NVIDIA
NVIDIA-Nemotron-Nano-9B-v2 is a large language model (LLM) trained from scratch by NVIDIA, and designed as a unified model for both reasoning and non-reasoning tasks. It responds to user queries and tasks by first generating a reasoning trace and then concluding with a final response. The model's reasoning capabilities can be controlled via a system prompt. If the user prefers the model to provide its final answer without intermediate reasoning traces, it can be configured to do so.\
NVIDIA model catalogRank #328 across 526
Rank #358 across 436
Rank #15 across 357
Percentile score by analysis domain.
* Cost is inverted: lower input, output, and blended prices rank higher.
Higher bars mean stronger relative placement.
| Metric | Domain | Value | Rank |
|---|---|---|---|
| Artificial Analysis Intelligence Index | overall | 14.8 | #328 |
| Artificial Analysis Coding Index | coding | 8.3 | #358 |
| Artificial Analysis Math Index | math | 69.7 | #97 |
| MMLU-Pro | reasoning | 74.2% | #189 |
| reasoning |
| 57.0% |
| #320 |
| Humanity's Last Exam | reasoning | 4.6% | #373 |
| LiveCodeBench | coding | 72.4% | #59 |
| SciCode | coding, reasoning | 22.0% | #372 |
| Output Speed | speed | 118 tok/s | #118 |
| Time to First Token | speed | 0.23s | #4 |
| Blended Price | cost | $0.070/M | #15 |
| Input Price | cost | $0.040/M | #13 |
| Output Price | cost | $0.160/M | #21 |
| Value Index | cost, overall | 211.4 | #19 |