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

An organization requires low-latency inference for a custom fine-tuned model deployed on OCI Generative AI. The model must be isolated from other tenants. Which infrastructure choice meets these requirements?

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

Provision a dedicated AI cluster with the required model units

A dedicated AI cluster provides isolated, low-latency inference for custom models. Shared infrastructure does not guarantee isolation and may have higher latency due to contention.

Answer analysis

Option-by-option breakdown

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

  • Use the shared infrastructure endpoint for the fine-tuned model

    Why it's wrong here

    Shared infrastructure does not provide tenant isolation and may have variable latency.

  • Deploy the model on OCI Data Science model deployment

    Why it's wrong here

    OCI Data Science deployments do not offer the same dedicated GPU isolation as GenAI dedicated clusters for inference.

  • Provision a dedicated AI cluster with the required model units

    Why this is correct

    A dedicated AI cluster provides isolated compute resources, ensuring low latency and no interference from other workloads.

  • Use an on-premises GPU server and call OCI GenAI via API gateway

    Why it's wrong here

    The requirement is for OCI GenAI managed service; on-premises is not part of the service.

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