A new benchmark for zero-shot topic localization in historical Czech documents has been introduced. The benchmark includes a human-annotated dataset with topics and annotated spans, and evaluates the performance of large language models and BERT-based models. The results show variability among LLMs, with some approaching human agreement, making it a useful resource for testing and improving LLMs.