Qwen 2.5: A Comprehensive Review of the Leading Resource-Efficient LLM with potentioal to Surpass All Competitors
Imtiaz Ahmed, Shahid Ul Islam, Partha Protim Datta, Imran Kabir, N Chowdhury, Ahshanul Haque
Abstract
The purpose of the review is to provide a comprehensive analysis of Qwen 2.5, highlighting its advancements in AI models. Key findings indicate that Qwen 2.5 features significant improvements in dataset size (expanding from 7 trillion to 18 trillion tokens), enhanced multilingual support (29+ languages focused on Asian languages), and innovative architectural mechanisms that facilitate efficient context processing and multimodal integration. Qwen 2.5's significance in the field of AI lies in its opensource approach, which encourages collaboration and adoption in various applications, making it a formidable competitor against existing AI models from other major players like OpenAI and Meta. Its advanced capabilities make it particularly relevant for industries looking to leverage AI for diverse tasks, as it addresses challenges in processing long texts and integrating multiple data modalities. The model's design and performance strengthen Alibaba's position in the AI landscape, positioning Qwen 2.5 as a crucial development to examine for future AI advancements.