This study examines the English translation of Cao Zhi's poetry from the perspective of the cultural turn, comparing Xu Yuanchong's translations with those generated by the large language models DeepSeek and ChatGPT. Cao Zhi's poetry features concise imagery, rich cultural connotations, and multi-layered emotional expression, making its translation crucial for cross-cultural communication. The study analyzes translations across dimensions such as cultural transmission, imagery transformation, emotional atmosphere, and the realization of cultural function, while also exploring the impact of prompt optimization on the models' translation strategies. Results show that Xu Yuanchong, as a culturally grounded translator, achieves cultural and aesthetic regeneration through creative adaptation. The two language models excel in semantic transmission but adopt different strategies for cultural reconstruction: DeepSeek emphasizes preserving cultural markers and contextual integrity, whereas ChatGPT favors emotional and universalized expression. Prompt guidance can partially influence the models' cultural rendering, poetic structure, and imagery handling, but cannot fully replace human translators' agency in cultural judgment and aesthetic choice. This study contributes to the understanding of poetry translation from a cultural perspective and provides insights for human-AI collaborative translation and model optimization.