Unlock the Future of AI with InternVL: The Open-Source Multimodal Revolution

Are you ready to dive into the world of next-generation AI? InternVL is a groundbreaking series of open-source multimodal large language models (MLLMs) that's pushing the boundaries of what's possible. This article explores its capabilities and guides you on getting started.

Why InternVL is Changing the Game

State-of-the-Art Performance: Achieve unmatched performance in perception and reasoning.
Open-Source Advantage: Harness the power of collaborative innovation and transparency.
Versatile Applications: From image understanding to complex reasoning tasks, InternVL adapts to your needs.

Latest News: Stay Updated with InternVL's Rapid Development

(2025/04/17): Data construction pipeline and training scripts of MPO and VisualPRM open-sourced.
(2025/04/11): InternVL3 introduced with SoTA performance among open-source MLLMs, featuring Variable Visual Position Encoding and Native Multimodal Pre-Training.
(2025/03/13): VisualPRM released, boosting InternVL2.5's reasoning performance with its VisualPRM400K training dataset.
(2024/12/20): InternVL2.5-MPO released, fine-tuned with Mixed Preference Optimization (MPO) for enhanced performance.
(2024/12/05): InternVL2.5 achieves over 70% on the MMMU benchmark, matching the performance of closed-source models like GPT-4o.

These updates show the team's commitment to improving InternVL and providing the community with the best possible tools.

Diving Deeper: Key Features and Innovations of InternVL

Variable Visual Position Encoding

InternVL3 introduces Variable Visual Position Encoding, which allows the model to understand the spatial relationships between different visual elements. This leads to significant accuracy improvements in visual tasks.

Mixed Preference Optimization (MPO)

MPO allows InternVL models to better align with human preferences, enhancing their ability to generate useful and relevant outputs.

Native Multimodal Pre-Training

InternVL utilizes native multimodal pre-training so it can understand different data types like images and text simultaniously.

VisualPRM

The Visual Process Reward Model (VisualPRM), an 8B parameter model, enhances the reasoning capabilities of InternVL versions further.

Getting Started with InternVL: Your Path to AI Mastery

Ready to experience the power of InternVL? Here’s your roadmap:

Installation: Follow the comprehensive [Installation Guide](link to guide).
Data Format: Understand the [Meta File](link to meta file), [Text](link to text), [Single-Image](link to single-image), [Multi-Image](link to multi-image), and [Video](link to video) formats.
Local Chat Demo: Set up a [Streamlit Demo](link to demo) for interactive exploration.

InternVL Family: A Model for Every Need

InternVL 2.5: The latest and greatest, offering top-tier performance. Explore the [Intro](link to intro), [Quick Start](link to quick start), [Finetune](link to finetune), [Evaluate](link to evaluate), [Deploy](link to deploy), and [MPO](link to mpo) guides.
InternVL 2.0: A robust and versatile predecessor. Check out its [Intro](link to intro), [Quick Start](link to quick start), [Finetune](link to finetune), [Evaluate](link to evaluate), [Deploy](link to deploy), and [MPO](link to mpo) resources.

Unleash the Power of Multimodal AI

With its cutting-edge features, open-source nature, and comprehensive documentation, InternVL empowers you to tackle complex AI challenges. Dive in, experiment, and unlock the future of multimodal intelligence.

Latest News: Stay Updated with InternVL's Rapid Development

(2025/04/17): Data construction pipeline and training scripts of MPO and VisualPRM open-sourced.

(2025/04/11): InternVL3 introduced with SoTA performance among open-source MLLMs, featuring Variable Visual Position Encoding and Native Multimodal Pre-Training.

(2025/03/13): VisualPRM released, boosting InternVL2.5's reasoning performance with its VisualPRM400K training dataset.

(2024/12/20): InternVL2.5-MPO released, fine-tuned with Mixed Preference Optimization (MPO) for enhanced performance.

(2024/12/05): InternVL2.5 achieves over 70% on the MMMU benchmark, matching the performance of closed-source models like GPT-4o.

These updates show the team's commitment to improving InternVL and providing the community with the best possible tools.

Diving Deeper: Key Features and Innovations of InternVL

Variable Visual Position Encoding

Mixed Preference Optimization (MPO)

MPO allows InternVL models to better align with human preferences, enhancing their ability to generate useful and relevant outputs.

Native Multimodal Pre-Training

InternVL utilizes native multimodal pre-training so it can understand different data types like images and text simultaniously.

VisualPRM

The Visual Process Reward Model (VisualPRM), an 8B parameter model, enhances the reasoning capabilities of InternVL versions further.

Getting Started with InternVL: Your Path to AI Mastery

Ready to experience the power of InternVL? Here’s your roadmap:

Installation: Follow the comprehensive [Installation Guide](link to guide).

Data Format: Understand the [Meta File](link to meta file), [Text](link to text), [Single-Image](link to single-image), [Multi-Image](link to multi-image), and [Video](link to video) formats.

Local Chat Demo: Set up a [Streamlit Demo](link to demo) for interactive exploration.

InternVL Family: A Model for Every Need

InternVL 2.5: The latest and greatest, offering top-tier performance. Explore the [Intro](link to intro), [Quick Start](link to quick start), [Finetune](link to finetune), [Evaluate](link to evaluate), [Deploy](link to deploy), and [MPO](link to mpo) guides.

InternVL 2.0: A robust and versatile predecessor. Check out its [Intro](link to intro), [Quick Start](link to quick start), [Finetune](link to finetune), [Evaluate](link to evaluate), [Deploy](link to deploy), and [MPO](link to mpo) resources.