What are the hardware requirements for Llama 43M Beta?

Llama 43M Beta requires approximately 0.2 GB of VRAM and supports a context window of 2K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Llama 43M Beta and how large is it?

Llama 43M Beta is developed by cpayne1303, a model with 68m 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 43M Beta?

Llama 43M Beta is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama 43M Beta by cpayne1303 — VRAM 0.2GB, 2K context

Name: Llama 43M Beta
Author: cpayne1303

Llama 43M Beta is an open-source language model by cpayne1303. Features: 68m LLM, VRAM: 0.2GB, Context: 2K, License: apache-2.0, LLM Explorer Score: 0.17.

Base model:finetune:jackfram/l... Base model:jackfram/llama-68m Conversational Dataset:allenai/c4 En Endpoints compatible Llama Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/cpayne1303/llama-43m-beta

Llama 43M Beta Parameters and Internals

LLM Name	Llama 43M Beta
Repository 🤗	https://huggingface.co/cpayne1303/llama-43m-beta
Base Model(s)	Llama 68M JackFram/llama-68m
Model Size	68m
Required VRAM	0.2 GB
Updated	2026-05-09
Maintainer	cpayne1303
Model Type	llama
Model Files	0.2 GB
Supported Languages	en
Model Architecture	LlamaForCausalLM
License	apache-2.0
Context Length	2048
Model Max Length	2048
Transformers Version	4.45.1
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32000
Torch Data Type	float32

Rank the Llama 43M Beta 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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