What are the hardware requirements for Llama 3.2.Instruct Q4 K M?

Llama 3.2.Instruct Q4 K M requires approximately 0.8 GB of VRAM and supports a context window of 128K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 3.2.Instruct Q4 K M and how large is it?

Llama 3.2.Instruct Q4 K M is developed by uonyeka, a model with 1.2b 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 Llama 3.2.Instruct Q4 K M?

Llama 3.2.Instruct Q4 K M is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.2.Instruct Q4 K M by uonyeka — VRAM 0.8GB, 128K context

Name: Llama 3.2.Instruct Q4 K M
Author: uonyeka

Llama 3.2.Instruct Q4 K M is an open-source language model by uonyeka. Features: 1.2b LLM, VRAM: 0.8GB, Context: 128K, Quantized, Merged, LLM Explorer Score: 0.15.

Merged Model Arxiv:1910.09700 Conversational Endpoints compatible Ggml Gguf Llama Q4 Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/uonyeka/llama-3.2.Instruct_q4_k_m

Llama 3.2.Instruct Q4 K M Parameters and Internals

LLM Name	Llama 3.2.Instruct Q4 K M
Repository 🤗	https://huggingface.co/uonyeka/llama-3.2.Instruct_q4_k_m
Merged Model	Yes
Model Size	1.2b
Required VRAM	0.8 GB
Updated	2026-07-30
Maintainer	uonyeka
Model Type	llama
Model Files	0.8 GB 4.9 GB 2.5 GB
GGML Quantization	Yes
GGUF Quantization	Yes
Quantization Type	gguf\|ggml\|q4\|q4_k
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.47.0.dev0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	float32

Rank the Llama 3.2.Instruct Q4 K M 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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Mynewbrain V1	128K / 2.5 GB	472	1
LYRA LLAMA	128K / 2.5 GB	426	3
Augmented 8a3f84c4cc4a7528	128K / 2.5 GB	286	0
Mazgu Llama V3 Merged	128K / 2.5 GB	301	0
Assn2 Sft Train5	128K / 2.5 GB	7	0
Zay Llama1b DPO Harmful PathD	128K / 2.5 GB	1	1
Akshar Nano V2	128K / 2.5 GB	15	0
Akshar Nano	128K / 2.5 GB	10	0
Second Tts Try	128K / 2.5 GB	39	0
...18 27e6 491c B3ab Ea03a5b93541	128K / 4.9 GB	10	0

Note: green Score (e.g. "73.2") means that the model is better than uonyeka/llama-3.2.Instruct_q4_k_m.