What are the hardware requirements for Llama3.1 8B Text2cypher?

Llama3.1 8B Text2cypher requires approximately 16.1 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 Llama3.1 8B Text2cypher and how large is it?

Llama3.1 8B Text2cypher is developed by Azzedde, a model with 8b 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 Llama3.1 8B Text2cypher?

Llama3.1 8B Text2cypher is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Llama3.1 8B Text2cypher by Azzedde — VRAM 16.1GB, 128K context

Name: Llama3.1 8B Text2cypher
Author: Azzedde

Llama3.1 8B Text2cypher is an open-source language model by Azzedde. Features: 8b LLM, VRAM: 16.1GB, Context: 128K, License: mit, Quantized, Instruction-Based, LLM Explorer Score: 0.17.

4bit Base model:finetune:unsloth/ll... Base model:unsloth/llama-3.1-8... Conversational Dataset:neo4j/text2cypher-2024... En Endpoints compatible Instruct Llama Pytorch Quantized Region:us Sft Sharded Trl Unsloth

Model Card on HF 🤗: https://huggingface.co/Azzedde/llama3.1-8b-text2cypher

Llama3.1 8B Text2cypher Parameters and Internals

LLM Name	Llama3.1 8B Text2cypher
Repository 🤗	https://huggingface.co/Azzedde/llama3.1-8b-text2cypher
Base Model(s)	unsloth/Llama-3.1-8B-Instruct unsloth/Llama-3.1-8B-Instruct
Model Size	8b
Required VRAM	16.1 GB
Updated	2026-08-25
Maintainer	Azzedde
Model Type	llama
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-4 5.0 GB: 2-of-4 4.9 GB: 3-of-4 1.2 GB: 4-of-4
Supported Languages	en
Quantization Type	4bit
Model Architecture	LlamaForCausalLM
License	mit
Context Length	131072
Model Max Length	131072
Transformers Version	4.48.3
Tokenizer Class	PreTrainedTokenizerFast
Padding Token	<\|finetune_right_pad_id\|>
Vocabulary Size	128256
Torch Data Type	float16

Rank the Llama3.1 8B Text2cypher 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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...B Instruct Gradient 1048K 4bit	1024K / 4.5 GB	10	2
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Llama 3 8B Instruct 1048K 8bit	1024K / 8.6 GB	213	17
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...B Instruct 262k V2 EXL2 5.0bpw	256K / 5.8 GB	5	1