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DuoNeural/NVIDIA-Nemotron-3-Nano-4B-GGUF
NVIDIA-Nemotron-3-Nano-4B-GGUF is a machine learning model from DuoNeural. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as other.
GGUF quantizations of NVIDIA's Nemotron-3-Nano 4B Instruct model, packaged by DuoNeural for local inference with llama.cpp, Ollama, LM Studio, and compatible runtimes.
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.gguf18.1 GB · 100%
From the Hugging Face model README
GGUF quantizations of NVIDIA's Nemotron-3-Nano 4B Instruct model, packaged by DuoNeural for local inference with llama.cpp, Ollama, LM Studio, and compatible runtimes.
| File | Size | Quality | Recommended Use |
|---|---|---|---|
nemotron-3-nano-4b-Q4_K_M.gguf | ~2.5 GB | Good | General use, best balance |
nemotron-3-nano-4b-Q5_K_M.gguf | ~3.0 GB | Better | Higher quality, more RAM |
nemotron-3-nano-4b-Q8_0.gguf | ~4.3 GB | Best | Near-lossless, 8+ GB RAM |
nemotron-3-nano-4b-f16.gguf | ~8.0 GB | Reference | Full precision, 10+ GB RAM |
ollama run hf.co/DuoNeural/NVIDIA-Nemotron-3-Nano-4B-GGUF:Q4_K_M
./llama-cli -m nemotron-3-nano-4b-Q4_K_M.gguf -p "Your prompt here" -n 512
Search DuoNeural/NVIDIA-Nemotron-3-Nano-4B-GGUF in the model browser and select your preferred quantization.
NVIDIA's Nemotron-3-Nano 4B Instruct is a compact, efficient instruction-following model from NVIDIA's Nemotron family. Built on the NemotronH architecture, it delivers strong reasoning and chat performance at the 4B parameter scale. Suitable for local deployment on consumer hardware.
convert_hf_to_gguf.pyDuoNeural is an open AI research lab — human + AI in collaboration.
| Platform | Link |
|---|---|
| HuggingFace | huggingface.co/DuoNeural |
| Website | duoneural.com |
| GitHub | github.com/DuoNeural |
| X / Twitter | @DuoNeural |
| [email protected] | |
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| Support | buymeacoffee.com/duoneural |
Open access, CC BY 4.0. Authored by Archon, Jesse Caldwell, Aura — DuoNeural.
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