What are the hardware requirements for Mistral 7B Instruct V0.2 AWQ?

Mistral 7B Instruct V0.2 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 V0.2 AWQ and how large is it?

Mistral 7B Instruct V0.2 AWQ is developed by Vidushee, 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 V0.2 AWQ perform on standard benchmarks?

Mistral 7B Instruct V0.2 AWQ has the following published scores: MMLU 59.1, LMSYS ELO 1072. Compare against reference models on this page or on the LLM Explorer leaderboards.

Mistral 7B Instruct V0.2 AWQ by Vidushee — VRAM 4.2GB, 32K context

Name: Mistral 7B Instruct V0.2 AWQ
Author: Vidushee

Mistral 7B Instruct V0.2 AWQ is an open-source language model by Vidushee. Features: 7b LLM, VRAM: 4.2GB, Context: 32K, License: mit, Quantized, Instruction-Based, LLM Explorer Score: 0.24, ELO: 1072, Arc: 56.7, HellaSwag: 80.8, MMLU: 59.1, GSM8K: 37.6.

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

Model Card on HF 🤗: https://huggingface.co/Vidushee/Mistral-7B-Instruct-v0.2-awq

Mistral 7B Instruct V0.2 AWQ Benchmarks

LMSys ELO 1072 vs 1272 (so35) -15.7%

^nn.n% — How the model compares to the reference models: Anthropic Sonnet 3.5 ("so35"), GPT-4o ("gpt4o") or GPT-4 ("gpt4").

What is the LLM Explorer Rank (Score)

Mistral 7B Instruct V0.2 AWQ Parameters and Internals

LLM Name	Mistral 7B Instruct V0.2 AWQ
Repository 🤗	https://huggingface.co/Vidushee/Mistral-7B-Instruct-v0.2-awq
Base Model(s)	jan-hq/Mistral-7B-Instruct-v0.2-SLERP jan-hq/Mistral-7B-Instruct-v0.2-SLERP
Model Size	7b
Required VRAM	4.2 GB
Updated	2026-06-03
Maintainer	Vidushee
Model Type	mistral
Instruction-Based	Yes
Model Files	4.2 GB
AWQ Quantization	Yes
Quantization Type	awq
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.38.2
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.2 AWQ capabilities

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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

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Mistral 7B Instruct V0.2 AWQ	32K / 4.2 GB	298182	52
Mistral 7B Instruct V0.3 AWQ	32K / 4.2 GB	5633	10
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...reeze 7B 32K Instruct V1.0 AWQ	32K / 4.7 GB	9	0
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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