Our experiments on the publicly available TED talks dataset (Qi et al., 2018) show that massively multilingual many-to-many models with up to 58 languages to-and-from English are very effective in low resource settings, allowing to use high-capacity models while avoiding overfitting and achieving superior results to the current stateof-the-art on this dataset <cite>(Neubig and Hu, 2018</cite>; Wang et al., 2019) when translating into English.