How to Use Frontier Vision LLMs: Qwen3-VL

Author(s): Eivind Kjosbakken

Originally published on Towards AI.

Learn how you can use vision language models to perform advanced document understanding tasks.

Vision language models (VLMs) are powerful models capable of inputting both images and text, and responding with text. This allows us to perform visual information extraction on documents and images. In this article, I’ll discuss the newly released Qwen 3 VL and the powerful capabilities VLMs possess.

This article explores the functionalities of Vision Language Models (VLMs), particularly focusing on the new Qwen 3 VL model. It outlines the importance of VLMs in document processing, comparing their efficiency with traditional OCR methods, and illustrates their capabilities with examples. Furthermore, it discusses the practicalities of implementing VLMs, the variety of tasks they can execute—from OCR to information extraction—and highlights the potential downsides, such as processing power requirements and occasional text extraction errors. Overall, the author suggests that VLMs are set to become increasingly vital as the field of AI evolves.

Read the full blog for free on Medium.

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Published via Towards AI