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Model Comparison
Model Comparison
Compare performance, benchmarks, and characteristics
nova-lite-v1
openrouter
Context300K tokens
Input Price$0.06 / 1M tokens
Output Price$0.24 / 1M tokens
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Model Comparison
| Metric |  |  |
|---|---|---|
Pricing | ||
| Input Price | $0.06 / 1M tokens | $2 / 1M tokens |
| Output Price | $0.24 / 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 | 37.4 | 57.5 |
| Academia | 33.6 | 56.6 |
| Finance | 34.0 | 57.1 |
| Marketing | 42.9 | 55.7 |
| Maths | 43.6 | 67.5 |
| Programming | 15.3 | 41.9 |
| Science | 42.6 | 66.5 |
| Vision | 56.2 | 74.8 |
| Writing | 31.3 | 39.5 |
Benchmark Tests | ||
| AIME | 10.7 | 43.7 |
| AA Coding Index | 15.3 | 41.9 |
| AAII | 24.5 | 46.8 |
| AA Math Index | 43.6 | 67.5 |
| DROP | 80.2 | _ |
| GPQA | 42.6 | 66.5 |
| HLE | 4.6 | 4.6 |
| HumanEval | 85.4 | _ |
| LiveCodeBench | 16.7 | 45.7 |
| MATH-500 | 76.5 | 91.3 |
| MMLU | 80.5 | 90.2 |
| MMLU-Pro | 59.0 | 80.6 |
| MMMU | 56.2 | 74.8 |
| SciCode | 13.9 | 38.1 |
nova-lite-v1 Advantages
- • Lower input token cost ($0.06 / 1M tokens vs $2 / 1M tokens)
gpt-4.1 Advantages
- • Higher benchmark scores (57.5 vs 37.4)
- • Larger context window (1047576 tokens vs 300K tokens)