What are the hardware requirements for Llama 3 8B ORPO?

Llama 3 8B ORPO requires approximately 16.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3 8B ORPO and how large is it?

Llama 3 8B ORPO is developed by kingabzpro, 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 8B ORPO?

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

Llama 3 8B ORPO by kingabzpro — VRAM 16.1GB

Name: Llama 3 8B ORPO
Author: kingabzpro

Llama 3 8B ORPO is an open-source language model by kingabzpro. Features: 8b LLM, VRAM: 16.1GB, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.12.

Arxiv:1910.09700 Conversational Dataset:trelis/orpo-dpo-mix-40... En Endpoints compatible Gguf Instruct Llama Lora Q4 Quantized Region:us Safetensors Sharded Tensorflow Text-embeddings-inference

Model Card on HF 🤗: https://huggingface.co/kingabzpro/Llama-3-8B-ORPO

Llama 3 8B ORPO Parameters and Internals

LLM Name	Llama 3 8B ORPO
Repository 🤗	https://huggingface.co/kingabzpro/Llama-3-8B-ORPO
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-04
Maintainer	kingabzpro
Instruction-Based	Yes
Model Files	0.2 GB 4.9 GB 5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	q4\|gguf\|q4_k
Model Architecture	AutoModelForCausalLM
License	apache-2.0
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|im_end\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	k_proj\|gate_proj\|o_proj\|q_proj\|up_proj\|down_proj\|v_proj
LoRA Alpha	32
LoRA Dropout	0.05
R Param	16

Rank the Llama 3 8B ORPO 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 kingabzpro/Llama-3-8B-ORPO.