What are the hardware requirements for NVIDIA Nemotron 3 Nano 4B BF16?

NVIDIA Nemotron 3 Nano 4B BF16 requires approximately 7.9 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 BF16 and how large is it?

NVIDIA Nemotron 3 Nano 4B BF16 is developed by mlx-community, 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 BF16?

NVIDIA Nemotron 3 Nano 4B BF16 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 BF16 by mlx-community — VRAM 7.9GB, 256K context

Name: NVIDIA Nemotron 3 Nano 4B BF16
Author: mlx-community

NVIDIA Nemotron 3 Nano 4B BF16 is an open-source language model by mlx-community. Features: 4b LLM, VRAM: 7.9GB, Context: 256K, License: other, Instruction-Based, LLM Explorer Score: 0.23.

Base model:finetune:nvidia/nvi... Base model:nvidia/nvidia-nemot... Conversational Custom code Dataset:nvidia/nemotron-agenti... Dataset:nvidia/nemotron-cc-v2 Dataset:nvidia/nemotron-compet... Dataset:nvidia/nemotron-instru... Dataset:nvidia/nemotron-math-p... Dataset:nvidia/nemotron-post-t... Dataset:nvidia/nemotron-rl-age... Dataset:nvidia/nemotron-rl-age... Dataset:nvidia/nemotron-rl-ins... Dataset:nvidia/nemotron-rl-ins... Dataset:nvidia/nemotron-scienc... En Instruct Mlx Nemotron h Nvidia Pytorch Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/mlx-community/NVIDIA-Nemotron-3-Nano-4B-BF16

NVIDIA Nemotron 3 Nano 4B BF16 Parameters and Internals

LLM Name	NVIDIA Nemotron 3 Nano 4B BF16
Repository 🤗	https://huggingface.co/mlx-community/NVIDIA-Nemotron-3-Nano-4B-BF16
Base Model(s)	NVIDIA Nemotron 3 Nano 4B BF16 nvidia/NVIDIA-Nemotron-3-Nano-4B-BF16
Model Size	4b
Required VRAM	7.9 GB
Updated	2026-08-08
Maintainer	mlx-community
Model Type	nemotron_h
Instruction-Based	Yes
Model Files	5.3 GB: 1-of-2 2.6 GB: 2-of-2
Supported Languages	en
Model Architecture	NemotronHForCausalLM
License	other
Context Length	262144
Model Max Length	262144
Transformers Version	4.53.0
Tokenizer Class	TokenizersBackend
Vocabulary Size	131072
Torch Data Type	bfloat16

Rank the NVIDIA Nemotron 3 Nano 4B BF16 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

Quantized Models of the NVIDIA Nemotron 3 Nano 4B BF16

Model	Likes	Downloads	VRAM
... Nemotron 3 Nano 4B OptiQ 4bit	3	855	3 GB

Best Alternatives to NVIDIA Nemotron 3 Nano 4B BF16

Best Alternatives	Context / RAM	Downloads	Likes
NVIDIA Nemotron 3 Nano 4B FP8	256K / 5.3 GB	83285	27
Nemotron H 4B Instruct 128K	128K / 9 GB	1686	10
... Nemotron 3 Nano 4B OptiQ 4bit	256K / 3.1 GB	855	3
NVIDIA Nemotron 3 Nano 4B 4bit	256K / 2.2 GB	445	2
NVIDIA Nemotron 3 Nano 4B 6bit	256K / 3.2 GB	47	1

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/NVIDIA-Nemotron-3-Nano-4B-BF16.