What are the hardware requirements for Nemotron3 8B?

Nemotron3 8B requires approximately 17.1 GB of VRAM and supports a context window of 4K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemotron3 8B and how large is it?

Nemotron3 8B is developed by thhaus, a model with 8b 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 Nemotron3 8B?

Nemotron3 8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemotron3 8B by thhaus — VRAM 17.1GB, 4K context

Name: Nemotron3 8B
Author: thhaus

Nemotron3 8B is an open-source language model by thhaus. Features: 8b LLM, VRAM: 17.1GB, Context: 4K, LLM Explorer Score: 0.15.

Arxiv:1910.09700 Endpoints compatible Nemotron Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/thhaus/nemotron3-8b

Nemotron3 8B Parameters and Internals

LLM Name	Nemotron3 8B
Repository 🤗	https://huggingface.co/thhaus/nemotron3-8b
Model Size	8b
Required VRAM	17.1 GB
Updated	2026-07-28
Maintainer	thhaus
Model Type	nemotron
Model Files	5.0 GB: 1-of-4 4.9 GB: 2-of-4 5.0 GB: 3-of-4 2.2 GB: 4-of-4
Model Architecture	NemotronForCausalLM
Context Length	4096
Model Max Length	4096
Transformers Version	4.44.0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	256000
Torch Data Type	bfloat16

Rank the Nemotron3 8B capabilities

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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 Nemotron3 8B

Best Alternatives	Context / RAM	Downloads	Likes
Minitron 8B Base	4K / 16.5 GB	26882	71

Note: green Score (e.g. "73.2") means that the model is better than thhaus/nemotron3-8b.