InternVL3-78B

Maintained By
OpenGVLab

InternVL3-78B

PropertyValue
Parameter Count78 Billion
LicenseMIT License (with Qwen License components)
ArchitectureViT-MLP-LLM with Variable Visual Position Encoding
PaperarXiv:2412.05271
AuthorOpenGVLab

What is InternVL3-78B?

InternVL3-78B is a state-of-the-art multimodal large language model that combines powerful vision capabilities with advanced language understanding. It builds upon the success of previous InternVL versions, incorporating a unique Native Multimodal Pre-Training approach that integrates vision and language learning in a single stage.

Implementation Details

The model utilizes a ViT-MLP-LLM architecture with InternViT-6B-448px-V2_5 for vision processing and Qwen2.5-72B for language understanding. It implements Variable Visual Position Encoding (V2PE) for improved long-context understanding and features Mixed Preference Optimization (MPO) for enhanced reasoning capabilities.

  • Native Multimodal Pre-Training that combines vision and language learning simultaneously
  • Advanced position encoding with V2PE for better visual context understanding
  • Mixed Preference Optimization for improved reasoning performance
  • Support for multi-image and video processing

Core Capabilities

  • Superior multimodal perception and reasoning across images and videos
  • Advanced tool usage and GUI agent capabilities
  • Industrial image analysis and 3D vision perception
  • Comprehensive multilingual understanding
  • Enhanced visual grounding and spatial reasoning

Frequently Asked Questions

Q: What makes this model unique?

InternVL3-78B stands out for its Native Multimodal Pre-Training approach, which integrates vision and language learning in a single stage, rather than the traditional two-stage approach. This results in better overall performance in both multimodal and pure language tasks.

Q: What are the recommended use cases?

The model excels in complex visual-linguistic tasks including image and video analysis, GUI operations, industrial applications, 3D scene understanding, and creative writing. It's particularly suitable for applications requiring advanced reasoning and detailed visual understanding.

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