What are the hardware requirements for MiniCPM V 4.7 1B Mnn?

MiniCPM V 4.7 1B Mnn requires approximately 0.3 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed MiniCPM V 4.7 1B Mnn and how large is it?

MiniCPM V 4.7 1B Mnn is developed by bakhil-aissa, a model with 1b 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 MiniCPM V 4.7 1B Mnn?

MiniCPM V 4.7 1B Mnn is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

MiniCPM V 4.7 1B Mnn by bakhil-aissa — VRAM 0.3GB

Name: MiniCPM V 4.7 1B Mnn
Author: bakhil-aissa

MiniCPM V 4.7 1B Mnn is an open-source language model by bakhil-aissa. Features: 1b LLM, VRAM: 0.3GB, License: apache-2.0, LLM Explorer Score: 0.28.

Base model:finetune:openbmb/mi... Base model:openbmb/minicpm-v-4... Image-text-to-text Minicpm-v Mnn Multimodal On-device Quantized Region:us Vision Vision-language

Model Card on HF 🤗: https://huggingface.co/bakhil-aissa/MiniCPM-V-4.7-1B-mnn

MiniCPM V 4.7 1B Mnn Parameters and Internals

LLM Name	MiniCPM V 4.7 1B Mnn
Repository 🤗	https://huggingface.co/bakhil-aissa/MiniCPM-V-4.7-1B-mnn
Base Model(s)	openbmb/MiniCPM-V-4.7-1B openbmb/MiniCPM-V-4.7-1B
Model Size	1b
Required VRAM	0.3 GB
Updated	2026-10-22
Maintainer	bakhil-aissa
Model Files	0.3 GB
License	apache-2.0

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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