Reasoning language models show strong performance but predominantly reason in English regardless of the input language, limiting accessibility for non‑English speakers and discarding language‑specific knowledge. The authors propose data mixing as a strategy to enhance L2 (second‑language) reasoning, enabling models to maintain consistent reasoning in the prompted language. This approach aims to improve generalization across languages and preserve the intent of multilingual queries.