What are the hardware requirements for BBAIIFEV1?

BBAIIFEV1 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 BBAIIFEV1 and how large is it?

BBAIIFEV1 is developed by Amaorynho, 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 BBAIIFEV1?

BBAIIFEV1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

BBAIIFEV1 by Amaorynho — VRAM 16.1GB, 128K context

Name: BBAIIFEV1
Author: Amaorynho

BBAIIFEV1 is an open-source language model by Amaorynho. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, Merged, LLM Explorer Score: 0.25.

Merged Model Arxiv:2403.19522 Base model:akjindal53244/llama... Base model:nexesenex/llama 3.1... Base model:nexesenex/llama 3.1... Conversational Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/Amaorynho/BBAIIFEV1

BBAIIFEV1 Parameters and Internals

LLM Name	BBAIIFEV1
Repository 🤗	https://huggingface.co/Amaorynho/BBAIIFEV1
Base Model(s)	Nexesenex/Llama_3.1_8b_DodoWild_v2.10 akjindal53244/Llama-3.1-Storm-8B Nexesenex/Llama_3.1_8b_Typhoon_v1.03 Nexesenex/Llama_3.1_8b_DodoWild_v2.10 akjindal53244/Llama-3.1-Storm-8B Nexesenex/Llama_3.1_8b_Typhoon_v1.03
Merged Model	Yes
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-25
Maintainer	Amaorynho
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
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|end_of_text\|>
Vocabulary Size	128266
Torch Data Type	bfloat16

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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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