What are the hardware requirements for Mistral 7B Instruct V0.3 DesarrolloSoftware1?

Mistral 7B Instruct V0.3 DesarrolloSoftware1 requires approximately 29 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 V0.3 DesarrolloSoftware1 and how large is it?

Mistral 7B Instruct V0.3 DesarrolloSoftware1 is developed by AndresCamargo, 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 Instruct V0.3 DesarrolloSoftware1?

Mistral 7B Instruct V0.3 DesarrolloSoftware1 is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

Mistral 7B Instruct V0.3 DesarrolloSoftware1 by AndresCamargo — VRAM 29GB, 32K context

Name: Mistral 7B Instruct V0.3 DesarrolloSoftware1
Author: AndresCamargo

Mistral 7B Instruct V0.3 DesarrolloSoftware1 is an open-source language model by AndresCamargo. Features: 7b LLM, VRAM: 29GB, Context: 32K, License: mit, Instruction-Based, LLM Explorer Score: 0.18.

Conversational Instruct Mistral Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/AndresCamargo/Mistral-7B-Instruct-v0.3-DesarrolloSoftware1

Mistral 7B Instruct V0.3 DesarrolloSoftware1 Parameters and Internals

LLM Name	Mistral 7B Instruct V0.3 DesarrolloSoftware1
Repository 🤗	https://huggingface.co/AndresCamargo/Mistral-7B-Instruct-v0.3-DesarrolloSoftware1
Model Size	7b
Required VRAM	29 GB
Updated	2026-08-11
Maintainer	AndresCamargo
Model Type	mistral
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-6 4.9 GB: 2-of-6 5.0 GB: 3-of-6 5.0 GB: 4-of-6 4.8 GB: 5-of-6 4.3 GB: 6-of-6
Model Architecture	MistralForCausalLM
License	mit
Context Length	32768
Model Max Length	32768
Transformers Version	4.49.0
Tokenizer Class	LlamaTokenizer
Padding Token	[PAD]
Vocabulary Size	32769
Torch Data Type	float32

Rank the Mistral 7B Instruct V0.3 DesarrolloSoftware1 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 V0.3 DesarrolloSoftware1

Best Alternatives	Context / RAM	Downloads	Likes
...Nemo Instruct 2407 Abliterated	1000K / 24.5 GB	220	20
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
... Summarize 64K QLoRANET Merged	128K / 4.1 GB	7	0
...1 Summarize 64K LoRANET Merged	128K / 14.4 GB	11	0
Mistral 7B Instruct V0.2	32K / 14.4 GB	1115337	3184
Mistral 7B Instruct V0.1	32K / 14.4 GB	253629	1846
Mistral 7B Instruct V0.2	32K / 14.4 GB	1338	0
Mixtral AI CyberCoder	32K / 14.3 GB	0	0

Note: green Score (e.g. "73.2") means that the model is better than AndresCamargo/Mistral-7B-Instruct-v0.3-DesarrolloSoftware1.