What are the hardware requirements for EverythingLM 13B 16K AWQ?

EverythingLM 13B 16K AWQ requires approximately 7.2 GB of VRAM and supports a context window of 16K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed EverythingLM 13B 16K AWQ and how large is it?

EverythingLM 13B 16K AWQ is developed by TheBloke, a model with 13b 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 EverythingLM 13B 16K AWQ?

EverythingLM 13B 16K AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

EverythingLM 13B 16K AWQ by TheBloke — VRAM 7.2GB, 16K context

Name: EverythingLM 13B 16K AWQ
Author: TheBloke

EverythingLM 13B 16K AWQ is an open-source language model by TheBloke. Features: 13b LLM, VRAM: 7.2GB, Context: 16K, License: llama2, Quantized, LLM Explorer Score: 0.09.

4-bit Awq Base model:quantized:totally-n... Base model:totally-not-an-llm/... Dataset:totally-not-an-llm/eve... Llama Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/TheBloke/EverythingLM-13B-16K-AWQ

EverythingLM 13B 16K AWQ Parameters and Internals

Model Type

llama

Use Cases

Limitations:

Occasionally falls into repetition

Additional Notes

This model is an early test of the EverythingLM dataset and some new experimental principles.

Training Details

Data Sources:

EverythingLM dataset

Methodology:

Training took about 1 hour using QLoRa on 1xA100.

Context Length:

16000

Training Time:

~ cost on 1xA100

Hardware Used:

1xA100

Model Architecture:

llama-2 based, general-purpose 13b model with 16k context thanks to LlongMa.

Input Output

Input Format:

Modified Vicuna format

Accepted Modalities:

text

Output Format:

Verbose and detailed replies

Performance Tips:

Works better with more detailed prompts.

LLM Name	EverythingLM 13B 16K AWQ
Repository 🤗	https://huggingface.co/TheBloke/EverythingLM-13B-16K-AWQ
Model Name	EverythingLM 13B 16K
Model Creator	Kai Howard
Base Model(s)	EverythingLM 13B 16K totally-not-an-llm/EverythingLM-13b-16k
Model Size	13b
Required VRAM	7.2 GB
Updated	2026-06-04
Maintainer	TheBloke
Model Type	llama
Model Files	7.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	LlamaForCausalLM
License	llama2
Context Length	16384
Model Max Length	16384
Transformers Version	4.31.0
Tokenizer Class	LlamaTokenizer
Beginning of Sentence Token	<s>
End of Sentence Token	</s>
Unk Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the EverythingLM 13B 16K AWQ 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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Yarn Llama 2 13B 128K AWQ	128K / 7.2 GB	4	2
LongAlign 13B 64K AWQ	64K / 7.2 GB	4	2
...oboros L2 13B 2 1 YaRN 64K AWQ	64K / 7.2 GB	5	2
OrcaMaid V3 13B 32K AWQ	32K / 7.2 GB	5	4
OrcaMaid V2 FIX 13B 32K AWQ	32K / 7.2 GB	7	1
NexusRaven V2 13B AWQ	16K / 7.2 GB	11	3
NexusRaven V2 13B AWQ	16K / 7.2 GB	1	3
...th CodeLlama 13B Python Hf AWQ	16K / 7.5 GB	6	0
WhiteRabbitNeo 13B AWQ	16K / 7.2 GB	332	4
NexusRaven V2 13B AWQ	16K / 7.2 GB	10	1

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/EverythingLM-13B-16K-AWQ.