1Z0-1127-25 OCI Generative AI Service Practice Question
An organization plans to deploy a custom fine-tuned model for a real-time chat application requiring consistent low-latency responses. They expect high throughput during business hours. Which OCI Generative AI infrastructure choice best 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 reserved compute with low latency and high throughput, ideal for production workloads with custom models. Shared infrastructure may have variable performance.
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 on-demand endpoint
Why it's wrong here
Shared infrastructure can have latency variability and is not optimized for high-throughput dedicated workloads.
- ✗
Use the OCI Generative AI Playground for production
Why it's wrong here
The Playground is for testing, not production deployment.
- ✓
Provision a Dedicated AI Cluster with the required model units
Why this is correct
Dedicated clusters offer isolated compute for low-latency inference and are suitable for custom fine-tuned models.
- ✗
Deploy the model on OCI Data Science using a custom container
Why it's wrong here
This requires manual setup and does not leverage the managed GenAI service's dedicated cluster benefits.
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