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What is Qwen2.5-VL?

The Qwen2.5-VL represents a significant advancement in the Qwen vision-language model series, offering substantial enhancements over the earlier version, Qwen2-VL. This sophisticated model showcases remarkable skills in visual interpretation, capable of recognizing a wide variety of elements in images, including text, charts, and numerous graphical components. Acting as an interactive visual assistant, it possesses the ability to reason and adeptly utilize tools, making it ideal for applications that require interaction on both computers and mobile devices. Additionally, Qwen2.5-VL excels in analyzing lengthy videos, being able to pinpoint relevant segments within those that exceed one hour in duration. It also specializes in precisely identifying objects in images, providing bounding boxes or point annotations, and generates well-organized JSON outputs detailing coordinates and attributes. The model is designed to output structured data for various document types, such as scanned invoices, forms, and tables, which proves especially beneficial for sectors like finance and commerce. Available in both base and instruct configurations across 3B, 7B, and 72B models, Qwen2.5-VL is accessible on platforms like Hugging Face and ModelScope, broadening its availability for developers and researchers. Furthermore, this model not only enhances the realm of vision-language processing but also establishes a new benchmark for future innovations in this area, paving the way for even more sophisticated applications.

What is Qwen2-VL?

Qwen2-VL stands as the latest and most sophisticated version of vision-language models in the Qwen lineup, enhancing the groundwork laid by Qwen-VL. This upgraded model demonstrates exceptional abilities, including: Delivering top-tier performance in understanding images of various resolutions and aspect ratios, with Qwen2-VL particularly shining in visual comprehension challenges such as MathVista, DocVQA, RealWorldQA, and MTVQA, among others. Handling videos longer than 20 minutes, which allows for high-quality video question answering, engaging conversations, and innovative content generation. Operating as an intelligent agent that can control devices such as smartphones and robots, Qwen2-VL employs its advanced reasoning abilities and decision-making capabilities to execute automated tasks triggered by visual elements and written instructions. Offering multilingual capabilities to serve a worldwide audience, Qwen2-VL is now adept at interpreting text in several languages present in images, broadening its usability and accessibility for users from diverse linguistic backgrounds. Furthermore, this extensive functionality positions Qwen2-VL as an adaptable resource for a wide array of applications across various sectors.

Media

Media

Integrations Supported

Alibaba Cloud
Hugging Face
LM-Kit.NET
ModelScope
Qwen Studio
BLACKBOX AI
Parasail
kluster.ai

Integrations Supported

Alibaba Cloud
Hugging Face
LM-Kit.NET
ModelScope
Qwen Studio
Open Computer Agent

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Open source
Free Version

Pricing Information

Free
Open source
Free Version

Supported Platforms

SaaS
Android
Windows
Mac
On-Prem
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Not specified

Customer Service / Support

Not specified

Training Options

Documentation Hub

Training Options

Documentation Hub

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwenlm.github.io/blog/qwen2.5-vl/

Company Facts

Organization Name

Alibaba

Date Founded

1999

Company Location

China

Company Website

qwenlm.github.io

Categories and Features

Agentic AI

Not specified

AI Agents

Not specified

AI Models

Not specified

AI Vision Models

Not specified

Computer Vision

Not specified

Foundation Models

Not specified

Large Language Models

Not specified

Multimodal Models

Not specified

Categories and Features

AI Models

Not specified

AI Vision Models

Not specified

Computer Vision

Not specified

Large Language Models

Not specified

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