What are the hardware requirements for NVIDIA Nemotron 3 Nano 4B FP8?

NVIDIA Nemotron 3 Nano 4B FP8 requires approximately 10.6 GB of VRAM and supports a context window of 256K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed NVIDIA Nemotron 3 Nano 4B FP8 and how large is it?

NVIDIA Nemotron 3 Nano 4B FP8 is developed by unsloth, a model with 4b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

Where can I download or evaluate NVIDIA Nemotron 3 Nano 4B FP8?

NVIDIA Nemotron 3 Nano 4B FP8 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

NVIDIA Nemotron 3 Nano 4B FP8 by unsloth — VRAM 10.6GB, 256K context

Name: NVIDIA Nemotron 3 Nano 4B FP8
Author: unsloth

NVIDIA Nemotron 3 Nano 4B FP8 is an open-source language model by unsloth. Features: 4b LLM, VRAM: 10.6GB, Context: 256K, License: other, LLM Explorer Score: 0.23.

Arxiv:2412.02595 Arxiv:2504.03624 Arxiv:2511.16664 Arxiv:2512.20848 Arxiv:2512.20856 Base model:finetune:nvidia/nvi... Base model:nvidia/nvidia-nemot... Conversational Custom code En Nemotron h Nvidia Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Nano-4B-FP8

NVIDIA Nemotron 3 Nano 4B FP8 Parameters and Internals

LLM Name	NVIDIA Nemotron 3 Nano 4B FP8
Repository 🤗	https://huggingface.co/unsloth/NVIDIA-Nemotron-3-Nano-4B-FP8
Base Model(s)	NVIDIA Nemotron 3 Nano 4B BF16 nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16
Model Size	4b
Required VRAM	10.6 GB
Updated	2026-08-03
Maintainer	unsloth
Model Type	nemotron_h
Model Files	4.0 GB: 1-of-2 4.0 GB: 1-of-10 1.3 GB: 2-of-2 1.3 GB: 2-of-10 0.0 GB: 3-of-10 0.0 GB: 4-of-10 0.0 GB: 5-of-10 0.0 GB: 6-of-10 0.0 GB: 7-of-10 0.0 GB: 8-of-10 0.0 GB: 9-of-10 0.0 GB: 10-of-10
Supported Languages	en
Model Architecture	NemotronHForCausalLM
License	other
Context Length	262144
Model Max Length	262144
Transformers Version	4.53.2
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the NVIDIA Nemotron 3 Nano 4B FP8 capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

Instruction Following and Task Automation
Factuality and Completeness of Knowledge
Censorship and Alignment
Data Analysis and Insight Generation
Text Generation
Text Summarization and Feature Extraction
Code Generation
Multi-Language Support and Translation

Best Alternatives to NVIDIA Nemotron 3 Nano 4B FP8

Best Alternatives	Context / RAM	Downloads	Likes
Lumi 4B	256K / 8 GB	191	19
...oppen Gen4k Ep2 Ncp5 N3nc Vs16	256K / 8 GB	2477	1
...ppen Gen4k Ep2 Ncp5 N3nc Iid16	256K / 8 GB	2447	1
...oppen Gen4k Ep2 Ncp5 N3nc Base	256K / 8 GB	2231	1
NVIDIA Nemotron 3 Nano 4B FP8	256K / 5.3 GB	83285	27
H2o Lightning 4B Nemotron Nano	256K / 8 GB	279	3
... Nano 4B 8K Grpo Hardyman S300	256K / 15.9 GB	338	1
NVIDIA Nemotron 3 Nano 4B	256K / 8 GB	4851	16
NVIDIA Nemotron 3 Nano 4B BF16	256K / 7.9 GB	131	2
Nemotron H 4B Instruct 128K	128K / 9 GB	1686	10

Note: green Score (e.g. "73.2") means that the model is better than unsloth/NVIDIA-Nemotron-3-Nano-4B-FP8.