What are the hardware requirements for Rune 0.3B Base?

Rune 0.3B Base requires approximately 1.4 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Rune 0.3B Base and how large is it?

Rune 0.3B Base is developed by samueljayasingh, a model with 0.3b 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 Rune 0.3B Base?

Rune 0.3B Base is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Rune 0.3B Base by samueljayasingh — VRAM 1.4GB

Name: Rune 0.3B Base
Rating: 2.75 (8 reviews)
Author: samueljayasingh

Rune 0.3B Base is an open-source language model by samueljayasingh. Features: 0.3b LLM, VRAM: 1.4GB, License: apache-2.0, LLM Explorer Score: 0.27.

Dataset:huggingfacefw/fineweb-... En From-scratch Pytorch Region:us Rune-r1 Safetensors

Model Card on HF 🤗: https://huggingface.co/samueljayasingh/rune-0.3b-base

Rune 0.3B Base Parameters and Internals

LLM Name	Rune 0.3B Base
Repository 🤗	https://huggingface.co/samueljayasingh/rune-0.3b-base
Model Size	0.3b
Required VRAM	1.4 GB
Updated	2026-08-03
Maintainer	samueljayasingh
Model Files	1.4 GB 1.4 GB
Supported Languages	en
License	apache-2.0
Vocabulary Size	50257

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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