Learn Editor: Update deployment-types.md

Author: sydneemayers

articles/ai-services/openai/how-to/deployment-types.md

@@ -13,34 +13,34 @@ ms.author: mbullwin
 
 # Azure OpenAI deployment types
 
-Azure OpenAI provides customers with choices on the hosting structure that fits their business and usage patterns. The service offers two main types of deployment: **standard** and **provisioned**. Standard is offered with a global deployment option, routing traffic globally to provide higher throughput. All deployments can perform the exact same inference operations, however the billing, scale and performance are substantially different. As part of your solution design, you will need to make two key decisions:
+Azure OpenAI provides customers with choices on the hosting structure that fits their business and usage patterns. The service offers two main types of deployment: **standard** and **provisioned**. Standard is offered with a global deployment option, routing traffic globally to provide higher throughput. Provisioned is also offered with a global deployment option, allowing customers to purchase and deploy provisioned throughput units across Azure global infrastructure. All deployments can perform the exact same inference operations, however the billing, scale and performance are substantially different. As part of your solution design, you will need to make two key decisions:
 
 - **Data residency needs**: global vs. regional resources  
 - **Call volume**: standard vs. provisioned
 
 ## Global versus regional deployment types
 
-For standard deployments you have an option of two types of configurations within your resource – **global** or **regional**. Global standard is the recommended starting point. 
+For standard and provisioned deployments, you have an option of two types of configurations within your resource – **global** or **regional**. Global standard is the recommended starting point. 
 
-Global deployments leverage Azure's global infrastructure, dynamically route customer traffic to the data center with best availability for the customer’s inference requests. This means you will get the higest initial throughput limits and best model availability with Global while still providing our uptime SLA and low latency.For high voulmne workloads above the specified usage tiers, you may experience increased latency variation. For customers that require the lower latency variance at large workload usage, we recommend purchasing provisioned throughput.
+Global deployments leverage Azure's global infrastructure, dynamically route customer traffic to the data center with best availability for the customer’s inference requests. This means you will get the highest initial throughput limits and best model availability with Global while still providing our uptime SLA and low latency. For high volume workloads above the specified usage tiers on standard and global standard, you may experience increased latency variation. For customers that require the lower latency variance at large workload usage, we recommend purchasing provisioned throughput.
 
 Our global deployments will be the first location for all new models and features. Customers with very large throughput requirements should consider our provisioned deployment offering.
 
 ## Deployment types
 
 Azure OpenAI offers three types of deployments. These provide a varied level of capabilities that provide trade-offs on: throughput, SLAs, and price. Below is a summary of the options followed by a deeper description of each.
 
