Researchers developed Tiny Aya L2-Thinker, a 3.35B multilingual reasoning model that reasons in the user's language rather than defaulting to English, achieving over 93% L2 reasoning rate across 60 languages on six benchmarks. The work demonstrates that reasoning capabilities can be transferred across typologically diverse languages through optimized data composition and scheduling in supervised fine-tuning, without requiring reasoning supervision in each target language.