What are the hardware requirements for Llama3 70B RAG?

Llama3 70B RAG requires approximately 141.9 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 Llama3 70B RAG and how large is it?

Llama3 70B RAG is developed by WendyHoang, 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 Llama3 70B RAG?

Llama3 70B RAG is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3 70B RAG by WendyHoang — VRAM 141.9GB, 8K context

Name: Llama3 70B RAG
Author: WendyHoang

Llama3 70B RAG is an open-source language model by WendyHoang. Features: 70b LLM, VRAM: 141.9GB, Context: 8K, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

Conversational Endpoints compatible Ggml Gguf Instruct Llama Pytorch Q4 Quantized Region:us Sharded

Model Card on HF 🤗: https://huggingface.co/WendyHoang/Llama3-70B-RAG

Llama3 70B RAG Parameters and Internals

LLM Name	Llama3 70B RAG
Repository 🤗	https://huggingface.co/WendyHoang/Llama3-70B-RAG
Model Size	70b
Required VRAM	141.9 GB
Updated	2026-08-02
Maintainer	WendyHoang
Model Type	llama
Instruction-Based	Yes
Model Files	42.5 GB 48.0 GB: 1-of-2 9.9 GB: 2-of-2 4.6 GB: 1-of-30 4.7 GB: 2-of-30 5.0 GB: 3-of-30 5.0 GB: 4-of-30 4.7 GB: 5-of-30 4.7 GB: 6-of-30 4.7 GB: 7-of-30 5.0 GB: 8-of-30 5.0 GB: 9-of-30 4.7 GB: 10-of-30 4.7 GB: 11-of-30 4.7 GB: 12-of-30 5.0 GB: 13-of-30 5.0 GB: 14-of-30 4.7 GB: 15-of-30 4.7 GB: 16-of-30 4.7 GB: 17-of-30 5.0 GB: 18-of-30 5.0 GB: 19-of-30 4.7 GB: 20-of-30 4.7 GB: 21-of-30 4.7 GB: 22-of-30 5.0 GB: 23-of-30 5.0 GB: 24-of-30 4.7 GB: 25-of-30 4.7 GB: 26-of-30 4.7 GB: 27-of-30 5.0 GB: 28-of-30 5.0 GB: 29-of-30 2.1 GB: 30-of-30
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	ggml\|q4\|gguf\|q4_k
Model Architecture	LlamaForCausalLM
Context Length	8192
Model Max Length	8192
Transformers Version	4.41.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|end_of_text\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama3 70B RAG 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 Llama3 70B RAG

Best Alternatives	Context / RAM	Downloads	Likes
...AI Korean Llama3.1 Sft DPO 70B	128K / 141.9 GB	126	7
Grok Oss Revenant 70B	128K / 141.9 GB	8503	2
Llama 3.3 70B Instruct GGUF	128K / 15.9 GB	23398	124
Reflection Llama 3.1 70B Bf16	128K / 141.9 GB	283	6
...ma3 70B Chinese Chat GGUF 4bit	8K / 40 GB	196	18
Meta Llama 3 70B Instruct	8K / 40.3 GB	6	1
CodeLlama 70B Instruct Hf GGUF	4K / 25.5 GB	487	2
...B Instruct Gradient 1048K 8bit	1024K / 75 GB	41	5
...B Instruct Gradient 1048K 4bit	1024K / 39.7 GB	25	3
...B Instruct Gradient 1048K 2bit	1024K / 21.9 GB	25	2

Note: green Score (e.g. "73.2") means that the model is better than WendyHoang/Llama3-70B-RAG.