What are the hardware requirements for Mistral 7B Instruct V0.3 GPTQ?

Mistral 7B Instruct V0.3 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 V0.3 GPTQ and how large is it?

Mistral 7B Instruct V0.3 GPTQ is developed by Bourdin, 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 V0.3 GPTQ?

Mistral 7B Instruct V0.3 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 V0.3 GPTQ by Bourdin — VRAM 4.2GB, 32K context

Name: Mistral 7B Instruct V0.3 GPTQ
Author: Bourdin

Mistral 7B Instruct V0.3 GPTQ is an open-source language model by Bourdin. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.13.

4-bit Conversational Endpoints compatible Gptq Instruct Mistral Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/Bourdin/Mistral-7B-Instruct-v0.3-GPTQ

Mistral 7B Instruct V0.3 GPTQ Parameters and Internals

Model Type

Large Language Model, Instruct fine-tuned

Additional Notes

The Mistral 7B Instruct model is a quick demonstration that the base model can be easily fine-tuned to achieve compelling performance. It does not have any moderation mechanisms. Future improvements will focus on respecting guardrails for moderated outputs.

LLM Name	Mistral 7B Instruct V0.3 GPTQ
Repository 🤗	https://huggingface.co/Bourdin/Mistral-7B-Instruct-v0.3-GPTQ
Base Model(s)	Finetuned Mistral On Ads not-lain/finetuned_mistral_on_ads
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-09-07
Maintainer	Bourdin
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	4.41.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32768
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.3 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 V0.3 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
...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
Breeze 7B Instruct V0.1 GPTQ	32K / 4.7 GB	6	2

Note: green Score (e.g. "73.2") means that the model is better than Bourdin/Mistral-7B-Instruct-v0.3-GPTQ.