What are the hardware requirements for Mistral 7B V0.3 Prune6?

Mistral 7B V0.3 Prune6 requires approximately 11.9 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 V0.3 Prune6 and how large is it?

Mistral 7B V0.3 Prune6 is developed by pszemraj, 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 V0.3 Prune6?

Mistral 7B V0.3 Prune6 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B V0.3 Prune6 by pszemraj — VRAM 11.9GB, 32K context

Name: Mistral 7B V0.3 Prune6
Author: pszemraj

Mistral 7B V0.3 Prune6 is an open-source language model by pszemraj. Features: 7b LLM, VRAM: 11.9GB, Context: 32K, License: apache-2.0, Merged, LLM Explorer Score: 0.13.

Merged Model Base model:finetune:mistralai/... Base model:mistralai/mistral-7... En Endpoints compatible Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/pszemraj/Mistral-7B-v0.3-prune6

Mistral 7B V0.3 Prune6 Parameters and Internals

Model Type

layer-pruned, pre-trained language model

Additional Notes

Merged using the passthrough merge method, with [mergekit](https://github.com/cg123/mergekit). No additional training was done.

Supported Languages

en (unknown)

LLM Name	Mistral 7B V0.3 Prune6
Repository 🤗	https://huggingface.co/pszemraj/Mistral-7B-v0.3-prune6
Base Model(s)	mistralai/Mistral-7B-v0.3 mistralai/Mistral-7B-v0.3
Merged Model	Yes
Model Size	7b
Required VRAM	11.9 GB
Updated	2026-08-07
Maintainer	pszemraj
Model Type	mistral
Model Files	4.9 GB: 1-of-3 4.9 GB: 2-of-3 2.1 GB: 3-of-3
Supported Languages	en
Model Architecture	MistralForCausalLM
License	apache-2.0
Context Length	32768
Model Max Length	32768
Transformers Version	4.41.1
Tokenizer Class	LlamaTokenizer
Vocabulary Size	32768
Torch Data Type	bfloat16

Rank the Mistral 7B V0.3 Prune6 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 V0.3 Prune6

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
MegaBeam Mistral 7B 512K	512K / 14.4 GB	8470	54
SpydazWeb AI HumanAI RP	512K / 14.4 GB	16	1
SpydazWeb AI HumanAI 002	512K / 14.4 GB	18	1
...daz Web AI ChatML 512K Project	512K / 14.5 GB	12	0
MegaBeam Mistral 7B 300K	282K / 14.4 GB	3779	16
MegaBeam Mistral 7B 300K	282K / 14.4 GB	8018	17
Hebrew Mistral 7B 200K	256K / 30 GB	23	15
Astral 256K 7B	250K / 14.4 GB	9	0
Astral 256K 7B V2	250K / 14.4 GB	8	0

Note: green Score (e.g. "73.2") means that the model is better than pszemraj/Mistral-7B-v0.3-prune6.