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metadata
base_model: nvidia/Llama-3_3-Nemotron-Super-49B-v1_5
language:
  - en
library_name: transformers
license: other
license_link: >-
  https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-open-model-license/
license_name: nvidia-open-model-license
mradermacher:
  readme_rev: 1
quantized_by: mradermacher
tags:
  - nvidia
  - llama-3
  - pytorch

About

static quants of https://huggingface.co/nvidia/Llama-3_3-Nemotron-Super-49B-v1_5

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

weighted/imatrix quants are available at https://huggingface.co/mradermacher/Llama-3_3-Nemotron-Super-49B-v1_5-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 18.8
GGUF Q3_K_S 22.1
GGUF Q3_K_M 24.4 lower quality
GGUF Q3_K_L 26.4
GGUF IQ4_XS 27.3
GGUF Q4_K_S 28.7 fast, recommended
GGUF Q4_K_M 30.3 fast, recommended
GGUF Q5_K_S 34.5
GGUF Q5_K_M 35.5
GGUF Q6_K 41.0 very good quality
PART 1 PART 2 Q8_0 53.1 fast, best quality

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

image.png

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.