What are the hardware requirements for Mistral Pre Trained Model?

Mistral Pre Trained Model requires approximately 0.3 GB of VRAM and supports a context window of 0.5K tokens. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed Mistral Pre Trained Model and how large is it?

Mistral Pre Trained Model is developed by hugsid, a model with 84.5m 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 Mistral Pre Trained Model?

Mistral Pre Trained Model is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral Pre Trained Model by hugsid — VRAM 0.3GB, 0.5K context

Name: Mistral Pre Trained Model
Author: hugsid

Mistral Pre Trained Model is an open-source language model by hugsid. Features: 84.5m LLM, VRAM: 0.3GB, Context: 0.5K, LLM Explorer Score: 0.18.

Base model:finetune:hugsid/mis... Base model:hugsid/mistral-pre-... Endpoints compatible Generated from trainer Mistral Region:us Safetensors Sft Trl

Model Card on HF 🤗: https://huggingface.co/hugsid/mistral-pre-trained-model

Mistral Pre Trained Model Parameters and Internals

LLM Name	Mistral Pre Trained Model
Repository 🤗	https://huggingface.co/hugsid/mistral-pre-trained-model
Model Name	mistral-pre-trained-model
Base Model(s)	Mistral Pre Trained Model hugsid/mistral-pre-trained-model
Model Size	84.5m
Required VRAM	0.3 GB
Updated	2026-08-02
Maintainer	hugsid
Model Type	mistral
Model Files	0.3 GB 0.0 GB
Model Architecture	MistralForCausalLM
Context Length	512
Model Max Length	512
Transformers Version	4.52.4
Tokenizer Class	LlamaTokenizerFast
Padding Token	<pad>
Vocabulary Size	32000
Torch Data Type	float32

Rank the Mistral Pre Trained Model 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 Mistral Pre Trained Model

Best Alternatives	Context / RAM	Downloads
Mistral Pretrained Test	128K / 0.3 GB	7
Mistral Pretraining	0.5K / 0.3 GB	11
Mistral Supervised	0.5K / 0.3 GB	13
Mistral Pretraining	0.5K / 0.3 GB	13
Lab 2	0.5K / 0.3 GB	6
Mistral Pretraining	0.5K / 0.3 GB	5
Mistral Pretraining	0.5K / 0.3 GB	7
Mistral Pretraining	0.5K / 0.3 GB	10
Mistral Pretraining	0.5K / 0.3 GB	5
Mistral Pretraining	0.5K / 0.3 GB	5

Note: green Score (e.g. "73.2") means that the model is better than hugsid/mistral-pre-trained-model.