What are the hardware requirements for Llama Chat Summary 3.2 3B GGUF?

Llama Chat Summary 3.2 3B GGUF requires approximately 2 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama Chat Summary 3.2 3B GGUF and how large is it?

Llama Chat Summary 3.2 3B GGUF is developed by prithivMLmods, a model with 3b 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 Chat Summary 3.2 3B GGUF?

Llama Chat Summary 3.2 3B GGUF is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama Chat Summary 3.2 3B GGUF by prithivMLmods — VRAM 2GB

Name: Llama Chat Summary 3.2 3B GGUF
Rating: 4 (1 reviews)
Author: prithivMLmods

Llama Chat Summary 3.2 3B GGUF is an open-source language model by prithivMLmods. Features: 3b LLM, VRAM: 2GB, License: creativeml-openrail-m, Quantized, LLM Explorer Score: 0.16.

Base model:prithivmlmods/llama... Base model:quantized:prithivml... Chat-summary Conversational Dataset:prithivmlmods/context-... En Endpoints compatible Gguf Llama Llama-cpp Ollama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/prithivMLmods/Llama-Chat-Summary-3.2-3B-GGUF

Llama Chat Summary 3.2 3B GGUF Parameters and Internals

LLM Name	Llama Chat Summary 3.2 3B GGUF
Repository 🤗	https://huggingface.co/prithivMLmods/Llama-Chat-Summary-3.2-3B-GGUF
Base Model(s)	prithivMLmods/Llama-Chat-Summary-3.2-3B prithivMLmods/Llama-Chat-Summary-3.2-3B
Model Size	3b
Required VRAM	2 GB
Updated	2026-08-08
Maintainer	prithivMLmods
Model Type	llama
Model Files	6.4 GB 2.0 GB 2.3 GB 3.4 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	AutoModel
License	creativeml-openrail-m

Rank the Llama Chat Summary 3.2 3B GGUF capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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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Note: green Score (e.g. "73.2") means that the model is better than prithivMLmods/Llama-Chat-Summary-3.2-3B-GGUF.