What are the hardware requirements for Mixtral BioMedical 7B?

Mixtral BioMedical 7B requires approximately 7.7 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 Mixtral BioMedical 7B and how large is it?

Mixtral BioMedical 7B is developed by LeroyDyer, 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 Mixtral BioMedical 7B?

Mixtral BioMedical 7B is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mixtral BioMedical 7B by LeroyDyer — VRAM 7.7GB, 32K context

Name: Mixtral BioMedical 7B
Author: LeroyDyer

Mixtral BioMedical 7B is an open-source language model by LeroyDyer. Features: 7b LLM, VRAM: 7.7GB, Context: 32K, Quantized, LLM Explorer Score: 0.11.

Arxiv:2203.05482 Endpoints compatible Gguf Merge Mergekit Mistral Pytorch Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/LeroyDyer/Mixtral_BioMedical_7b

Mixtral BioMedical 7B Parameters and Internals

Additional Notes

This model was created through merging using the Mergekit tool.

Training Details

Methodology:

Model merged using the linear merge method.

LLM Name	Mixtral BioMedical 7b
Repository 🤗	https://huggingface.co/LeroyDyer/Mixtral_BioMedical_7b
Base Model(s)	Nitral-AI/ProdigyXBioMistral_7B LeroyDyer/Mixtral_AI Nitral-AI/ProdigyXBioMistral_7B LeroyDyer/Mixtral_AI
Model Size	7b
Required VRAM	7.7 GB
Updated	2026-07-30
Maintainer	LeroyDyer
Model Type	mistral
Model Files	7.7 GB 14.5 GB
GGUF Quantization	Yes
Quantization Type	gguf
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Padding Token	<unk>
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mixtral BioMedical 7B 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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Note: green Score (e.g. "73.2") means that the model is better than LeroyDyer/Mixtral_BioMedical_7b.