ChatGPT and neural machine translation (NMT) engines such as Google Translate and DeepL each have distinct strengths and limitations when it comes to translation tasks. ChatGPT excels in producing natural-sounding and context-rich text, making it suitable for creative content like marketing copy, but struggles with consistency and precision, especially when scaling. On the other hand, NMT engines prioritize structure and consistency, adhering to glossaries and segmentation, which makes them more reliable for technical and legal content. While ChatGPT can outperform NMT in creative translation tasks, it is not optimized for all languages and can introduce issues like hallucinations and inconsistency. Machine translation post-editing (MTPE) serves as a crucial step to ensure quality by having human editors refine machine-generated translations. Utilizing a system like Lokalise, which intelligently routes content to the appropriate engine and incorporates MTPE, can help achieve a balance between speed and quality in translations.