What are the hardware requirements for Rebekah AI 1.8B?

Rebekah AI 1.8B requires approximately 4 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 Rebekah AI 1.8B and how large is it?

Rebekah AI 1.8B is developed by nextgenaimx, a model with 1.8b 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 Rebekah AI 1.8B?

Rebekah AI 1.8B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Rebekah AI 1.8B by nextgenaimx — VRAM 4GB, 8K context

Name: Rebekah AI 1.8B
Author: nextgenaimx

Rebekah AI 1.8B is an open-source language model by nextgenaimx. Features: 1.8b LLM, VRAM: 4GB, Context: 8K, License: apache-2.0, LLM Explorer Score: 0.32.

Agentic Benchmarks Edge-model En Es Llama Nextgenai Region:us Safetensors Sovereign-ai Tool-use

Model Card on HF 🤗: https://huggingface.co/nextgenaimx/Rebekah-AI-1.8B

Rebekah AI 1.8B Parameters and Internals

LLM Name	Rebekah AI 1.8B
Repository 🤗	https://huggingface.co/nextgenaimx/Rebekah-AI-1.8B
Model Name	Rebekah-AI-1.8B
Model Size	1.8b
Required VRAM	4 GB
Updated	2026-09-23
Maintainer	nextgenaimx
Model Type	llama
Model Files	4.0 GB
Supported Languages	en es
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	8192
Model Max Length	8192
Transformers Version	4.44.0
Tokenizer Class	TokenizersBackend
Padding Token	<pad>
Vocabulary Size	65536
Torch Data Type	bfloat16

Rank the Rebekah AI 1.8B capabilities

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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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