Nemotron 3 Nano 9B
NVIDIA's Nemotron 3 at 9B. Tuned for NVIDIA-stack deployment patterns; strong tool-calling reliability.
Overview
NVIDIA's Nemotron 3 at 9B. Tuned for NVIDIA-stack deployment patterns; strong tool-calling reliability.
Family & lineage
How this model relates to others in its lineage. Family members share architecture and training-data roots; parent / children edges record direct distillation or fine-tune relationships.
Strengths
- NVIDIA stack alignment
- Strong tool-calling
Weaknesses
- Smaller community than Llama / Qwen
Quantization variants
Each quantization trades model quality for file size and VRAM. Q4_K_M is the most popular starting point.
| Quantization | File size | VRAM required |
|---|---|---|
| Q4_K_M | 5.3 GB | 7 GB |
Get the model
HuggingFace
Original weights
Source repository — direct quantization required.
Hardware that runs this
Cards with enough VRAM for at least one quantization of Nemotron 3 Nano 9B.
Models worth comparing
Same parameter band, plus what's one tier above and below — so you can decide what actually fits your hardware.
Frequently asked
What's the minimum VRAM to run Nemotron 3 Nano 9B?
Can I use Nemotron 3 Nano 9B commercially?
What's the context length of Nemotron 3 Nano 9B?
Source: huggingface.co/nvidia/Nemotron-3-Nano-9B
Reviewed by RunLocalAI Editorial. See our editorial policy for how we research and verify model claims.
Related — keep moving
Verify Nemotron 3 Nano 9B runs on your specific hardware before committing money.