What are the hardware requirements for Nous Hermes 2 Mixtral 8x7B SFT GGUF?

Nous Hermes 2 Mixtral 8x7B SFT GGUF requires approximately 17.3 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 SFT GGUF and how large is it?

Nous Hermes 2 Mixtral 8x7B SFT GGUF is developed by second-state. 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 SFT GGUF?

Nous Hermes 2 Mixtral 8x7B SFT GGUF 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 SFT GGUF by second-state — VRAM 17.3GB, 32K context

Name: Nous Hermes 2 Mixtral 8x7B SFT GGUF
Author: second-state

Nous Hermes 2 Mixtral 8x7B SFT GGUF is an open-source language model by second-state. Features: LLM, VRAM: 17.3GB, Context: 32K, License: apache-2.0, MoE, Quantized, LLM Explorer Score: 0.11.

Base model:nousresearch/nous-h... Base model:quantized:nousresea... Chatml Conversational Distillation Dpo En Finetuned Gguf Gpt4 Instruct Mixtral Moe Q2 Quantized Region:us Rlhf Synthetic data

Model Card on HF 🤗: https://huggingface.co/second-state/Nous-Hermes-2-Mixtral-8x7B-SFT-GGUF

Nous Hermes 2 Mixtral 8x7B SFT GGUF Parameters and Internals

Model Type

mixtral

Additional Notes

Quantized by Second State Inc. - The model has undergone quantization to multiple versions, such as Q2_K, Q3_K_L, Q3_K_M, Q3_K_S, Q4_0, Q4_K_M, Q4_K_S, Q5_0, Q5_K_M, Q5_K_S, Q6_K, and Q8_0, each having different bits and size specifications for various use cases.

Supported Languages

en (full)

LLM Name	Nous Hermes 2 Mixtral 8x7B SFT GGUF
Repository 🤗	https://huggingface.co/second-state/Nous-Hermes-2-Mixtral-8x7B-SFT-GGUF
Model Name	Nous Hermes 2 Mixtral 8X7B SFT
Model Creator	NousResearch
Base Model(s)	Nous Hermes 2 Mixtral 8x7B SFT NousResearch/Nous-Hermes-2-Mixtral-8x7B-SFT
Required VRAM	17.3 GB
Updated	2026-08-08
Maintainer	second-state
Model Type	mixtral
Model Files	17.3 GB 24.2 GB 22.5 GB 20.4 GB 26.4 GB 28.4 GB 26.7 GB 32.2 GB 33.2 GB 32.2 GB 38.4 GB 49.6 GB
Supported Languages	en
GGUF Quantization	Yes
Quantization Type	gguf\|q2\|q4_k\|q5_k
Model Architecture	MixtralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.0.dev0
Vocabulary Size	32002
Torch Data Type	bfloat16

Rank the Nous Hermes 2 Mixtral 8x7B SFT GGUF 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 SFT GGUF

Best Alternatives	Context / RAM	Downloads	Likes
WizardLM2 2bit	64K / 4.8 GB	155	0
NebulaNet V2 4x7B MoE	32K / 8.8 GB	131	4
Dolphin 2.7 Mixtral 8x7b GGUF	32K / 15.6 GB	1162	5
Cerebrum 1.0 8x7b GGUF	32K / 17.3 GB	18	1
...ixtral 8x7B Instruct V0.1 GGUF	32K / 17.3 GB	507	5
...Hermes 2 Mixtral 8x7B DPO GGUF	32K / 17.3 GB	277	2
...oE V0.1 DPO F16 4.0bpw H6 EXL2	195K / 31.3 GB	7	0
...oE V0.1 DPO F16 5.0bpw H6 EXL2	195K / 38.8 GB	6	0
...2 Mixtral 8x22b 6.0bpw H8 EXL2	64K / 105.8 GB	2	1
WizardLM 2 8x22 EXL2 4.0bpw	64K / 70.9 GB	7	1

Note: green Score (e.g. "73.2") means that the model is better than second-state/Nous-Hermes-2-Mixtral-8x7B-SFT-GGUF.