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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 | $3 / 1M tokens |
| Output Price | $0.3 / 1M tokens | $15 / 1M tokens |
Capabilities | ||
| Context Window | 131072 tokens | 256K tokens |
| Capabilities | tools | tools |
| Input type | text | text |
Category Scores | ||
| Overall Average | 37.1 | 71.3 |
| Academia | 34.7 | 76.4 |
| Finance | 36.0 | 81.0 |
| Marketing | 42.2 | 51.5 |
| Maths | 49.0 | 96.7 |
| Programming | 20.1 | 63.8 |
| Science | 46.5 | 87.6 |
| Writing | 31.6 | 42.2 |
Benchmark Tests | ||
| AIME | 24.7 | 94.3 |
| AA Coding Index | 20.1 | 63.8 |
| AAII | 22.9 | 65.3 |
| AA Math Index | 49.0 | 96.7 |
| GPQA | 46.5 | 87.6 |
| HLE | 4.6 | 23.9 |
| LiveCodeBench | 16.9 | 81.9 |
| MATH-500 | 73.3 | 99.0 |
| MMLU | 80.2 | _ |
| MMLU-Pro | 69.0 | 86.6 |
| SciCode | 23.3 | 45.7 |
llama-3.1-nemotron-70b-instruct Advantages
- • Lower input token cost ($0.12 / 1M tokens vs $3 / 1M tokens)
grok-4 Advantages
- • Higher benchmark scores (71.3 vs 37.1)
- • Larger context window (256K tokens vs 131072 tokens)