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

Yarn Mistral 7B 128K requires approximately 14.4 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 and how large is it?

Yarn Mistral 7B 128K is developed by NousResearch, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Yarn Mistral 7B 128K perform on standard benchmarks?

Yarn Mistral 7B 128K has the following published scores: MMLU 63.02. Compare against reference models on this page or on the LLM Explorer leaderboards.

Yarn Mistral 7B 128K by NousResearch — VRAM 14.4GB, 32K context

Name: Yarn Mistral 7B 128K
Author: NousResearch

Yarn Mistral 7B 128K is an open-source language model by NousResearch. Features: 7b LLM, VRAM: 14.4GB, Context: 32K, License: apache-2.0, LLM Explorer Score: 0.19, Arc: 59.6, HellaSwag: 82.5, MMLU: 63, GSM8K: 32.6.

Arxiv:2309.00071 Custom code Dataset:emozilla/yarn-train-to... En Endpoints compatible Mistral Pytorch Region:us Sharded Yarn

Model Card on HF 🤗: https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k

Yarn Mistral 7B 128K Parameters and Internals

Model Type

language model

Supported Languages

en (Fluent)

Training Details

Data Sources:

emozi/ya-rn-train-tokenized-16k-mistral

Methodology:

YaRN extension method

Context Length:

128000

Training Time:

1500 steps

Input Output

Accepted Modalities:

text

LLM Name	Yarn Mistral 7B 128K
Repository 🤗	https://huggingface.co/NousResearch/Yarn-Mistral-7b-128k
Model Size	7b
Required VRAM	14.4 GB
Updated	2026-05-21
Maintainer	NousResearch
Model Type	mistral
Model Files	9.9 GB: 1-of-2 4.5 GB: 2-of-2
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Yarn Mistral 7B 128K capabilities

Have you tried this model? Rate its performance — this feedback helps the ML community find the right model for their needs.

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

Quantized Models of the Yarn Mistral 7B 128K

Model	Likes	Downloads	VRAM
Yarn Mistral 7B 128K GGUF	131	1701	3 GB
Yarn Mistral 7B 128K AWQ	72	81	4 GB
Yarn Mistral 7B 128K GPTQ	13	42	4 GB

Best Alternatives to Yarn Mistral 7B 128K

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

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