What are the hardware requirements for Llama2SWA512?

Llama2SWA512 requires approximately 2.5 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 Llama2SWA512 and how large is it?

Llama2SWA512 is developed by Maxtimer97, 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 Llama2SWA512?

Llama2SWA512 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama2SWA512 by Maxtimer97 — VRAM 2.5GB, 128K context

Name: Llama2SWA512
Author: Maxtimer97

Llama2SWA512 is an open-source language model by Maxtimer97. Features: 1.2b LLM, VRAM: 2.5GB, Context: 128K, LLM Explorer Score: 0.19.

Arxiv:1910.09700 Conversational Custom code Hymba Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Maxtimer97/Llama2SWA512

Llama2SWA512 Parameters and Internals

LLM Name	Llama2SWA512
Repository 🤗	https://huggingface.co/Maxtimer97/Llama2SWA512
Model Size	1.2b
Required VRAM	2.5 GB
Updated	2026-07-30
Maintainer	Maxtimer97
Model Type	hymba
Model Files	2.5 GB
Model Architecture	HymbaForCausalLM
Context Length	131072
Model Max Length	131072
Transformers Version	4.53.0
Tokenizer Class	PreTrainedTokenizerFast
Vocabulary Size	128256
Torch Data Type	bfloat16

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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
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Multi-Language Support and Translation

Best Alternatives to Llama2SWA512

Best Alternatives	Context / RAM	Downloads	Likes
Llama2SWA	128K / 2.5 GB	8	0