What are the hardware requirements for Llama 3.1 Argunaut 1 8B SFT?

Llama 3.1 Argunaut 1 8B SFT requires approximately 16.1 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 Llama 3.1 Argunaut 1 8B SFT and how large is it?

Llama 3.1 Argunaut 1 8B SFT is developed by DebateLabKIT, 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 Llama 3.1 Argunaut 1 8B SFT?

Llama 3.1 Argunaut 1 8B SFT is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.1 Argunaut 1 8B SFT by DebateLabKIT — VRAM 16.1GB, 128K context

Name: Llama 3.1 Argunaut 1 8B SFT
Author: DebateLabKIT

Llama 3.1 Argunaut 1 8B SFT is an open-source language model by DebateLabKIT. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: llama3.1, Instruction-Based, LLM Explorer Score: 0.23.

Argument-mapping Argumentation Base model:finetune:meta-llama... Base model:meta-llama/llama-3.... Conversational Critical-thinking Dataset:allenai/tulu-3-sft-mix... Dataset:debatelabkit/deep-argm... Dataset:debatelabkit/deepa2-co... Endpoints compatible Instruct Llama Logic Model-index Region:us Safetensors Sft Sharded Tensorflow Trl

Model Card on HF 🤗: https://huggingface.co/DebateLabKIT/Llama-3.1-Argunaut-1-8B-SFT

Llama 3.1 Argunaut 1 8B SFT Parameters and Internals

LLM Name	Llama 3.1 Argunaut 1 8B SFT
Repository 🤗	https://huggingface.co/DebateLabKIT/Llama-3.1-Argunaut-1-8B-SFT
Base Model(s)	meta-llama/Llama-3.1-8B-Instruct meta-llama/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-24
Maintainer	DebateLabKIT
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Model Architecture	LlamaForCausalLM
License	llama3.1
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|eot_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3.1 Argunaut 1 8B SFT 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

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