update

Author: mrbullwinkle

articles/ai-services/openai/quotas-limits.md

@@ -10,7 +10,7 @@ ms.custom:
   - ignite-2023
   - references_regions
 ms.topic: conceptual
-ms.date: 11/11/2024
+ms.date: 01/09/2025
 ms.author: mbullwin
 ---
 
@@ -61,26 +61,26 @@ The following sections provide you with a quick guide to the default quotas and
 
 [!INCLUDE [Quota](./includes/global-batch-limits.md)]
 
-## o1-preview & o1-mini rate limits
+## o1 & o1-mini rate limits
 
 > [!IMPORTANT]
 > The ratio of RPM/TPM for quota with o1-series models works differently than older chat completions models:
 >
 > - **Older chat models:** 1 unit of capacity = 6 RPM and 1,000 TPM.
-> - **o1-preview:** 1 unit of capacity = 1 RPM and 6,000 TPM.
+> - **o1 & o1-preview:** 1 unit of capacity = 1 RPM and 6,000 TPM.
 > - **o1-mini:** 1 unit of capacity = 1 RPM per 10,000 TPM.
 >
 > This is particularly important for programmatic model deployment as this change in RPM/TPM ratio can result in accidental under allocation of quota if one is still assuming the 1:1000 ratio followed by older chat completion models.
 >
 > There is a known issue with the [quota/usages API](/rest/api/aiservices/accountmanagement/usages/list?view=rest-aiservices-accountmanagement-2024-06-01-preview&tabs=HTTP&preserve-view=true) where it assumes the old ratio applies to the new o1-series models. The API returns the correct base capacity number, but does not apply the correct ratio for the accurate calculation of TPM.
 
-### o1-preview & o1-mini global standard
+### o1 & o1-mini global standard
 
 | Model|Tier| Quota Limit in tokens per minute (TPM) | Requests per minute |
 |---|---|:---:|:---:|
-| `o1-preview` | Enterprise agreement | 30 M | 5 K |
+| `o1` & `o1-preview` | Enterprise agreement | 30 M | 5 K |
 | `o1-mini`| Enterprise agreement | 50 M | 5 K |
-| `o1-preview` | Default | 3 M | 500 |
+| `o1` & `o1-preview` | Default | 3 M | 500 |
 | `o1-mini`| Default | 5 M | 500 |
 
 ### o1-preview & o1-mini standard
@@ -179,9 +179,9 @@ To minimize issues related to rate limits, it's a good idea to use the following
 - Test different load increase patterns.
 - Increase the quota assigned to your deployment. Move quota from another deployment, if necessary.
 
-### How to request increases to the default quotas and limits
+## How to request increases to the default quotas and limits
 
-Quota increase requests can be submitted from the [Quotas](./how-to/quota.md) page in the Azure AI Foundry portal. Due to high demand, quota increase requests are being accepted and will be filled in the order they're received. Priority is given to customers who generate traffic that consumes the existing quota allocation, and your request might be denied if this condition isn't met.
+Quota increase requests can be submitted via the [quota increase request form](https://aka.ms/oai/stuquotarequest). Due to high demand, quota increase requests are being accepted and will be filled in the order they're received. Priority is given to customers who generate traffic that consumes the existing quota allocation, and your request might be denied if this condition isn't met.
 
 For other rate limits, [submit a service request](../cognitive-services-support-options.md?context=/azure/ai-services/openai/context/context).