Hello Alex Thaman, Quota is assigned to your subscription on a per-region, per-model basis in units of Tokens-per-Minute (TPM). Your subscription is onboarded with a default quota for most models. You can allocate TPM among deployments until reaching quota. If you exceed a model's TPM limit in a region, you can reassign quota among deployments or request a quota increase. Alternatively, if viable, consider creating a deployment in a new Azure region in the same geography as the existing one.
For example, with a 240,000 TPM quota for GPT-35-Turbo in East US, you could create one deployment of 240K TPM, two of 120K TPM each, or multiple deployments adding up to less than 240K TPM in that region.
There is also a limit of 30 Azure OpenAI resource instances per region. So, the one that you're referring to in the above screenshot would represent the limits in terms of number of OpenAI instances per region or the TPM. Here's a useful reference -- https://techcommunity.microsoft.com/t5/fasttrack-for-azure/optimizing-azure-openai-a-guide-to-limits-quotas-and-best/ba-p/4076268
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