Clarification on Handling Multiple Requests with Azure OpenAI GPT-4 Vision Model

Question

I am a Python developer working on a use case where an image is taken as input, passed to the Azure OpenAI GPT-4 Vision model, and output is extracted data from the image.

I have deployed the model to a region where it is available on the Microsoft Azure platform. I have integrated its key and endpoint into my code and deployed my code to the server. The model has a maximum rate limit of 30 requests per minute.

I would like to understand how the model handles multiple requests that are made simultaneously by different users. Specifically, will the model process the requests one by one or in parallel?

Answer 1

Hi there Kunal Nichit

Thanks for using QandA platform.

the rate limits specified for your deployment, which in this case is 30 requests per minute. When multiple requests are made at the same time by different users, the model processes these requests within the constraints of the rate limit. This means that while the model can handle multiple incoming requests in parallel, it will queue and throttle them to ensure that the rate limit is not exceeded.

Overall, while the model is capable of parallel processing to a certain extent, adherence to the rate limit means that there will be a managed throughput to ensure optimal performance and compliance with the specified limits.\

If this helps kindly accept the answer thanks much.