How to find regions & models that have quota available for OpenAi Models? (Pay as you go)

You can check available regional quotas and model capacities directly inside the Azure AI Foundry portal under Management > Quota.

You can also check capacity programmatically through the Azure capacity API. The API can be queried using your subscriptionId, model_name, and model_version to determine available capacity pools for the model and version you want to deploy. This is useful for automation because you can query multiple regions first, identify regions with sufficient capacity, and then deploy to an appropriate region without repeatedly attempting deployments that fail because of capacity limitations.

For example, the following Python code uses the Azure REST API to query model capacity for a subscription. You need an Azure access token with appropriate permissions, and you should substitute your subscription ID, model name, and model version.

import requests
from azure.identity import DefaultAzureCredential

subscription_id = "YOUR-SUBSCRIPTION-ID"
model_name = "gpt-4.1"
model_version = "2025-04-14"

credential = DefaultAzureCredential()
token = credential.get_token("https://management.azure.com/.default").token

url = (
f"https://management.azure.com/subscriptions/{subscription_id}"
f"/providers/Microsoft.CognitiveServices/locations"
f"?api-version=2023-05-01"
)

headers = {
"Authorization": f"Bearer {token}",
"Content-Type": "application/json"
}

response = requests.get(url, headers=headers)
response.raise_for_status()

locations = response.json().get("value", [])

for location in locations:
region = location["name"]
print(region)

The specific capacity endpoint and API version can vary as Microsoft changes the Azure AI Foundry capacity APIs, so for production automation you should use the current capacity API documented for the model and deployment type you are checking.

Another option is to use Global Standard deployments instead of trying to obtain Standard capacity in a specific region such as East US 2. Global Standard uses a shared capacity pool across multiple Azure regions rather than relying solely on capacity available in one individual region. This can help when a particular regional capacity pool is constrained, although the model, deployment type, quota, and availability still have to support Global Standard.

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hth

Marcin