What are the hardware requirements for Llama2.c Stories110M?

Llama2.c Stories110M requires approximately 0.4 GB of VRAM and supports a context window of 1K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama2.c Stories110M and how large is it?

Llama2.c Stories110M is developed by Xenova, a model with 109.5m 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 Llama2.c Stories110M?

Llama2.c Stories110M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama2.c Stories110M by Xenova — VRAM 0.4GB, 1K context

Name: Llama2.c Stories110M
Author: Xenova

Llama2.c Stories110M is an open-source language model by Xenova. Features: 109.5m LLM, VRAM: 0.4GB, Context: 1K, LLM Explorer Score: 0.09.

Deploy:azure Endpoints compatible Llama Onnx Pytorch Region:us Safetensors Transformers.js

Model Card on HF 🤗: https://huggingface.co/Xenova/llama2.c-stories110M

Llama2.c Stories110M Parameters and Internals

Model Type

text-generation

LLM Name	Llama2.c Stories110M
Repository 🤗	https://huggingface.co/Xenova/llama2.c-stories110M
Model Size	109.5m
Required VRAM	0.4 GB
Updated	2026-07-30
Maintainer	Xenova
Model Type	llama
Model Files	0.4 GB 0.4 GB
Model Architecture	LlamaForCausalLM
Context Length	1024
Model Max Length	1024
Transformers Version	4.33.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000

Rank the Llama2.c Stories110M 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 Llama2.c Stories110M

Best Alternatives	Context / RAM	Downloads	Likes
Mia 001	1K / 0.2 GB	141	11

Note: green Score (e.g. "73.2") means that the model is better than Xenova/llama2.c-stories110M.