This study conducts a corpus-based comparative analysis of the translation styles of ChatGPT4o and the official human translation of the 2025 Chinese Government Work Report. Drawing on a multi-level stylistic framework, it integrates quantitative and qualitative analysis to examine salient features at the lexical, syntactic, and textual levels. Findings show systematic stylistic divergences. Lexically, the official translation exhibits a significant overuse of “will” and underuse of “can” relative to ChatGPT, and it consistently employs the explicitation stategy to clarify China-specific terms and abbreviations. ChatGPT, by contrast, tends toward literal translation and occasional transliteration, producing a more compressed but less interpretively informative rendering. Syntactically, the official version strongly favors agentive declaratives, whereas ChatGPT relies heavily on imperative structures; the two also differ significantly in passive usage. Textually, the official translation prefers additive progression aligned with recurring institutional frames, while ChatGPT more frequently uses “while + V-ing” to condense inter-clausal relations, altering tone and perceived authority. The study attributes these differences to institutional skopos and norms, cross-linguistic discourse tendencies, and the absence of political-communicative constraints in LLM output, and it outlines implications for prompt design, materials of varied genres and registers, and different LLMs.