What is Qwen? 

Qwen is an open-source series of large language models and multimodal models developed by e-commerce giant Alibaba Cloud.  Qwen2.5, the cloud computing company’s most recent release, is a multimodal AI model capable of analyzing and processing a variety of data types far beyond only text.

What is multimodal AI?

Multimodal AI models are machine learning models that are capable of processing and integrating information from multiple modalities or multiple types of data, such as text, images, audio, video and other forms of sensory input. IBM explains that the ability of multimodal AI models to combine and analyze different forms of data inputs makes it possible for these models to “achieve a more comprehensive understanding and generate more robust outputs.”

The advancements and capabilities of the Qwen2.5 model include better natural language understanding, analysis, reasoning and context. This makes it very well suited for complex tasks, automation and coding as well as compiling and analyzing real-time data. 

Latest upgrades to Qwen 

Meanwhile, another upgrade to Qwen is reportedly on the cusp, according to industry reports, with Qwen 3 likely to be launched in the Spring of 2025. Alibaba Cloud continues to upgrade these large language models with a focus on performance, with each upgrade intended to improve how the model understands and analyzes data. The company is also looking to outperform other AI rivals such as Deepseek. 

Advanced capabilities in natural language understanding

According to Alibaba Cloud, its Qwen2.5 models have been pre-trained on their latest large-scale dataset, which includes up to 18 trillion tokens. With this pre-training, Qwen2.5 has acquired considerably more knowledge and has made significant advancements in coding and mathematics. 

The Qwen2.5 series includes a number of “offshoot models” that serve specific purposes like coding, math, vision, language and audio.

Specifically, Qwen2.5 models are more advanced in following instructions, generating long texts, understanding structured data and generating structured outputs. As a result, the Qwen2.5 models can better understand diverse system prompts, allowing for things like enhanced role-play implementation and condition-setting for chatbots. 

One of the models can generate real-time responses in the form of text and natural speech and can be deployed on mobile phones and laptops. There are also significant advancements in analysis and processing, and an expansion of use cases due to Qwen2.5’s ability to capture and process real-time data from many formats, including video, audio, speech, images, shared content, sensory and tactile inputs.

What are some key benefits and use cases? 

Qwen2.5’s multimodal capabilities can enhance tasks such as analyzing documents, understanding images, transcribing speech and even participating in video-based interactions.

Other key features of the Qwen2.5 models include: 

• An extended content window – this means it can process larger amounts of information in a single session and allows it to analyze longer documents or audio conversations, for instance. 
• Multilingual support – Qwen2.5 supports 29 languages, including Chinese, English, French, Spanish, Portuguese, German and Japanese, making it highly adaptable for businesses with global operations. 
• Open source – this allows organizations to fine-tune, customize and deploy the product according to their specific requirements, giving them greater transparency and control. 
• Self-hostable – organizations can run the product on their own servers rather than cloud-based AI models that store data externally. This allows businesses to maintain control over sensitive data and comply with stringent privacy regulations by running the model on their own proprietary servers.
• Supports real-time interactions – this includes streaming input and output, and generates natural, adaptable speech responses suitable for conversational AI and interactive applications. 

These robust and advanced capabilities further advance popular use cases.

The Qwen2.5 model is capable of powering agile and cost-effective AI agents. Meanwhile, chatbots benefit from the model’s advanced understanding and improved responses, creating benefits including real-time interactions and better role-playing capabilities. 

The advanced multimodal capabilities of the model elevate integration and data analysis for customer service and workflow automation. Qwen AI also has the ability to generate insights from large data volumes. This allows for advanced data analytics for areas including governance, compliance, risk management and fraud detection. Qwen2.5 can also help build integrations that enhance the user experience using interactive and real-time data. Developers can use the tool to build AI automation tools as well. 

Using Qwen as an AI tool can help organizations more easily and intuitively integrate multimodal data inputs to create interactive and nimble experiences and leverage the analysis of large volumes of comprehensive data. 

A powerful engine for the multimodal future

Alibaba Cloud’s Qwen2.5 represents a significant leap forward in the evolution of multimodal AI. With its ability to process and synthesize a wide range of data types—text, images, audio and more—Qwen2.5 is not just keeping pace with global AI innovation, it’s helping redefine it. Its enhanced language understanding, real-time responsiveness and open-source flexibility make it a compelling option for businesses looking to unlock deeper insights, streamline operations and build more intelligent, human-like interactions.

As AI continues to mature, models like Qwen2.5 set a high bar for what’s possible in both enterprise and developer applications—from customer service automation and compliance analytics to interactive product experiences and real-time decision-making support. With Qwen 3 on the horizon, organizations have even more reason to explore how Alibaba Cloud’s multimodal AI capabilities can empower their next wave of innovation.