What are the hardware requirements for Mistral 7B Instruct V0.2 8bit?

Mistral 7B Instruct V0.2 8bit requires approximately 7.6 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 8bit and how large is it?

Mistral 7B Instruct V0.2 8bit is developed by LsTam, 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 8bit perform on standard benchmarks?

Mistral 7B Instruct V0.2 8bit 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 8bit by LsTam — VRAM 7.6GB, 32K context

Name: Mistral 7B Instruct V0.2 8bit
Author: LsTam

Mistral 7B Instruct V0.2 8bit is an open-source language model by LsTam. Features: 7b LLM, VRAM: 7.6GB, Context: 32K, Quantized, Instruction-Based, LLM Explorer Score: 0.22, ELO: 1072, Arc: 56.7, HellaSwag: 80.8, MMLU: 59.1, GSM8K: 37.6.

Arxiv:2310.06825 8-bit 8bit Bitsandbytes Endpoints compatible Instruct Mistral Quantized Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/LsTam/Mistral-7B-Instruct-v0.2-8bit

Mistral 7B Instruct V0.2 8bit 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 8bit Parameters and Internals

Model Type

8bit quantized

Additional Notes

The model is loaded in 8bit with `torch_dtype=torch.float16`.

Input Output

Accepted Modalities:

text

Performance Tips:

Use `use_flash_attention_2=True` for improved performance.

LLM Name	Mistral 7B Instruct V0.2 8bit
Repository 🤗	https://huggingface.co/LsTam/Mistral-7B-Instruct-v0.2-8bit
Base Model(s)	lachiewyoung/mistral-7b-instruct-1.58bit lachiewyoung/mistral-7b-instruct-1.58bit
Model Size	7b
Required VRAM	7.6 GB
Updated	2026-08-05
Maintainer	LsTam
Model Type	mistral
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 2.6 GB: 2-of-2
Quantization Type	8bit
Model Architecture	MistralForCausalLM
Context Length	32768
Model Max Length	32768
Transformers Version	4.35.2
Vocabulary Size	32000
Torch Data Type	float16

Rank the Mistral 7B Instruct V0.2 8bit 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 8bit

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
Mistral 7B Instruct V0.2 4bit	32K / 4.3 GB	79	1
...tral 7B Instruct V0.3 Bnb 4bit	32K / 4.1 GB	34633	42
...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 LsTam/Mistral-7B-Instruct-v0.2-8bit.