What is InternVL used for?

InternVL is an MIT-licensed family of open multimodal vision-language models and training code from OpenGVLab, positioned as an open alternative to GPT-4o. It is a good fit for image and document understanding research, and building multimodal chat features on local models.

Is InternVL open source?

Yes. InternVL is open source under the MIT licence. Its source code is on GitHub at OpenGVLab/InternVL and is written mainly in Python.

Yes. InternVL is open source, so the software itself is free to use. A managed cloud version is also available.

Can I self-host InternVL?

Yes. InternVL can be self-hosted on your own server or infrastructure.

What is InternVL an alternative to?

InternVL is an open-source alternative to ChatGPT. Other open-source alternatives to ChatGPT include Ollama, PrivateGPT and LocalAI.

Is InternVL actively maintained?

The most recent commit to InternVL was on 22 September 2025, and the latest release is v1.5.0, published on 8 May 2024. The project has 10k stars on GitHub.

InternVL: open-source alternative to ChatGPT

About InternVL

InternVL is a family of open-source multimodal models from the OpenGVLab research group that combine vision and language understanding. The project presents the series as an open alternative to commercial multimodal models such as GPT-4o, and it covers image and video understanding, image-text retrieval and related vision tasks.

The repository documents successive releases, from InternVL 1.0 and 1.5 through 2.0, 2.5, 3.0 and 3.5, along with papers, a blog, FAQs, a chat demo and an API. Recent updates mention open-sourced training code and data for reinforcement-learning stages, and the largest InternVL3.5 model listed has 241 billion parameters. Quick-start instructions use Hugging Face.

It is written in Python and released under the MIT license, so the models and code can be run on your own GPU hardware. Documentation is hosted on Read the Docs, and the project is mainly a research and model resource rather than an end-user application.

Key features

Open vision-language models for image and video understanding
Multiple model generations and sizes
Quick start with Hugging Face
Training code and data for reinforcement learning
Online chat demo and API access

Good fit for

→Image and document understanding research
→Building multimodal chat features on local models

Built with: Python
Tags: multimodal; vision-language; llm; computer-vision; image-understanding; open-models; python; research

InternVL: questions and answers

What is InternVL used for?: InternVL is an MIT-licensed family of open multimodal vision-language models and training code from OpenGVLab, positioned as an open alternative to GPT-4o. It is a good fit for image and document understanding research, and building multimodal chat features on local models.
Is InternVL open source?: Yes. InternVL is open source under the MIT licence. Its source code is on GitHub at OpenGVLab/InternVL and is written mainly in Python.
Is InternVL free?: Yes. InternVL is open source, so the software itself is free to use. A managed cloud version is also available.
Can I self-host InternVL?: Yes. InternVL can be self-hosted on your own server or infrastructure.
What is InternVL an alternative to?: InternVL is an open-source alternative to ChatGPT. Other open-source alternatives to ChatGPT include Ollama, PrivateGPT and LocalAI.
Is InternVL actively maintained?: The most recent commit to InternVL was on 22 September 2025, and the latest release is v1.5.0, published on 8 May 2024. The project has 10k stars on GitHub.