What are the hardware requirements for WIBA Extract V1?

WIBA Extract V1 requires approximately 6.1 GB of VRAM and supports a context window of 8K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed WIBA Extract V1 and how large is it?

WIBA Extract V1 is developed by armaniii, 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 WIBA Extract V1?

WIBA Extract V1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

WIBA Extract V1 by armaniii — VRAM 6.1GB, 8K context

Name: WIBA Extract V1
Author: armaniii

WIBA Extract V1 is an open-source language model by armaniii. Features: 8b LLM, VRAM: 6.1GB, Context: 8K, License: llama3, LLM Explorer Score: 0.12.

Arxiv:2405.00828 4-bit Argument-mining Base model:meta-llama/meta-lla... Base model:quantized:meta-llam... Bitsandbytes Claim-extraction Computational-social-science Conversational En Endpoints compatible Llama Region:us Safetensors Sharded Tensorflow Topic-extraction Wiba

Model Card on HF 🤗: https://huggingface.co/armaniii/WIBA-Extract-V1

WIBA Extract V1 Parameters and Internals

LLM Name	WIBA Extract V1
Repository 🤗	https://huggingface.co/armaniii/WIBA-Extract-V1
Base Model(s)	Meta Llama 3 8B meta-llama/Meta-Llama-3-8B
Model Size	8b
Required VRAM	6.1 GB
Updated	2026-08-04
Maintainer	armaniii
Model Type	llama
Model Files	5.0 GB: 1-of-2 1.1 GB: 2-of-2
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	llama3
Context Length	8192
Model Max Length	8192
Transformers Version	4.37.0
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	ĠINC
Vocabulary Size	128256
Torch Data Type	float16

Rank the WIBA Extract V1 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

Best Alternatives to WIBA Extract V1

Best Alternatives	Context / RAM	Downloads	Likes
...otron 8B UltraLong 4M Instruct	4192K / 32.1 GB	1135	125
UltraLong Thinking	4192K / 16.1 GB	2	3
...a 3.1 8B UltraLong 4M Instruct	4192K / 32.1 GB	176	24
...a 3.1 8B UltraLong 2M Instruct	2096K / 32.1 GB	875	9
...otron 8B UltraLong 2M Instruct	2096K / 32.1 GB	124	18
Cthulhu 8B V1.4	1048K / 16.1 GB	10	10
...raLong 1M Instruct Abliterated	1048K / 32.1 GB	4	9
...a 3.1 8B UltraLong 1M Instruct	1048K / 32.1 GB	1387	29
...otron 8B UltraLong 1M Instruct	1048K / 32.1 GB	702	59
...xis Bookwriter Llama3.1 8B Sft	1048K / 16.1 GB	25	4

Note: green Score (e.g. "73.2") means that the model is better than armaniii/WIBA-Extract-V1.