What are the hardware requirements for Llama 3.3 8B Instruct?

Llama 3.3 8B Instruct requires approximately 16.1 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 Llama 3.3 8B Instruct and how large is it?

Llama 3.3 8B Instruct is developed by allura-forge, 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 3.3 8B Instruct?

Llama 3.3 8B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.3 8B Instruct by allura-forge — VRAM 16.1GB, 8K context

Name: Llama 3.3 8B Instruct
Author: allura-forge

Llama 3.3 8B Instruct is an open-source language model by allura-forge. Features: 8b LLM, VRAM: 16.1GB, Context: 8K, License: llama3.3, Instruction-Based, LLM Explorer Score: 0.26.

Instruct Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/allura-forge/Llama-3.3-8B-Instruct

Llama 3.3 8B Instruct Parameters and Internals

LLM Name	Llama 3.3 8B Instruct
Repository 🤗	https://huggingface.co/allura-forge/Llama-3.3-8B-Instruct
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-07-22
Maintainer	allura-forge
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	llama3.3
Context Length	8192
Model Max Length	8192
Transformers Version	4.57.3
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256

Rank the Llama 3.3 8B Instruct 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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