What are the hardware requirements for Reverx 1 100M?

Reverx 1 100M requires approximately 0.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Reverx 1 100M and how large is it?

Reverx 1 100M is developed by Cortiqa, a model with 100m 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 Reverx 1 100M?

Reverx 1 100M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Reverx 1 100M by Cortiqa — VRAM 0.4GB

Name: Reverx 1 100M
Author: Cortiqa

Reverx 1 100M is an open-source language model by Cortiqa. Features: 100m LLM, VRAM: 0.4GB, License: mit, LLM Explorer Score: 0.33.

Arxiv:1707.04585 Arxiv:2001.04451 Cortiqa Dataset:tatsu-lab/alpaca En Pytorch Reformer Region:us Reversible-transformer Reverx Revnet

Model Card on HF 🤗: https://huggingface.co/Cortiqa/reverx-1-100m

Reverx 1 100M Parameters and Internals

LLM Name	Reverx 1 100M
Repository 🤗	https://huggingface.co/Cortiqa/reverx-1-100m
Model Size	100m
Required VRAM	0.4 GB
Updated	2026-09-28
Maintainer	Cortiqa
Model Type	reverx
Model Files	0.4 GB
Supported Languages	en
Model Architecture	ReverX100M
License	mit
Vocabulary Size	50257
Torch Data Type	float32

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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