What are the hardware requirements for InternVL3 5 4B Instruct?

InternVL3 5 4B Instruct requires approximately 9.5 GB of VRAM. Quantized variants may run on less VRAM; see the Quantized Models section on this page.

Who developed InternVL3 5 4B Instruct and how large is it?

InternVL3 5 4B Instruct is developed by OpenGVLab, a model with 4b 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 InternVL3 5 4B Instruct?

InternVL3 5 4B Instruct is hosted on Hugging Face and linked from this page. LLM Explorer also lists quantized variants and similar alternatives if available.

InternVL3 5 4B Instruct by OpenGVLab — VRAM 9.5GB

Name: InternVL3 5 4B Instruct
Author: OpenGVLab

InternVL3 5 4B Instruct is an open-source language model by OpenGVLab. Features: 4b LLM, VRAM: 9.5GB, License: apache-2.0, Instruction-Based, LLM Explorer Score: 0.22.

Arxiv:2312.14238 Arxiv:2404.16821 Arxiv:2411.10442 Arxiv:2412.05271 Arxiv:2504.10479 Arxiv:2508.18265 Base model:finetune:opengvlab/... Base model:opengvlab/internvl3... Conversational Custom code Dataset:opengvlab/mmpr-tiny Dataset:opengvlab/mmpr-v1.2 Feature-extraction Image-text-to-text Instruct Internvl Internvl chat Multilingual Region:us Safetensors Sharded Tensorflow

Model Card on HF 🤗: https://huggingface.co/OpenGVLab/InternVL3_5-4B-Instruct

InternVL3 5 4B Instruct Parameters and Internals

LLM Name	InternVL3 5 4B Instruct
Repository 🤗	https://huggingface.co/OpenGVLab/InternVL3_5-4B-Instruct
Base Model(s)	InternVL3 5 4B Pretrained OpenGVLab/InternVL3_5-4B-Pretrained
Model Size	4b
Required VRAM	9.5 GB
Updated	2026-08-08
Maintainer	OpenGVLab
Model Type	internvl_chat
Instruction-Based	Yes
Model Files	5.0 GB: 1-of-2 4.5 GB: 2-of-2
Model Architecture	InternVLChatModel
License	apache-2.0
Model Max Length	32768
Tokenizer Class	Qwen2Tokenizer
Padding Token	<\|endoftext\|>
Torch Data Type	bfloat16
Errors	replace

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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

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