What are the hardware requirements for Yarn Mistral 7B 128K AWQ?

Yarn Mistral 7B 128K AWQ requires approximately 4.2 GB of VRAM and supports a context window of 32K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Yarn Mistral 7B 128K AWQ and how large is it?

Yarn Mistral 7B 128K AWQ is developed by TheBloke, a model with 7b 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 Yarn Mistral 7B 128K AWQ?

Yarn Mistral 7B 128K AWQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Yarn Mistral 7B 128K AWQ by TheBloke — VRAM 4.2GB, 32K context

Name: Yarn Mistral 7B 128K AWQ
Author: TheBloke

Yarn Mistral 7B 128K AWQ is an open-source language model by TheBloke. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.1.

Arxiv:2309.00071 4-bit Awq Base model:nousresearch/yarn-m... Base model:quantized:nousresea... Custom code Dataset:emozilla/yarn-train-to... En Mistral Quantized Region:us Safetensors Yarn

Model Card on HF 🤗: https://huggingface.co/TheBloke/Yarn-Mistral-7B-128k-AWQ

Yarn Mistral 7B 128K AWQ Parameters and Internals

Model Type

mistral

Additional Notes

AWQ quantization method supports efficient 4-bit weight quantization. Special thanks to various sponsors for compute support.

Supported Languages

en (full)

Training Details

Data Sources:

iostreamzloma/yarn-train-tokenized-16k-mistral

Methodology:

further pretrained on long context data for 1500 steps using the YaRN extension method

Context Length:

128000

Training Time:

unknown

Hardware Used:

JUWELS supercomputer at LAION AI

Model Architecture:

An extension of Mistral-7B-v0.1 supporting a 128k token context window

Input Output

Input Format:

{prompt}

Accepted Modalities:

text

Output Format:

generated text

Performance Tips:

Use trust_remote_code=True when loading the model

LLM Name	Yarn Mistral 7B 128K AWQ
Repository 🤗	https://huggingface.co/TheBloke/Yarn-Mistral-7B-128k-AWQ
Model Name	Yarn Mistral 7B 128K
Model Creator	NousResearch
Base Model(s)	Yarn Mistral 7B 128K NousResearch/Yarn-Mistral-7b-128k
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-08-03
Maintainer	TheBloke
Model Type	mistral
Model Files	4.2 GB
Supported Languages	en
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Yarn Mistral 7B 128K 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

Best Alternatives to Yarn Mistral 7B 128K AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	6	0
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	298182	52
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5633	10
Mistral 7B Instruct V0.1 AWQ	32K / 4.2 GB	15461	2
Ghost 7B Alpha AWQ	32K / 4.2 GB	14	0
Tess 7B V2.0 AWQ	32K / 4.2 GB	1	1
OpenHermes 2.5 Mistral 7B AWQ	32K / 4.2 GB	23691	21
...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	5	0
NSFW DPO Noromaid 7B AWQ	32K / 4.2 GB	206	2

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Yarn-Mistral-7B-128k-AWQ.