We evaluate the performance of Chemformer and Chemformer-Large models on three downstream sequence-to-sequence tasks: direct synthesis prediction, retrosynthesis prediction and molecular optimisation. Additionally, we investigate Chemformer's ability to train simultaneously on multiple downstream discriminative tasks. Specifically, we look at three molecular property prediction tasks and biological activity prediction for 133 genes.