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

Mistral 7B Instruct V0.1 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 V0.1 AWQ and how large is it?

Mistral 7B Instruct V0.1 AWQ is developed by casperhansen, a model with 7b parameters. The model is published as open weights on Hugging Face and indexed on LLM Explorer with full benchmark history.

How does Mistral 7B Instruct V0.1 AWQ perform on standard benchmarks?

Mistral 7B Instruct V0.1 AWQ has the following published scores: MMLU 55.4. Compare against reference models on this page or on the LLM Explorer leaderboards.

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

Name: Mistral 7B Instruct V0.1 AWQ
Author: casperhansen

Mistral 7B Instruct V0.1 AWQ is an open-source language model by casperhansen. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.15, Arc: 54.7, HellaSwag: 75.7, MMLU: 55.4, GSM8K: 31.2.

4-bit Awq Deploy:azure Endpoints compatible Instruct Mistral Pytorch Quantized Region:us

Model Card on HF 🤗: https://huggingface.co/casperhansen/mistral-7b-instruct-v0.1-awq

Mistral 7B Instruct V0.1 AWQ Parameters and Internals

Model Type

text generation

Supported Languages

en (Proficient)

Input Output

Input Format:

Tokens

Accepted Modalities:

text

Output Format:

Generated text

Performance Tips:

Optimal performance with CUDA-enabled GPU.

LLM Name	Mistral 7B Instruct V0.1 AWQ
Repository 🤗	https://huggingface.co/casperhansen/mistral-7b-instruct-v0.1-awq
Base Model(s)	frankmorales2020/Mistral-7B-v0.1_McGill-MEDAL frankmorales2020/Mistral-7B-v0.1_McGill-MEDAL
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-08-07
Maintainer	casperhansen
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	4.34.0.dev0
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.1 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 V0.1 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 V0.3 AWQ	32K / 4.2 GB	5633	10
...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 casperhansen/mistral-7b-instruct-v0.1-awq.