What are the hardware requirements for Llama 3 70B Quantised?

Llama 3 70B Quantised requires approximately 48.7 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3 70B Quantised and how large is it?

Llama 3 70B Quantised is developed by farhan-ahmad, a model with 70b 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 70B Quantised?

Llama 3 70B Quantised is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3 70B Quantised by farhan-ahmad — VRAM 48.7GB, 8K context

Name: Llama 3 70B Quantised
Author: farhan-ahmad

Llama 3 70B Quantised is an open-source language model by farhan-ahmad. Features: 70b LLM, VRAM: 48.7GB, Context: 8K, License: mit, Quantized, LLM Explorer Score: 0.13.

Conversational Endpoints compatible Gguf Llama Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/farhan-ahmad/llama-3-70b-quantised

Llama 3 70B Quantised Parameters and Internals

LLM Name	Llama 3 70B Quantised
Repository 🤗	https://huggingface.co/farhan-ahmad/llama-3-70b-quantised
Model Size	70b
Required VRAM	48.7 GB
Updated	2026-08-06
Maintainer	farhan-ahmad
Model Type	llama
Model Files	48.7 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	LlamaForCausalLM
License	mit
Context Length	8192
Model Max Length	8192
Transformers Version	4.40.0.dev0
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3 70B Quantised 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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Note: green Score (e.g. "73.2") means that the model is better than farhan-ahmad/llama-3-70b-quantised.