What are the hardware requirements for Mistral 7B Instruct V0.2 4bit?

Mistral 7B Instruct V0.2 4bit requires approximately 4.3 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 4bit and how large is it?

Mistral 7B Instruct V0.2 4bit is developed by mlx-community, 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 4bit perform on standard benchmarks?

Mistral 7B Instruct V0.2 4bit 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 4bit by mlx-community — VRAM 4.3GB, 32K context

Name: Mistral 7B Instruct V0.2 4bit
Author: mlx-community

Mistral 7B Instruct V0.2 4bit is an open-source language model by mlx-community. Features: 7b LLM, VRAM: 4.3GB, Context: 32K, License: apache-2.0, Quantized, Instruction-Based, LLM Explorer Score: 0.24, ELO: 1072, Arc: 56.7, HellaSwag: 80.8, MMLU: 59.1, GSM8K: 37.6.

4bit Conversational Finetuned Instruct Mistral Mlx Quantized Region:us Safetensors

Model Card on HF 🤗: https://huggingface.co/mlx-community/Mistral-7B-Instruct-v0.2-4bit

Mistral 7B Instruct V0.2 4bit 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 4bit Parameters and Internals

Model Type

text-generation

Additional Notes

This model was converted to MLX format.

LLM Name	Mistral 7B Instruct V0.2 4bit
Repository 🤗	https://huggingface.co/mlx-community/Mistral-7B-Instruct-v0.2-4bit
Base Model(s)	lachiewyoung/mistral-7b-instruct-1.58bit lachiewyoung/mistral-7b-instruct-1.58bit
Model Size	7b
Required VRAM	4.3 GB
Updated	2026-08-07
Maintainer	mlx-community
Model Type	mistral
Instruction-Based	Yes
Model Files	4.3 GB
Quantization Type	4bit
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.39.0.dev0
Vocabulary Size	32000
Torch Data Type	bfloat16

Rank the Mistral 7B Instruct V0.2 4bit 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 V0.2 4bit

Best Alternatives	Context / RAM	Downloads	Likes
...aude Sonnet Mistral 7B It V0.3	32K / 14.5 GB	7	2
Mistral 7B Instruct V0.2 Fp16	32K / 14.4 GB	26	0
...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
Mistral 7B Instruct V0.2 8bit	32K / 7.6 GB	5	1
...tral 7B Instruct V0.2 Bnb 4bit	32K / 4.1 GB	7160	35
Mixtral V0.3 Full 16bit	32K / 14.5 GB	8	0
... 7B Instruct V0.3ContinuedFine	32K / 14.5 GB	14	0
Mistral 7B Instruct V0.3 4bit	32K / 4.1 GB	12492	10
...eMistral 7B Instruct Ead 16bit	32K / 14.5 GB	38	0
NaturalLM 7B Instruct	32K / 14.5 GB	17	10

Note: green Score (e.g. "73.2") means that the model is better than mlx-community/Mistral-7B-Instruct-v0.2-4bit.