LocalClaw/LLM/Nemotron Nano 9B v2
Open-weight local LLM

Nemotron Nano 9B v2

NVIDIA hybrid Mamba-Transformer 9B. 6x throughput vs comparable dense models, 128K context, strong maths/code. Efficient toggle-able reasoning. NVIDIA Open Model License.

16 GB sweet spot 10 GB RAM Q5_K_M Coding assistant
Run with LocalClaw Compare all models
Parameters
9B
Minimum RAM
10 GB
Model size
5.5 GB
Quantization
Q5_K_M

Can Nemotron Nano 9B v2 run locally?

Nemotron Nano 9B v2 is a practical pick for 16 GB machines, especially with Q5_K_M quantization.

Search for nvidia-nemotron-nano-9b-v2 in LM Studio or another GGUF-compatible runtime.

nvidia/NVIDIA-Nemotron-Nano-9B-v2
chatreasoningcodestandardgeneral

Install path

01
Check RAM fitMinimum 10 GB RAM. Start with the Q5_K_M quant.
02
Load the modelSearch nvidia-nemotron-nano-9b-v2 in LM Studio.
03
Control locallyUse LocalClaw to manage models, agents, chat, channels and scheduled OpenClaw work.

Strengths

  • NVIDIA hybrid Mamba-Transformer 9B. 6x throughput vs comparable dense models, 128K context, strong maths/code. Efficient toggle-able reasoning. NVIDIA Open Model License.

Limitations

  • Performance depends on quantization, RAM bandwidth and runtime support.

Best use cases

  • chat
  • reasoning
  • code
  • standard
  • general

Capability profile

speed
9
quality
7
coding
8
reasoning
8

Technical notes

Developer
nemotron
License
See model repository
Context window
Unknown tokens
Architecture
See model card

This model fits these next steps

Hardware fit is based on LocalClaw's RAM tier, model size and quantization metadata. Always leave memory headroom for your OS and runtime.

Starter desktopMac mini M4 16GBPortable fitMacBook Air M4 16GBBest 16GB models16GB RAM guide

Where to go next