What are the hardware requirements for Llama 3.2 1B No Robots GGUF?

Llama 3.2 1B No Robots GGUF 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 1B No Robots GGUF and how large is it?

Llama 3.2 1B No Robots GGUF is developed by shambhuraje, a model with 1b 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 1B No Robots GGUF?

Llama 3.2 1B No Robots GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 3.2 1B No Robots GGUF by shambhuraje — VRAM 0.8GB, 128K context

Name: Llama 3.2 1B No Robots GGUF
Author: shambhuraje

Llama 3.2 1B No Robots GGUF is an open-source language model by shambhuraje. Features: 1b LLM, VRAM: 0.8GB, Context: 128K, License: llama3.2, Quantized, Instruction-Based, LLM Explorer Score: 0.33.

Base model:meta-llama/llama-3.... Base model:quantized:meta-llam... Conversational Dataset:huggingfaceh4/no robot... En Endpoints compatible Gguf Human-like Instruct Llama Qlora Quantized Region:us Unsloth

Model Card on HF 🤗: https://huggingface.co/shambhuraje/Llama-3.2-1B-no-robots-GGUF

Llama 3.2 1B No Robots GGUF Parameters and Internals

LLM Name	Llama 3.2 1B No Robots GGUF
Repository 🤗	https://huggingface.co/shambhuraje/Llama-3.2-1B-no-robots-GGUF
Base Model(s)	meta-llama/Llama-3.2-1B-Instruct meta-llama/Llama-3.2-1B-Instruct
Model Size	1b
Required VRAM	0.8 GB
Updated	2026-11-10
Maintainer	shambhuraje
Model Type	llama
Instruction-Based	Yes
Model Files	0.8 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	LlamaForCausalLM
License	llama3.2
Context Length	131072
Model Max Length	131072
Transformers Version	5.5.0
Vocabulary Size	128256
Torch Data Type	bfloat16

Rank the Llama 3.2 1B No Robots GGUF 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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