The same training set and hyperparameter ranges as in the 1M model were used and the same procedure to obtain the best UC-JSD was performed. The best models with best UC-JSD were sampled 2 billion times and results show (Table , Suppl. Table complete) that the performance is consistently lower than using normal canonical SMILES. This is especially marked with the new ring syntax, from which only a model training up to 68.6 % of GDB-13 was obtained. The other syntax change, branching, was the best of the three, having a slightly worse performance than the canonical SMILES models. When the two syntax changes are used the performance is the worst of the three variants. The validity is generally 1-3% lower than in canonical SMILES, possibly indicating that the model has difficulties in learning the basics of the syntax.