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

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

Mistral 7B Instruct V0.3 AWQ is developed by solidrust, 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 AWQ?

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

Name: Mistral 7B Instruct V0.3 AWQ
Author: solidrust

Mistral 7B Instruct V0.3 AWQ is an open-source language model by solidrust. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.15.

4-bit Autotrain compatible Awq Base model:mistralai/mistral-7... Base model:quantized:mistralai... Conversational Deploy:azure Endpoints compatible Instruct Mistral Quantized Region:us Safetensors

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

Mistral 7B Instruct V0.3 AWQ Parameters and Internals

Model Type

text-generation

Use Cases

Areas:

research, commercial applications

Additional Notes

The model supports function calling and utilizes a v3 tokenizer.

Training Details

Methodology:

Instruct fine-tuning

Input Output

Accepted Modalities:

text

Performance Tips:

Utilize AWQ supported platforms for optimal performance.

LLM Name	Mistral 7B Instruct V0.3 AWQ
Repository 🤗	https://huggingface.co/solidrust/Mistral-7B-Instruct-v0.3-AWQ
Base Model(s)	mistralai/Mistral-7B-Instruct-v0.3 mistralai/Mistral-7B-Instruct-v0.3
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-07-04
Maintainer	solidrust
Model Type	mistral
Instruction-Based	Yes
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32768
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.3 AWQ 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 AWQ

Best Alternatives	Context / RAM	Downloads	Likes
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	6	0
Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	298182	52
Mistral 7B Instruct V0.1 AWQ	32K / 4.2 GB	15461	2
...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	5	0
Breeze 7B Instruct V1.0 AWQ	32K / 4.6 GB	14	1
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	628	1
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5	0
...Instruct V0.2 AWQ 4bit Smashed	32K / 4.2 GB	8	1
Mistral 7B Instruct 32K AWQ	32K / 4.2 GB	4	1

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