Clarify quota limit is per model, region, and subscription

Author: nachoalonsoportillo

articles/cognitive-services/openai/how-to/quota.md

@@ -21,7 +21,7 @@ Quota provides the flexibility to actively manage the allocation of rate limits
 Azure OpenAI's quota feature enables assignment of rate limits to your deployments, up-to a global limit called your “quota.”  Quota is assigned to your subscription on a per-region, per-model basis in units of **Tokens-per-Minute (TPM)**. When you onboard a subscription to Azure OpenAI, you'll receive default quota for most available models. Then, you'll assign TPM to each deployment as it is created, and the available quota for that model will be reduced by that amount. You can continue to create deployments and assign them TPM until you reach your quota limit. Once that happens, you can only create new deployments of that model by reducing the TPM assigned to other deployments of the same model (thus freeing TPM for use), or by requesting and being approved for a model quota increase in the desired region.
 
 > [!NOTE]
-> With a quota of 240,000 TPM for GPT-35-Turbo in East US, a customer can create a single deployment of 240K TPM, 2 deployments of 120K TPM each, or any number of deployments in one or multiple Azure OpenAI resources as long as their TPM adds up to less than 240K total in that region.
+> With a quota of 240,000 TPM for GPT-35-Turbo in East US, a customer can create a single deployment of 240K TPM, 2 deployments of 120K TPM each, or any number of deployments in one or multiple Azure OpenAI resources as long as their TPM adds up to less than 240K total in that region for that subscription.
 
 When a deployment is created, the assigned TPM will directly map to the tokens-per-minute rate limit enforced on its inferencing requests. A **Requests-Per-Minute (RPM)** rate limit will also be enforced whose value is set proportionally to the TPM assignment using the following ratio: