small verbiage change to bring differentiation

Author: AmarBadal

articles/ai-services/openai/concepts/provisioned-throughput.md

@@ -21,9 +21,13 @@ The provisioned throughput capability allows you to specify the amount of throug
 ## What do the provisioned deployment types provide?
 
 - **Predictable performance:** stable max latency and throughput for uniform workloads.
-- **Reserved processing capacity:** A deployment configures the amount of throughput. Once deployed, the throughput is available whether used or not.
+- **Allocated processing capacity:** A deployment configures the amount of throughput. Once deployed, the throughput is available whether used or not.
 - **Cost savings:** High throughput workloads might provide cost savings vs token-based consumption.
 
+> [!NOTE]
+> Customers can avail additional cost savings on provisioned deployments when they buy [Microsoft Azure OpenAI service reservations](https://learn.microsoft.com/en-us/azure/cost-management-billing/reservations/azure-openai#buy-a-microsoft-azure-openai-service-reservation). 
+
+
 An Azure OpenAI Deployment is a unit of management for a specific OpenAI Model. A deployment provides customer access to a model for inference and integrates more features like Content Moderation ([See content moderation documentation](content-filter.md)). Global provisioned deployments are available in the same Azure OpenAI resources as all other deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center with the best availability for each request. Similarly, data zone provisioned deployments are also available in the same resources as all other deployment types but allow you to leverage Azure's global infrastructure to dynamically route traffic to the data center within the Microsoft specified data zone with the best availability for each request. 
 
 ## What do you get?