What are the hardware requirements for Llama 3 8B Claudstruct V3?

Llama 3 8B Claudstruct V3 requires approximately 0.1 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3 8B Claudstruct V3 and how large is it?

Llama 3 8B Claudstruct V3 is developed by jrahn, a model with 8b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Llama 3 8B Claudstruct V3 perform on standard benchmarks?

Llama 3 8B Claudstruct V3 has the following published scores: MMLU 64.55. Compare against reference models on this page or on the LLM Explorer leaderboards.

Llama 3 8B Claudstruct V3 by jrahn — VRAM 0.1GB

Name: Llama 3 8B Claudstruct V3
Author: jrahn

Llama 3 8B Claudstruct V3 is an open-source language model by jrahn. Features: 8b LLM, VRAM: 0.1GB, License: llama3, Instruction-Based, LLM Explorer Score: 0.14, Arc: 59, HellaSwag: 80.1, MMLU: 64.6, GSM8K: 64.2.

4-bit Adapter Base model:adapter:meta-llama/... Base model:meta-llama/meta-lla... Bitsandbytes Dataset:norquinal/claude multi... En Finetuned Generated from trainer Instruct Llama Lora Peft Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/jrahn/llama-3-8b-claudstruct-v3

Llama 3 8B Claudstruct V3 Parameters and Internals

Model Type

LlamaForCausalLM

Additional Notes

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct] on the [Norquinal/claude_multi_instruct_30k] dataset.

Training Details

Data Sources:

Norquinal/claude_multi_instruct_30k

Context Length:

512

Hardware Used:

multi-GPU, 2 devices

LLM Name	Llama 3 8B Claudstruct V3
Repository 🤗	https://huggingface.co/jrahn/llama-3-8b-claudstruct-v3
Base Model(s)	Meta Llama 3 8B Instruct meta-llama/Meta-Llama-3-8B-Instruct
Model Size	8b
Required VRAM	0.1 GB
Updated	2026-07-26
Maintainer	jrahn
Instruction-Based	Yes
Model Files	0.1 GB 0.0 GB
Supported Languages	en
Model Architecture	Adapter
License	llama3
Is Biased	none
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|end_of_text\|>
PEFT Type	LORA
LoRA Model	Yes
PEFT Target Modules	v_proj\|up_proj\|gate_proj\|down_proj\|o_proj\|k_proj\|q_proj
LoRA Alpha	16
LoRA Dropout	0.05
R Param	8

Rank the Llama 3 8B Claudstruct V3 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 jrahn/llama-3-8b-claudstruct-v3.