What are the hardware requirements for Llama3 8B CPP?

Llama3 8B CPP requires approximately 0.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama3 8B CPP and how large is it?

Llama3 8B CPP is developed by wttw, 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 Llama3 8B CPP?

Llama3 8B CPP is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3 8B CPP by wttw — VRAM 0.2GB

Name: Llama3 8B CPP
Author: wttw

Llama3 8B CPP is an open-source language model by wttw. Features: 8b LLM, VRAM: 0.2GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

4-bit 4bit Base model:quantized:unsloth/l... Base model:unsloth/llama-3-8b-... Bitsandbytes Dataset:wttw/code contest inst... En Endpoints compatible Instruct Llama Lora Quantized Region:us Safetensors Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/wttw/Llama3-8B-CPP

Llama3 8B CPP Parameters and Internals

Model Type

text-generation

Additional Notes

This llama model was trained 2x faster with Unsloth and Huggingface's TRL library.

Training Details

Methodology:

Fine-tuning using Unsloth and Huggingface's TRL library

Training Time:

2x faster training

LLM Name	Llama3 8B CPP
Repository 🤗	https://huggingface.co/wttw/Llama3-8B-CPP
Base Model(s)	Llama 3 8B Bnb 4bit unsloth/llama-3-8b-bnb-4bit
Model Size	8b
Required VRAM	0.2 GB
Updated	2026-05-06
Maintainer	wttw
Instruction-Based	Yes
Model Files	0.2 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Model Max Length	8192
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|end_of_text\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|gate_proj\|k_proj\|down_proj\|q_proj\|o_proj\|up_proj
LoRA Alpha	16
LoRA Dropout	0
R Param	16

Rank the Llama3 8B CPP 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

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Note: green Score (e.g. "73.2") means that the model is better than wttw/Llama3-8B-CPP.