What are the hardware requirements for Nemotron W 4B MagLight 0.1?

Nemotron W 4B MagLight 0.1 requires approximately 9.2 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Nemotron W 4B MagLight 0.1 and how large is it?

Nemotron W 4B MagLight 0.1 is developed by Nexesenex, 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 Nemotron W 4B MagLight 0.1?

Nemotron W 4B MagLight 0.1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nemotron W 4B MagLight 0.1 by Nexesenex — VRAM 9.2GB, 128K context

Name: Nemotron W 4B MagLight 0.1
Author: Nexesenex

Nemotron W 4B MagLight 0.1 is an open-source language model by Nexesenex. Features: 4b LLM, VRAM: 9.2GB, Context: 128K, Merged, LLM Explorer Score: 0.21.

Merged Model Arxiv:2403.19522 Base model:anthracite-org/magn... Base model:fourohfour/deedlit ... Base model:magpie-align/magpie... Conversational Endpoints compatible Llama Model-index Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Nexesenex/Nemotron_W_4b_MagLight_0.1

Nemotron W 4B MagLight 0.1 Parameters and Internals

LLM Name	Nemotron W 4b MagLight 0.1
Repository 🤗	https://huggingface.co/Nexesenex/Nemotron_W_4b_MagLight_0.1
Base Model(s)	Deedlit 4B Magpie-Align/MagpieLM-4B-Chat-v0.1 Magnum V2 4B FourOhFour/Deedlit_4B Magpie-Align/MagpieLM-4B-Chat-v0.1 anthracite-org/magnum-v2-4b
Merged Model	Yes
Model Size	4b
Required VRAM	9.2 GB
Updated	2026-07-29
Maintainer	Nexesenex
Model Type	llama
Model Files	0.8 GB: 1-of-10 1.0 GB: 2-of-10 1.0 GB: 3-of-10 1.0 GB: 4-of-10 1.0 GB: 5-of-10 1.0 GB: 6-of-10 1.0 GB: 7-of-10 1.0 GB: 8-of-10 1.0 GB: 9-of-10 0.4 GB: 10-of-10
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Nemotron W 4B MagLight 0.1 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 Nemotron W 4B MagLight 0.1

Best Alternatives	Context / RAM	Downloads	Likes
4Bcpt	256K / 8.8 GB	5	0
HoldMy4BKTO	256K / 8.8 GB	5	0
Xgen Small 4B Instruct R	256K / 17.7 GB	54	4
Xgen Small 4B Base R	256K / 17.7 GB	30	3
SJT 4B	146K / 7.6 GB	7	0
...lama 3.1 Nemotron Nano 4B V1.1	128K / 9 GB	3940	116
Loxa 4B	128K / 16 GB	8	0
Nemotron W 4b Halo 0.1	128K / 9.2 GB	22	3
Aura 4B	128K / 9 GB	24	14
Impish LLAMA 4B	128K / 9 GB	50	66

Note: green Score (e.g. "73.2") means that the model is better than Nexesenex/Nemotron_W_4b_MagLight_0.1.