Learn Editor: Update provisioned-throughput.md

Author: sydneemayers

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

@@ -164,16 +164,16 @@ For provisioned deployments, we use a variation of the leaky bucket algorithm to
 1. When a request is made:
 
     a.    When the current utilization is above 100%, the service returns a 429 code with the `retry-after-ms` header set to the time until utilization is below 100%
+   
+    b.    Otherwise, the service estimates the incremental change to utilization required to serve the request by combining the prompt tokens, less any cacehd tokens, and the specified `max_tokens` in the call. A customer can receive up to a 100% discount on their prompt tokens depending on the size of their cached tokens. If the `max_tokens` parameter is not specified, the service estimates a value. This estimation can lead to lower concurrency than expected when the number of actual generated tokens is small.  For highest concurrency, ensure that the `max_tokens` value is as close as possible to the true generation size.
+   
+1. When a request finishes, we now know the actual compute cost for the call. To ensure an accurate accounting, we correct the utilization using the following logic:
 
-    b.    Otherwise, the service estimates the incremental change to utilization required to serve the request by combining prompt tokens and the specified `max_tokens` in the call. For requests that include at least 1024 cached tokens, the cached tokens are subtracted from the prompt token value. A customer can receive up to a 100% discount on their prompt tokens depending on the size of their cached tokens. If the `max_tokens` parameter is not specified, the service estimates a value. This estimation can lead to lower concurrency than expected when the number of actual generated tokens is small.  For highest concurrency, ensure that the `max_tokens` value is as close as possible to the true generation size.
-
-1.  When a request finishes, we now know the actual compute cost for the call. To ensure an accurate accounting, we correct the utilization using the following logic:
-
-    a.    If the actual > estimated, then the difference is added to the deployment's utilization.
-
-    b.    If the actual < estimated, then the difference is subtracted.
-
-1.  The overall utilization is decremented down at a continuous rate based on the number of PTUs deployed. 
+   a.    If the actual > estimated, then the difference is added to the deployment's utilization.
+   
+   b.    If the actual < estimated, then the difference is subtracted.
+   
+1. The overall utilization is decremented down at a continuous rate based on the number of PTUs deployed. 
 
 > [!NOTE]
 > Calls are accepted until utilization reaches 100%. Bursts just over 100% may be permitted in short periods, but over time, your traffic is capped at 100% utilization.
@@ -183,7 +183,7 @@ For provisioned deployments, we use a variation of the leaky bucket algorithm to
 
 #### How many concurrent calls can I have on my deployment?
 
-The number of concurrent calls you can achieve depends on each call's shape (prompt size, max_token parameter, etc.). The service continues to accept calls until the utilization reach 100%. To determine the approximate number of concurrent calls, you can model out the maximum requests per minute for a particular call shape in the [capacity calculator](https://oai.azure.com/portal/calculator). If the system generates less than the number of samplings tokens like max_token, it will accept more requests.
+The number of concurrent calls you can achieve depends on each call's shape (prompt size, `max_tokens` parameter, etc.). The service continues to accept calls until the utilization reaches 100%. To determine the approximate number of concurrent calls, you can model out the maximum requests per minute for a particular call shape in the [capacity calculator](https://oai.azure.com/portal/calculator). If the system generates less than the number of output tokens set for the `max_tokens` parameter, then the provisioned deployment will accept more requests.
 
 ## What models and regions are available for provisioned throughput?