Microsoft Azure AI Engineer Associate AI-102 Practice Question
Your project in Azure AI Foundry must summarize support tickets containing up to 14 000 tokens and use Azure OpenAI function calling to write the summary to Cosmos DB. You are preparing the Deploy Model step in Foundry Studio. Which model should you select and deploy to satisfy these requirements while keeping cost as low as possible?
Deploy the gpt-35-turbo-16k chat completion model.
Deploy the text-embedding-ada-002 embeddings model.
The gpt-35-turbo-16k model offers a 16 000-token context window-enough for the 14 000-token inputs-and natively supports the Azure OpenAI function calling feature. It is significantly less expensive than any GPT-4 variant, making it the most cost-effective choice that still fulfils both the context-length and function-calling requirements.
GPT-4-32k also meets the technical requirements but costs considerably more. text-davinci-003 is a completions model with only a 4 000-token limit and no function-calling capability. text-embedding-ada-002 is an embeddings model, not a chat/completions model, so it cannot generate summaries or call functions.
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