ |
| LiveCodeBench | 23.3 | 45.7 |
| MATH-500 | 78.6 | 91.3 |
| MMLU | 85.9 | 90.2 |
| MMLU-Pro | 69.1 | 80.6 |
| MMMU | 61.7 | 74.8 |
| SciCode | 20.8 | 38.1 |
nova-pro-v1 Advantages
- • Lower input token cost ($0.8 / 1M tokens vs $2 / 1M tokens)
gpt-4.1 Advantages
- • Higher benchmark scores (52.2 vs 36.1)
- • Larger context window (1047576 tokens vs 300K tokens)