What are the hardware requirements for OpenHermes 2.5 Mistral 7B Marlin?

OpenHermes 2.5 Mistral 7B Marlin requires approximately 4.1 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 OpenHermes 2.5 Mistral 7B Marlin and how large is it?

OpenHermes 2.5 Mistral 7B Marlin is developed by RedHatAI, 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 OpenHermes 2.5 Mistral 7B Marlin perform on standard benchmarks?

OpenHermes 2.5 Mistral 7B Marlin has the following published scores: MMLU 63.82, LMSYS ELO 1074. Compare against reference models on this page or on the LLM Explorer leaderboards.

OpenHermes 2.5 Mistral 7B Marlin by RedHatAI — VRAM 4.1GB, 32K context

Name: OpenHermes 2.5 Mistral 7B Marlin
Author: RedHatAI

OpenHermes 2.5 Mistral 7B Marlin is an open-source language model by RedHatAI. Features: 7b LLM, VRAM: 4.1GB, Context: 32K, Quantized, LLM Explorer Score: 0.24, ELO: 1074, Arc: 64.9, HellaSwag: 84.3, MMLU: 63.8, GSM8K: 25.5.

Arxiv:2210.17323 4-bit Base model:quantized:teknium/o... Base model:teknium/openhermes-... Conversational Endpoints compatible Gptq Int4 Marlin Mistral Nm-vllm Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/RedHatAI/OpenHermes-2.5-Mistral-7B-marlin

OpenHermes 2.5 Mistral 7B Marlin Benchmarks

LMSys ELO 1074 vs 1272 (so35) -15.6%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

OpenHermes 2.5 Mistral 7B Marlin Parameters and Internals

LLM Name	OpenHermes 2.5 Mistral 7B Marlin
Repository 🤗	https://huggingface.co/RedHatAI/OpenHermes-2.5-Mistral-7B-marlin
Base Model(s)	teknium/OpenHermes-2.5-Mistral-7B teknium/OpenHermes-2.5-Mistral-7B
Model Size	7b
Required VRAM	4.1 GB
Updated	2026-08-01
Maintainer	RedHatAI
Model Type	mistral
Model Files	4.1 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32002
Torch Data Type	float16

Rank the OpenHermes 2.5 Mistral 7B Marlin 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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