base_model, datasets, language, library_name, license, license_link, license_name, mradermacher, quantized_by, tags

base_model	datasets	language	library_name	license	license_link	license_name	mradermacher	quantized_by	tags
nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16	nvidia/Nemotron-CC-v2 nvidia/Nemotron-Post-Training-Dataset-v2 nvidia/Nemotron-Science-v1 nvidia/Nemotron-Instruction-Following-Chat-v1 nvidia/Nemotron-Agentic-v1 nvidia/Nemotron-Competitive-Programming-v1 nvidia/Nemotron-Math-Proofs-v1 nvidia/Nemotron-RL-Agentic-Conversational-Tool-Use-Pivot-v1 nvidia/Nemotron-RL-instruction_following nvidia/Nemotron-RL-agent-calendar_scheduling nvidia/Nemotron-RL-instruction_following-structured_outputs	en	transformers	other	https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-nemotron-open-model-license/	nvidia-nemotron-open-model-license	readme_rev 1	mradermacher	nvidia pytorch

About

static quants of https://huggingface.co/nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16

For a convenient overview and download list, visit our model page for this model.

weighted/imatrix quants are available at https://huggingface.co/mradermacher/NVIDIA-Nemotron-3-Nano-4B-BF16-i1-GGUF

Usage

If you are unsure how to use GGUF files, refer to one of TheBloke's READMEs for more details, including on how to concatenate multi-part files.

Provided Quants

(sorted by size, not necessarily quality. IQ-quants are often preferable over similar sized non-IQ quants)

Link	Type	Size/GB	Notes
GGUF	Q2_K	2.3
GGUF	Q3_K_S	2.4
GGUF	Q3_K_M	2.5	lower quality
GGUF	IQ4_XS	2.5
GGUF	Q3_K_L	2.6
GGUF	Q4_K_S	2.9	fast, recommended
GGUF	Q4_K_M	2.9	fast, recommended
GGUF	Q5_K_S	3.1
GGUF	Q5_K_M	3.2
GGUF	Q6_K	4.0	very good quality
GGUF	Q8_0	4.3	fast, best quality
GGUF	f16	8.1	16 bpw, overkill

Here is a handy graph by ikawrakow comparing some lower-quality quant types (lower is better):

And here are Artefact2's thoughts on the matter: https://gist.github.com/Artefact2/b5f810600771265fc1e39442288e8ec9

FAQ / Model Request

See https://huggingface.co/mradermacher/model_requests for some answers to questions you might have and/or if you want some other model quantized.

Thanks

I thank my company, nethype GmbH, for letting me use its servers and providing upgrades to my workstation to enable this work in my free time.