Exam GES-C01 Topic 1 Question 344 Discussion

Actual exam question for Snowflake's GES-C01 exam
Question #: 344
Topic #: 1

A financial institution is deploying a sentiment analysis application that uses Snowflake Cortex 'SENTIMENT' and 'COMPLETE' functions, with different LLMs, for processing customer feedback. They are using AI Observability (Public Preview) to compare the cost- efficiency of using 'mistral-7b' versus 'claude-3-5-sonnet' as LLM judges for evaluation metrics, and also tracking the overall cost of their AI Observability usage. Which statements accurately reflect the cost implications and monitoring tools for this scenario?

A. Option A B. Option B C. Option C D. Option D E. Option E

Suggested Answer: A,D,E Vote an answer

Option A is correct because AI Observability utilizes LLM judges (such as 'mistral-7b' or 'claude-3-5-sonnet') through 'COMPLETE (SNOWFLAKE.CORTEX)' function calls to compute evaluation metrics, and these calls incur charges based on the 'tokens processed'. Option D is correct as, beyond LLM judge costs, AI Observability also incurs warehouse charges for managing evaluation runs and for queries that compute evaluation metrics. Option E is correct because the view, with a filter for 'SERVICE _ TYPE ILIKE , provides a comprehensive daily credit usage report for all AI services, which would include AI Observability's components. Option B is incorrect; the view is specifically for Document AI processing functions like '!PREDICT and 'AI_EXTRACT , not for general LLM judge usage in AI Observability. The view is more appropriate for tracking individual Cortex function calls. Option C is incorrect because while prompt sizes might be similar, the pricing for different LLMs (e.g., 'mistral-7b' at 0.12 credits per million tokens vs. 'claude-3-5-sonnet' at 2.55 credits per million tokens for AI Complete) will still result in different billed amounts due to varying per-token costs, even if the number of tokens is the same.

by Tiffany at Jul 18, 2026, 03:47 AM

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