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Kimi was trained Chinese-first and is excellent across languages. Learn how to write multilingual prompts that take advantage of that — without accidentally degrading the output.
Kimi was trained on a corpus heavily weighted toward Chinese — including academic, legal, and literary sources that Western-headquartered models have less exposure to. Its English is excellent, but its Chinese is exceptional. That asymmetry is real and exploitable.
System (Chinese): 你是一名资深律师助理。请仅根据下面的合同段落作答,并标注出处。
User: Read the attached contract and answer in English: which clauses limit our indemnification?
Assistant: I will analyze the Chinese contract internally and report the
relevant clauses (with citations) in English.A Chinese system prompt grounds the model in its strongest language; the user gets the answer in their language.| Prompt language | Source language | Output language | Behavior |
|---|---|---|---|
| Chinese | Chinese | Chinese | Best raw quality |
| Chinese | Chinese | English | Strong, with translation step |
| English | Chinese | English | Good, but loses some nuance |
| English | English | English | On par with Western models |
The big idea: write prompts in the strongest language for the source. Kimi rewards you for going Chinese-first when the documents are Chinese — and English where English is the source language.
15 questions · take it digitally for instant feedback at tendril.neural-forge.io/learn/quiz/end-moonshot-multilingual-prompts-creators
What is the core idea behind "Multilingual Prompting on Kimi: Chinese-First, Globally Capable"?
Which term best describes a foundational idea in "Multilingual Prompting on Kimi: Chinese-First, Globally Capable"?
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