What are the hardware requirements for OpenHermes 2.5 Mistral 7B Mlx 4bit?

OpenHermes 2.5 Mistral 7B Mlx 4bit requires approximately 4.3 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 OpenHermes 2.5 Mistral 7B Mlx 4bit and how large is it?

OpenHermes 2.5 Mistral 7B Mlx 4bit is developed by cogbuji, 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 OpenHermes 2.5 Mistral 7B Mlx 4bit?

OpenHermes 2.5 Mistral 7B Mlx 4bit is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

OpenHermes 2.5 Mistral 7B Mlx 4bit by cogbuji — VRAM 4.3GB, 32K context

Name: OpenHermes 2.5 Mistral 7B Mlx 4bit
Author: cogbuji

OpenHermes 2.5 Mistral 7B Mlx 4bit is an open-source language model by cogbuji. Features: 7b LLM, VRAM: 4.3GB, Context: 32K, License: apache-2.0, Quantized, LLM Explorer Score: 0.11.

4bit Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Chatml Dataset:teknium/openhermes-2.5 Distillation En Finetuned Gpt4 Instruct Mistral Mlx Quantized Region:us Safetensors Synthetic data

Model Card on HF 🤗: https://huggingface.co/cogbuji/OpenHermes-2.5-Mistral-7B-mlx-4bit

OpenHermes 2.5 Mistral 7B Mlx 4bit Parameters and Internals

Model Type

instruct, finetune, chatml, gpt4, synthetic data, distillation, mlx

Additional Notes

This model was converted to MLX format from teknium/OpenHermes-2.5-Mistral-7B and quantized to 4-bit format. It should be used with the specified versions of mlx and mlx_lm as later versions may deprecate this model.

LLM Name	OpenHermes 2.5 Mistral 7B Mlx 4bit
Repository 🤗	https://huggingface.co/cogbuji/OpenHermes-2.5-Mistral-7B-mlx-4bit
Base Model(s)	mistralai/Mistral-7B-v0.1 mistralai/Mistral-7B-v0.1
Model Size	7b
Required VRAM	4.3 GB
Updated	2026-08-06
Maintainer	cogbuji
Model Type	mistral
Model Files	4.3 GB 4.3 GB
Supported Languages	en
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.1
Vocabulary Size	32002
Torch Data Type	bfloat16

Rank the OpenHermes 2.5 Mistral 7B Mlx 4bit 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

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Best Alternatives	Context / RAM	Downloads	Likes
...t 3.5 0106 128K 4.0bpw H6 EXL2	128K / 3.9 GB	4	1
...t 3.5 0106 128K 8.0bpw H8 EXL2	128K / 7.4 GB	1	1
Mistral 7B 4bit 1C MLX	32K / 4.1 GB	156	1
...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
Mistral 7B Instruct V0.2 4bit	32K / 4.3 GB	79	1
Mistral 7B V0.3 Bnb 4bit	32K / 4.1 GB	381323	22
...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
...tral 7B Instruct V0.2 Bnb 4bit	32K / 4.1 GB	7160	35

Note: green Score (e.g. "73.2") means that the model is better than cogbuji/OpenHermes-2.5-Mistral-7B-mlx-4bit.