What are the hardware requirements for Mistral 7B Instruct V0.1 GPTQ?

Mistral 7B Instruct V0.1 GPTQ requires approximately 4.2 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 Mistral 7B Instruct V0.1 GPTQ and how large is it?

Mistral 7B Instruct V0.1 GPTQ is developed by MaziyarPanahi, 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 Mistral 7B Instruct V0.1 GPTQ?

Mistral 7B Instruct V0.1 GPTQ is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B Instruct V0.1 GPTQ by MaziyarPanahi — VRAM 4.2GB, 32K context

Name: Mistral 7B Instruct V0.1 GPTQ
Author: MaziyarPanahi

Mistral 7B Instruct V0.1 GPTQ is an open-source language model by MaziyarPanahi. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.1.

Arxiv:2310.06825 4-bit Autotrain compatible Base model:finetune:mistralai/... Base model:mistralai/mistral-7... Conversational Finetuned Gptq Has space Instruct Mistral Pytorch Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/MaziyarPanahi/Mistral-7B-Instruct-v0.1-GPTQ

Mistral 7B Instruct V0.1 GPTQ Parameters and Internals

Model Type

text-generation

Additional Notes

The model is quantized using GPTQ and optimized for text generation tasks.

Input Output

Accepted Modalities:

text

LLM Name	Mistral 7B Instruct V0.1 GPTQ
Repository 🤗	https://huggingface.co/MaziyarPanahi/Mistral-7B-Instruct-v0.1-GPTQ
Model Name	Mistral-7B-Instruct-v0.1-GPTQ
Model Creator	mistralai
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.1 mistralai/Mistral-7B-Instruct-v0.1
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-08-08
Maintainer	MaziyarPanahi
Model Type	mistral
Instruction-Based	Yes
Model Files	4.2 GB
GPTQ Quantization	Yes
Quantization Type	gptq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.36.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.1 GPTQ 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 7B Instruct V0.1 GPTQ

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.3 GPTQ	32K / 4.2 GB	113881	1
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2946	18
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	2658	25
Mistral 7B Instruct V0.2 GPTQ	32K / 4.2 GB	6743	56
Mistral 7B Instruct V0.3 GPTQ	32K / 4.2 GB	17	0
...tral 7B Instruct 32K GPTQ INT8	32K / 7.7 GB	22	1
...ral 7B Instruct V0.3 GPTQ 4bit	32K / 4.2 GB	6	0
...stral 7B Instruct V0.3 GPTQ 8B	32K / 7.7 GB	3	1
...stral 7B Instruct V0.3 GPTQ 4B	32K / 4.2 GB	5	0
...nstruct V0.2 Neural Story GPTQ	32K / 4.6 GB	6	1

Note: green Score (e.g. "73.2") means that the model is better than MaziyarPanahi/Mistral-7B-Instruct-v0.1-GPTQ.