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articles/ai-foundry/how-to/model-catalog-overview.md

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You can deploy certain models in the model catalog with pay-per-token billing. This deployment method, also called *standard deployment*, provides a way to consume the models as APIs without hosting them on your subscription. Models are hosted in a Microsoft-managed infrastructure, which enables API-based access to the model provider's model. API-based access can dramatically reduce the cost of accessing a model and simplify the provisioning experience.
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Models that are available for deployment as pay-as-you-go deployments with Standard billing are offered by the model provider, but they're hosted in a Microsoft-managed Azure infrastructure and accessed via API. Model providers define the license terms and set the price for use of their models. The Azure Machine Learning service:
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Models that are available for deployment as standard deployments with pay-as-you-go billing are offered by the model provider, but they're hosted in a Microsoft-managed Azure infrastructure and accessed via API. Model providers define the license terms and set the price for use of their models. The Azure Machine Learning service:
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* Manages the hosting infrastructure.
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* Makes the inference APIs available.

articles/machine-learning/concept-model-catalog.md

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* **Fine-tune:** Customize fine-tunable models using your own training data and pick the best model by comparing metrics across all your fine-tuning jobs. Built-in optimizations speed up fine-tuning and reduce the memory and compute needed for fine-tuning.
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* **Deploy:** Deploy pretrained models or fine-tuned models seamlessly for inference. Models that can be deployed to managed compute can also be downloaded.
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## Model deployment: Managed compute and standard deployment with pay-as-you-go billing
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## Model deployment: Managed compute and standard deployment (pay-as-you-go)
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Model Catalog offers two distinct ways to deploy models from the catalog for your use: managed compute and standard deployments. The deployment options available for each model vary; learn more about the features of the deployment options, and the options available for specific models, in the tables below. Learn more about [data processing](concept-data-privacy.md) with the deployment options.
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