Multilingual support

Overview

Claude demonstrates robust multilingual capabilities, with particularly strong performance in zero-shot tasks across languages.

Claude is capable in many languages beyond those benchmarked in the following table. Test with any languages relevant to your specific use cases.

Performance data

The following table shows zero-shot scores for Claude models on Global-MMLU, which extends the MMLU (Massive Multitask Language Understanding) test set to 42 languages. Each score is a percentage of the same model’s English score:

All scores use adaptive thinking at the max effort level. Scores exclude questions that safety classifiers blocked or that went unanswered. For each score in the table, at most 1.7 percent of the questions are excluded.

Set the response language

Claude infers the response language from the conversation, but for production applications you should state the target language explicitly. The most reliable place to do this is the system prompt, which keeps the instruction stable across every turn of a conversation.

client = anthropic.Anthropic()

message = client.messages.create(
    model="claude-opus-5-5",
    max_tokens=1024,
    system="Always respond in French, regardless of the language the user writes in.",
    messages=[{"role": "user", "content": "How do I reset my password?"}],
)

print(message.content)

If your application lets users pick a language at runtime, interpolate that choice into the system prompt rather than relying on Claude to infer it from the user’s message. To translate between two specific languages, name both: Translate the user's message from German to Korean. Respond with only the translation.

Best practices

When working with multilingual content:

1. Provide clear language context: Although Claude can detect the target language automatically, explicitly stating the input and output languages you want improves reliability. For enhanced fluency, you can prompt Claude to use “idiomatic speech as if it were a native speaker.”
2. Use native scripts: Submit text in its native script rather than transliteration for optimal results.
3. Consider cultural context: Effective communication often requires cultural and regional awareness beyond pure translation.

Also follow the general guidance in Prompt engineering overview to further improve output quality.

Language support considerations

• Claude processes input and generates output in most world languages that use standard Unicode characters.
• Performance varies by language, with particularly strong capabilities in widely spoken languages.
• Even in languages with fewer digital resources, Claude maintains meaningful capabilities.

Next steps

Availability

Multilingual support is available on every model.

API support