Microsoft Azure AI Engineer Associate AI-102 Practice Question
Your company needs to build a summarization endpoint that processes individual documents up to 100,000 tokens. The stakeholder insists on minimizing inference latency and cost while maintaining accuracy. You decide to use Azure OpenAI models. Which base model should you select to best meet these requirements?
GPT-4-Turbo with a 128k context window
text-embedding-ada-002
GPT-4o (128k context, optimized for speed and cost)
GPT-4o supports a 128k-token context window-enough for a 100,000-token document-and is engineered to run roughly twice as fast and at lower cost per token than GPT-4 Turbo. This makes it the best balance of large context, performance and price for the scenario. GPT-4-Turbo-128k also supports the needed context but is slower and more expensive. GPT-3.5-Turbo-16k cannot accept the required prompt length, and the Ada embedding model is not a generative language model, so it cannot directly perform summarization.
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Microsoft Azure AI Engineer Associate AI-102
Plan and manage an Azure AI solution
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