Your team needs to deploy a large open-source foundation model in Azure AI Foundry for an internal application. The workload is intermittent, with unpredictable spikes a few times per day and near-zero traffic overnight. You want to minimize idle infrastructure cost and avoid managing GPU VM capacity, while still being able to consume the model through a REST endpoint billed per token. Which deployment option should you choose?