In the PlyLoom Arena: Qwen vs. DeepSeek

In a recent experiment published on Habr, the author conducts a comparative analysis of responses from two advanced language models: QWEN 3.8 MAX and DEEPSEEK V4. The main goal of the study is to evaluate the quality and structure of graph-based responses generated by these neural networks when processing identical cross-referenced queries. To visualize and compare the data, the author utilized the PlyLoom platform. This tool allows for a clear representation of the differences in logic and completeness of the answers provided by the models. The experiment highlights the importance of comparative LLM testing to understand their strengths and weaknesses in tasks requiring structured information representation. This approach helps developers and researchers navigate the rapidly growing landscape of generative AI, enabling them to select the most suitable tools for specific applied tasks.