What are the hardware requirements for Shortstories20M?

Shortstories20M requires approximately 0.1 GB of VRAM and supports a context window of 0.3K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Shortstories20M and how large is it?

Shortstories20M is developed by gargabhi, a model with 20.4m 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 Shortstories20M?

Shortstories20M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Shortstories20M by gargabhi — VRAM 0.1GB, 0.3K context

Name: Shortstories20M
Author: gargabhi

Shortstories20M is an open-source language model by gargabhi. Features: 20.4m LLM, VRAM: 0.1GB, Context: 0.3K, LLM Explorer Score: 0.12.

Arxiv:1910.09700 Endpoints compatible Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/gargabhi/shortstories20M

Shortstories20M Parameters and Internals

LLM Name	Shortstories20M
Repository 🤗	https://huggingface.co/gargabhi/shortstories20M
Model Size	20.4m
Required VRAM	0.1 GB
Updated	2026-07-22
Maintainer	gargabhi
Model Type	llama
Model Files	0.1 GB
Model Architecture	LlamaForCausalLM
Context Length	350
Model Max Length	350
Transformers Version	4.40.2
Tokenizer Class	GPT2Tokenizer
Vocabulary Size	50257
Torch Data Type	float32

Rank the Shortstories20M 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

Best Alternatives to Shortstories20M

Best Alternatives	Context / RAM	Downloads	Likes
Shortrecipes20M	0.3K / 0.1 GB	5	0
Tavik 1	1K / 0 GB	86	0

Note: green Score (e.g. "73.2") means that the model is better than gargabhi/shortstories20M.