What are the hardware requirements for Llama3.2 BLChat 3B Pretrained?

Llama3.2 BLChat 3B Pretrained requires approximately 7.2 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 Llama3.2 BLChat 3B Pretrained and how large is it?

Llama3.2 BLChat 3B Pretrained is developed by baesad, 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 Llama3.2 BLChat 3B Pretrained?

Llama3.2 BLChat 3B Pretrained is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3.2 BLChat 3B Pretrained by baesad — VRAM 7.2GB, 128K context

Name: Llama3.2 BLChat 3B Pretrained
Author: baesad

Llama3.2 BLChat 3B Pretrained is an open-source language model by baesad. Features: 3b LLM, VRAM: 7.2GB, Context: 128K, Quantized, Instruction-Based, LLM Explorer Score: 0.16.

Arxiv:1910.09700 4bit Conversational Endpoints compatible Instruct Llama Pytorch Quantized Region:us Sft Sharded Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/baesad/Llama3.2-BLChat-3B-pretrained

Llama3.2 BLChat 3B Pretrained Parameters and Internals

LLM Name	Llama3.2 BLChat 3B Pretrained
Repository 🤗	https://huggingface.co/baesad/Llama3.2-BLChat-3B-pretrained
Model Size	3b
Required VRAM	7.2 GB
Updated	2026-08-08
Maintainer	baesad
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 2.2 GB: 2-of-2
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.2
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama3.2 BLChat 3B Pretrained 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 baesad/Llama3.2-BLChat-3B-pretrained.