The ability to reason about tabular or semi-structured knowledge is a fundamental problem for today’s Natural Language Processing (NLP) systems. While significant progress has been achieved in the direction of tabular reasoning, these advances are limited to English due to the absence of multilingual benchmark datasets for semi-structured data. In this paper, we use machine translation methods to construct a multilingual tabular NLI dataset, namely XINFOTABS, which expands the English tabular NLI dataset of INFOTABS to ten diverse languages. We also present several baselines for multilingual tabular reasoning, e.g., machine translation-based methods and cross-lingual. We discover that the XINFOTABS evaluation suite is both practical and challenging. As a result, this dataset will contribute to increased linguistic inclusion in tabular reasoning research and applications.