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1Z0-1127-25 OCI Generative AI Service Practice Question

A team is building a multilingual semantic search application. They need to index documents in English, Spanish, and French, and later search using queries in any of these languages. Which embedding model should they use?

Answer choices

Why each option matters

Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.

Correct answer & explanation

Cohere embed-multilingual-v3.0

Cohere embed-multilingual-v3.0 supports multiple languages in a single model, enabling cross-lingual semantic search. embed-english-v3.0 is English-only. Command R and Llama 3 are not embedding models.

Answer analysis

Option-by-option breakdown

For each option: why learners choose it and why it is or isn't the right answer here.

  • Meta Llama 3 70B

    Why it's wrong here

    Llama 3 is a general-purpose LLM, not an embedding model.

  • Cohere Command R

    Why it's wrong here

    Command R is a generation model, not an embedding model.

  • Cohere embed-multilingual-v3.0

    Why this is correct

    This model is designed for multilingual text, supporting English, Spanish, French, and many other languages.

  • Cohere embed-english-v3.0

    Why it's wrong here

    This model only handles English, not Spanish or French.

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