-| **Offering** | **Global-Batch** | **Global-Standard** | **Standard** | **Provisioned**  |
-|---|:---|:---|:---|:---|
-| **Best suited for**      | Offline scoring <br><br> Workloads that are not latency sensitive and can be completed in hours.<br><br> For use cases that do not have data processing residency requirements.| Recommended starting place for customers. <br><br>Global-Standard will have the higher default quota and larger number of models available than Standard. | For customers with data residency requirements. Optimized for low to medium volume. | Real-time scoring for large consistent volume. Includes the highest commitments and limits.|
-| **How it works**         | Offline processing via files |Traffic may be routed anywhere in the world | | |
-| **Getting started**      | [Global-Batch](./batch.md) | [Model deployment](./create-resource.md) | [Model deployment](./create-resource.md) | [Provisioned onboarding](./provisioned-throughput-onboarding.md) |
-| **Cost**                 | [Least expensive option](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) <br> 50% less cost compared to Global Standard prices. Access to all new models with larger quota allocations.  | [Global deployment pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) |  [Regional pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) | May experience cost savings for consistent usage |
-| **What you get**         |[Significant discount compared to Global Standard](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) | Easy access to all new models with highest default pay-per-call limits.<br><br> Customers with high volume usage may see higher latency variability | Easy access with [SLA on availability](https://azure.microsoft.com/support/legal/sla/). Optimized for low to medium volume workloads with high burstiness. <br><br>Customers with high consistent volume may experience greater latency variability. | Regional access with very high & predictable throughput. Determine throughput per PTU using the provided [capacity calculator](./provisioned-throughput-onboarding.md#estimate-provisioned-throughput-and-cost) |
-| **What you don’t get**   |❌Real-time call performance <br><br>❌Data processing guarantee<br> <br> Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/)  |❌Data processing guarantee<br> <br> Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/) | ❌High volume w/consistent low latency | ❌Pay-per-call flexibility |
-| **Per-call Latency**     | Not Applicable (file based async process) | Optimized for real-time calling & low to medium volume usage. Customers with high volume usage may see higher latency variability. Threshold set per model | Optimized for real-time calling & low to medium volume usage. Customers with high volume usage may see higher latency variability. Threshold set per model | Optimized for real-time. |
-| **Sku Name in code**     |  `GlobalBatch` |   `GlobalStandard`               | `Standard`   |      `ProvisionedManaged`       |
-| **Billing model**        |  Pay-per-token |Pay-per-token | Pay-per-token | Monthly Commitments |
+| **Offering** | **Global-Batch** | **Global-Standard**|  **Global-Provisioned**  | **Standard** | **Provisioned**  |
+|---|:---|:---| -------- |:---|:---|
+| **Best suited for**      | Offline scoring <br><br> Workloads that are not latency sensitive and can be completed in hours.<br><br> For use cases that do not have data processing residency requirements.|Recommended starting place for customers. <br><br>Global-Standard will have the higher default quota and larger number of models available than Standard. |Real-time scoring for large consistent volume. Includes the highest commitments and limits.                                                                                               For use cases that do not have data residency requirements.| For customers with data residency requirements. Optimized for low to medium volume. |Real-time scoring for large consistent volume. Includes the highest commitments and limits.                                                                                          For use cases with data residency requirements|
+| **How it works**         | Offline processing via files |Traffic may be routed anywhere in the world |Traffic may be routed anywhere in the world| | |
+| **Getting started**      | [Global-Batch](./batch.md) | [Model deployment](./create-resource.md) |[Provisioned onboarding](/azure/ai-services/openai/how-to/provisioned-throughput-onboarding)| [Model deployment](./create-resource.md) | [Provisioned onboarding](./provisioned-throughput-onboarding.md) |
+| **Cost**                 | [Least expensive option](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) <br> 50% less cost compared to Global Standard prices. Access to all new models with larger quota allocations.  | [Global deployment pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) |May experience cost savings for consistent usage|  [Regional pricing](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) |May experience cost savings for consistent usage |
+| **What you get**         |[Significant discount compared to Global Standard](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/) | Easy access to all new models with highest default pay-per-call limits.<br><br> Customers with high volume usage may see higher latency variability |Access to high & predictable throughput across Azure global infrastructure. Determine throughput per PTU using the provided [capacity calculator](/azure/ai-services/openai/how-to/provisioned-throughput-onboarding). | Easy access with [SLA on availability](https://azure.microsoft.com/support/legal/sla/). Optimized for low to medium volume workloads with high burstiness. <br><br>Customers with high consistent volume may experience greater latency variability. | Regional access with very high & predictable throughput. Determine throughput per PTU using the provided [capacity calculator](./provisioned-throughput-onboarding.md#estimate-provisioned-throughput-and-cost) |
+| **What you don’t get**   |❌Real-time call performance <br><br>❌Data processing guarantee<br> <br> Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/)  |❌Data processing guarantee<br> <br> Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/) |❌Pay-per-call flexibility <br> <br>❌Data processing guarantee<br> <br> Data stored at rest remains in the designated Azure geography, while data may be processed for inferencing in any Azure OpenAI location. [Learn more about data residency](https://azure.microsoft.com/explore/global-infrastructure/data-residency/)| ❌High volume w/consistent low latency | ❌Pay-per-call flexibility |
+| **Per-call Latency**     | Not Applicable (file based async process) | Optimized for real-time calling & low to medium volume usage. Customers with high volume usage may see higher latency variability. Threshold set per model |Optimized for real-time calling & high-volume usage. | Optimized for real-time calling & low to medium volume usage. Customers with high volume usage may see higher latency variability. Threshold set per model |Optimized for real-time calling & high volume usage.|
+| **Sku Name in code**     |  `GlobalBatch` |   `GlobalStandard`               |`GlobalProvisionedManaged`| `Standard`   |      `ProvisionedManaged`       |
+| **Billing model**        |  Pay-per-token |Pay-per-token |Hourly billing with optional purchase of monthly or yearly reservations| Pay-per-token |Hourly billing with optional purchase of monthly or yearly reservations|
 
 ## Provisioned