What are the hardware requirements for Nous Hermes 2 Mixtral 8x7B DPO GPTQ?

Nous Hermes 2 Mixtral 8x7B DPO GPTQ requires approximately 23.8 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 Nous Hermes 2 Mixtral 8x7B DPO GPTQ and how large is it?

Nous Hermes 2 Mixtral 8x7B DPO GPTQ is developed by TheBloke, a model with 46.7b 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 Nous Hermes 2 Mixtral 8x7B DPO GPTQ?

Nous Hermes 2 Mixtral 8x7B DPO GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Nous Hermes 2 Mixtral 8x7B DPO GPTQ by TheBloke — VRAM 23.8GB, 32K context

Name: Nous Hermes 2 Mixtral 8x7B DPO GPTQ
Author: TheBloke

Nous Hermes 2 Mixtral 8x7B DPO GPTQ is an open-source language model by TheBloke. Features: 46.7b LLM, VRAM: 23.8GB, Context: 32K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.11.

4-bit Base model:nousresearch/nous-h... Base model:quantized:nousresea... Chatml Conversational Distillation Dpo En Finetuned Gpt4 Gptq Instruct Mixtral Moe Quantized Region:us Rlhf Safetensors Synthetic data

Model Card on HF 🤗: https://huggingface.co/TheBloke/Nous-Hermes-2-Mixtral-8x7B-DPO-GPTQ

Nous Hermes 2 Mixtral 8x7B DPO GPTQ Parameters and Internals

LLM Name	Nous Hermes 2 Mixtral 8x7B DPO GPTQ
Repository 🤗	https://huggingface.co/TheBloke/Nous-Hermes-2-Mixtral-8x7B-DPO-GPTQ
Model Name	Nous Hermes 2 Mixtral 8X7B DPO
Model Creator	NousResearch
Base Model(s)	Nous Hermes 2 Mixtral 8x7B DPO NousResearch/Nous-Hermes-2-Mixtral-8x7B-DPO
Model Size	46.7b
Required VRAM	23.8 GB
Updated	2026-06-08
Maintainer	TheBloke
Model Type	mixtral
Model Files	23.8 GB
Supported Languages	en
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.37.0.dev0
Tokenizer Class	LlamaTokenizer
Padding Token	</s>
Vocabulary Size	32002
Torch Data Type	bfloat16

Rank the Nous Hermes 2 Mixtral 8x7B DPO GPTQ 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

Best Alternatives to Nous Hermes 2 Mixtral 8x7B DPO GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Mixtral 8x7B V0.1 GPTQ	32K / 23.8 GB	181	126
...ixtral 8x7B Instruct V0.1 GPTQ	32K / 23.8 GB	210	141
...Hermes 2 Mixtral 8x7B SFT GPTQ	32K / 23.8 GB	10	11
Dolphin 2.5 Mixtral 8x7b GPTQ	32K / 23.8 GB	81	114
Bagel DPO 8x7b V0.2 GPTQ	32K / 23.8 GB	12	2
Open Gpt4 8x7B V0.2 GPTQ	32K / 23.8 GB	9	6
...xtral Instruct 8x7b Zloss GPTQ	32K / 23.8 GB	7	2
Sensualize Mixtral GPTQ	32K / 23.8 GB	9	5
....1 LimaRP ZLoss DARE TIES GPTQ	32K / 23.8 GB	5	6
Dolphin 2.7 Mixtral 8x7b GPTQ	32K / 23.8 GB	32	19

Note: green Score (e.g. "73.2") means that the model is better than TheBloke/Nous-Hermes-2-Mixtral-8x7B-DPO-GPTQ.