What are the hardware requirements for Tinyllama Gguf 16B?

Tinyllama Gguf 16B requires approximately 2.2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Tinyllama Gguf 16B and how large is it?

Tinyllama Gguf 16B is developed by abdymazhit, a model with 16b 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 Tinyllama Gguf 16B?

Tinyllama Gguf 16B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Tinyllama Gguf 16B by abdymazhit — VRAM 2.2GB

Name: Tinyllama Gguf 16B
Author: abdymazhit

Tinyllama Gguf 16B is an open-source language model by abdymazhit. Features: 16b LLM, VRAM: 2.2GB, License: apache-2.0, Quantized, LLM Explorer Score: 0.13.

4bit Base model:quantized:unsloth/t... Base model:unsloth/tinyllama-b... En Endpoints compatible Gguf Llama Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/abdymazhit/tinyllama-gguf-16b

Tinyllama Gguf 16B Parameters and Internals

Model Type

text-generation-inference, transformers, gguf

Additional Notes

This llama model was trained 2x faster with [Unsloth](https://github.com/unslothai/unsloth) and Huggingface's TRL library.

Supported Languages

en (supported)

LLM Name	Tinyllama Gguf 16B
Repository 🤗	https://huggingface.co/abdymazhit/tinyllama-gguf-16b
Base Model(s)	Tinyllama Bnb 4bit unsloth/tinyllama-bnb-4bit
Model Size	16b
Required VRAM	2.2 GB
Updated	2026-08-05
Maintainer	abdymazhit
Model Type	llama
Model Files	2.2 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|4bit
Model Architecture	AutoModel
License	apache-2.0

Rank the Tinyllama Gguf 16B 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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