Large Language Models (LLMs) represent discursive formations that both shape and are shaped by global geopolitical imaginaries. They (re-)produce hierarchies of power relations, constructing some regions as sites of strategic importance while rendering others peripheral, some as potential threats while others as zones of opportunity. This study investigates how the interaction between ChatGPT-4-generated questions and DeepSeek-R1 responses, mediated by the author, functions as a dialogic space that (re-)constructs broader geopolitical imaginations. It adopts a qualitative approach grounded in discursive geopolitics, historical approach to discourse (HAD), and pragmasemiotic emphasis on textual agency. The primary dataset consists of ChatGPT’s prompted questions about seven geopolitically sensitive topics (CCP media control; Crimea; Uyghurs/Xinjiang; Chinese tech influence; U.S.–China trade; Great Firewall; Liu Xiaobo) and DeepSeek’s responses and its algorithmic behaviours (erasure messages, disclaimers, warnings, and suggested topic shifts). The conversational exchanges between ChatGPT and DeepSeek reveal how LLMs function not merely as data-generation tools but as a geopolitical actor that enacts national identity projects and ideological alignments.