What are the hardware requirements for Auto RAG Llama 3 8B Instruct?

Auto RAG Llama 3 8B Instruct requires approximately 32.1 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 Auto RAG Llama 3 8B Instruct and how large is it?

Auto RAG Llama 3 8B Instruct is developed by ICTNLP, 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 Auto RAG Llama 3 8B Instruct?

Auto RAG Llama 3 8B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Auto RAG Llama 3 8B Instruct by ICTNLP — VRAM 32.1GB, 8K context

Name: Auto RAG Llama 3 8B Instruct
Author: ICTNLP

Auto RAG Llama 3 8B Instruct is an open-source language model by ICTNLP. Features: 8b LLM, VRAM: 32.1GB, Context: 8K, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.16.

Arxiv:2411.19443 Conversational Endpoints compatible Instruct Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/ICTNLP/Auto-RAG-Llama-3-8B-Instruct

Auto RAG Llama 3 8B Instruct Parameters and Internals

LLM Name	Auto RAG Llama 3 8B Instruct
Repository 🤗	https://huggingface.co/ICTNLP/Auto-RAG-Llama-3-8B-Instruct
Model Size	8b
Required VRAM	32.1 GB
Updated	2026-07-22
Maintainer	ICTNLP
Model Type	llama
Instruction-Based	Yes
Model Files	4.9 GB: 1-of-7 4.8 GB: 2-of-7 5.0 GB: 3-of-7 5.0 GB: 4-of-7 4.8 GB: 5-of-7 5.0 GB: 6-of-7 2.6 GB: 7-of-7
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.43.3
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float32

Rank the Auto RAG Llama 3 8B Instruct 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 Auto RAG Llama 3 8B Instruct

Best Alternatives	Context / RAM	Downloads	Likes
...otron 8B UltraLong 4M Instruct	4192K / 32.1 GB	1135	125
UltraLong Thinking	4192K / 16.1 GB	2	3
...a 3.1 8B UltraLong 4M Instruct	4192K / 32.1 GB	176	24
...a 3.1 8B UltraLong 2M Instruct	2096K / 32.1 GB	875	9
...otron 8B UltraLong 2M Instruct	2096K / 32.1 GB	124	18
Cthulhu 8B V1.4	1048K / 16.1 GB	10	10
...raLong 1M Instruct Abliterated	1048K / 32.1 GB	4	9
...a 3.1 8B UltraLong 1M Instruct	1048K / 32.1 GB	1387	29
...otron 8B UltraLong 1M Instruct	1048K / 32.1 GB	702	59
Zero Llama 3.1 8B Beta6	1048K / 16.1 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than ICTNLP/Auto-RAG-Llama-3-8B-Instruct.