What are the hardware requirements for Llama3.1 Aloe Beta 8B?

Llama3.1 Aloe Beta 8B requires approximately 16.1 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama3.1 Aloe Beta 8B and how large is it?

Llama3.1 Aloe Beta 8B is developed by HPAI-BSC, 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 Llama3.1 Aloe Beta 8B?

Llama3.1 Aloe Beta 8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3.1 Aloe Beta 8B by HPAI-BSC — VRAM 16.1GB, 128K context

Name: Llama3.1 Aloe Beta 8B
Author: HPAI-BSC

Llama3.1 Aloe Beta 8B is an open-source language model by HPAI-BSC. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: cc-by-nc-4.0, Merged, LLM Explorer Score: 0.24.

Merged Model Arxiv:2505.04388 Biology Dataset:hpai-bsc/aloe-beta-gen... Dataset:hpai-bsc/chain-of-diag... Dataset:hpai-bsc/headqa-cot-ll... Dataset:hpai-bsc/medmcqa-cot-l... Dataset:hpai-bsc/medqa-cot-lla... Dataset:hpai-bsc/meds-ins Dataset:hpai-bsc/mmlu-medical-... Dataset:hpai-bsc/polymed-qa Dataset:hpai-bsc/pubmedqa-cot-... Dataset:hpai-bsc/ultramedical En Endpoints compatible Healthcare Instruct Llama Medical Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/HPAI-BSC/Llama3.1-Aloe-Beta-8B

Llama3.1 Aloe Beta 8B Parameters and Internals

Model Type

Causal decoder-only transformer language model

Supported Languages

English (capable but not formally evaluated on other languages)

Training Details

Data Sources:

HPAI-BSC/Aloe-Beta-General-Collection, HPAI-BSC/chain-of-diagnosis, HPAI-BSC/MedS-Ins, HPAI-BSC/ultramedical, HPAI-BSC/pubmedqa-cot-llama31, HPAI-BSC/medqa-cot-llama31, HPAI-BSC/medmcqa-cot-llama31, HPAI-BSC/headqa-cot-llama31, HPAI-BSC/MMLU-medical-cot-llama31, HPAI-BSC/Polymed-QA

Data Volume:

1.8B tokens

Methodology:

Fine-tuning on Llama 3.1 using axolotl. Deepspeed Zero-3 distributed training.

Context Length:

16384

Hardware Used:

32x NVIDIA Hopper H100 64GB for 8B, 64x NVIDIA Hopper H100 64GB for 70B

LLM Name	Llama3.1 Aloe Beta 8B
Repository 🤗	https://huggingface.co/HPAI-BSC/Llama3.1-Aloe-Beta-8B
Merged Model	Yes
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-04-26
Maintainer	HPAI-BSC
Model Type	llama
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
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	cc-by-nc-4.0
Context Length	131072
Model Max Length	131072
Transformers Version	4.46.1
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	bfloat16

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