Azure OpenAI Service quotas and limits

This article contains a quick reference and a detailed description of the quotas and limits for Azure OpenAI in Azure AI services.

Quotas and limits reference

The following sections provide you with a quick guide to the default quotas and limits that apply to Azure OpenAI:

Limit Name	Limit Value
OpenAI resources per region per Azure subscription	30
Default DALL-E quota limits	2 concurrent requests
Maximum prompt tokens per request	Varies per model. For more information, see Azure OpenAI Service models
Max fine-tuned model deployments	2
Total number of training jobs per resource	100
Max simultaneous running training jobs per resource	1
Max training jobs queued	20
Max Files per resource	30
Total size of all files per resource	1 GB
Max training job time (job will fail if exceeded)	720 hours
Max training job size (tokens in training file) x (# of epochs)	2 Billion
Max size of all files per upload (Azure OpenAI on your data)	16 MB

Regional quota limits

The default quota for models varies by model and region. Default quota limits are subject to change.

Model	Regions	Tokens per minute
gpt-35-turbo	East US, South Central US, West Europe, France Central, UK South	240 K
	North Central US, Australia East, East US 2, Canada East, Japan East, Sweden Central, Switzerland North	300 K
gpt-35-turbo-16k	East US, South Central US, West Europe, France Central, UK South	240 K
	North Central US, Australia East, East US 2, Canada East, Japan East, Sweden Central, Switzerland North	300 K
gpt-4	East US, South Central US, West Europe, France Central	20 K
	North Central US, Australia East, East US 2, Canada East, Japan East, UK South, Sweden Central, Switzerland North	40 K
gpt-4-32k	East US, South Central US, West Europe, France Central	40 K
	North Central US, Australia East, East US 2, Canada East, Japan East, UK South, Sweden Central, Switzerland North	80 K
text-embedding-ada-002	East US, South Central US, West Europe, France Central	240 K
	North Central US, Australia East, East US 2, Canada East, Japan East, UK South, Switzerland North	350 K
all other models	East US, South Central US, West Europe, France Central	120 K

General best practices to remain within rate limits

To minimize issues related to rate limits, it's a good idea to use the following techniques:

• Implement retry logic in your application.
• Avoid sharp changes in the workload. Increase the workload gradually.
• 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

Quota increase requests can be submitted from the Quotas page of Azure OpenAI Studio. Please note that due to overwhelming demand, we are not currently approving new quota increase requests. Your request will be queued until it can be filled at a later time.

For other rate limits, please submit a service request.

Next steps

Explore how to manage quota for your Azure OpenAI deployments. Learn more about the underlying models that power Azure OpenAI.