This paper outlines our winning submission to the English-to-Tatar translation task. We evaluated three strategies: few-shot prompting with Gemini 3 Pro Preview, specialized trans-tokenized Tweeties models, and the RL-distilled TranslateGemma family. Results demonstrate that large commercial models significantly outperform smaller specialized ones in this low-resource setting. Gemini secured first place with a chrF++ score of 56.71, surpassing the open-source baseline of 25.23.