How to use from
llama.cpp
Install (macOS, Linux)
curl -LsSf https://llama.app/install.sh | sh
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
# Run inference directly in the terminal:
llama cli -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
Install from WinGet (Windows)
winget install llama.cpp
# Start a local OpenAI-compatible server with a web UI:
llama serve -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
# Run inference directly in the terminal:
llama cli -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
Use pre-built binary
# Download pre-built binary from:
# https://github.com/ggerganov/llama.cpp/releases
# Start a local OpenAI-compatible server with a web UI:
./llama-server -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
# Run inference directly in the terminal:
./llama-cli -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
Build from source code
git clone https://github.com/ggerganov/llama.cpp.git
cd llama.cpp
cmake -B build
cmake --build build -j --target llama-server llama-cli
# Start a local OpenAI-compatible server with a web UI:
./build/bin/llama-server -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
# Run inference directly in the terminal:
./build/bin/llama-cli -hf noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
Use Docker
docker model run hf.co/noctrex/Nemotron-3-Nano-30B-A3B-MXFP4_MOE-GGUF:MXFP4_MOE
Quick Links

This is a MXFP4_MOE imatrix quantization of the model NVIDIA-Nemotron-3-Nano-30B-A3B, based on the imatrix from unsloth.

Get the latest llama.cpp in order to run it.

Also see the instructions here: Unsloth NVIDIA Nemotron 3 Nano - How To Run Guide

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GGUF
Model size
32B params
Architecture
nemotron_h_moe
Hardware compatibility
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