Nemotron Nano 9B v2
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, albeit with a slight decrease in accuracy for harder prompts that require reasoning. Conversely, allowing the model to generate reasoning traces first generally results in higher-quality final solutions to queries and tasks.
Benchmark results
| Benchmark | Score | Tags | Source |
|---|---|---|---|
| AIME 2025 | 72.1% | self-reported llm-stats | link → |
| BFCL_v3_MultiTurn | 66.9% | self-reported llm-stats | link → |
| GPQA | 64.0% | self-reported llm-stats | link → |
| IFEval | 90.3% | self-reported llm-stats | link → |
| LiveCodeBench | 71.1% | self-reported llm-stats | link → |
| MATH-500 | 97.8% | self-reported llm-stats | link → |