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Model Comparison
Model Comparison
Compare performance, benchmarks, and characteristics
llama-3.1-nemotron-70b-instruct
deepinfra
Context131072 tokens
Input Price$0.12 / 1M tokens
Output Price$0.3 / 1M tokens
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Model Comparison
| Metric |  |  |
|---|---|---|
Pricing | ||
| Input Price | $0.12 / 1M tokens | $2 / 1M tokens |
| Output Price | $0.3 / 1M tokens | $8 / 1M tokens |
Capabilities | ||
| Context Window | 131072 tokens | 1047576 tokens |
| Capabilities | tools | tools |
| Input type | text | text, image |
Category Scores | ||
| Overall Average | 28.0 | 52.2 |
| Academia | 35.0 | 54.9 |
| Finance | 17.3 | 39.0 |
| Marketing | 33.2 | 59.0 |
| Maths | 11.0 | 34.7 |
| Programming | 14.8 | 32.2 |
| Science | 50.6 | 66.1 |
| Writing | 34.1 | 56.6 |
| Vision | N/A | 74.8 |
Benchmark Tests | ||
| AIME | 24.7 | 43.7 |
| AA Coding Index | 14.8 | 32.2 |
| AAII | 23.6 | 43.4 |
| AA Math Index | 11.0 | 34.7 |
| GPQA | 46.5 | 66.5 |
| HLE | 4.6 | 4.6 |
| LiveCodeBench | 16.9 | 45.7 |
| MATH-500 | 73.3 | 91.3 |
| MMLU | 80.2 | 90.2 |
| MMLU-Pro | 69.0 | 80.6 |
| MMMU | _ | 74.8 |
| SciCode | 23.3 | 38.1 |
llama-3.1-nemotron-70b-instruct Advantages
- • Lower input token cost ($0.12 / 1M tokens vs $2 / 1M tokens)
gpt-4.1 Advantages
- • Higher benchmark scores (52.2 vs 28.0)
- • Larger context window (1047576 tokens vs 131072 tokens)