Models behave differently across languages due to tokenizer distributions and training bias. Multi-lingual prompting requires explicitly calibrating instructions, formatting schema compliance, and testing few-shot patterns across target languages to prevent translation bugs.
To ensure formatting (like JSON output) is maintained when the model generates text in other languages, you must provide language-specific few-shot examples and keep schema keys in English to prevent parser crashes.