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I am using the Python SDK to access Azure OpenAI (GPT-4o / GPT-4o-mini). My usage logs show that I'm well below the Tokens-per-Minute and Requests-per-Minute limits for my instance. Even so, I so...
#2: Post edited
by
Michael
·
2025-11-25T21:23:45Z (10 months ago)
Remove suspicious link
Why Does My Azure OpenAI Deployment Occasionally Return a '429 Too Many Requests' Error Even When I Am Under the Documented Rate Limits, How to solve?
- I am using the Python SDK to access Azure OpenAI (GPT-4o / GPT-4o-mini).
- My usage logs show that I'm well below the Tokens-per-Minute and Requests-per-Minute limits for my instance.
- Even so, I sometimes get:
- 429 Too Many Requests
- Please try again later.
- This happens randomly in small batches of requests, even when exponential backoff is turned on.
- I checked:
No other deployments are using the same quota.No spikes in use.No quota exhaustion in the [Azure](https://azure.status.microsoft/en-us/status) portal.No signs of problems with the model starting up cold.- Some people online say this can happen because of regional load, hidden [rate](https://platform.openai.com/docs/guides/rate-limits) limits, or shared backend capacity, but no one really knows why.
- Has anyone looked into this in depth or found a solution that works?
Is this a problem with [Azure]( https://imatix.com/what-is-microsoft-azure/), or is there something developers need to set up differently?
- I am using the Python SDK to access Azure OpenAI (GPT-4o / GPT-4o-mini).
- My usage logs show that I'm well below the Tokens-per-Minute and Requests-per-Minute limits for my instance.
- Even so, I sometimes get:
- 429 Too Many Requests
- Please try again later.
- This happens randomly in small batches of requests, even when exponential backoff is turned on.
- I checked:
- - No other deployments are using the same quota.
- - No spikes in use.
- - No quota exhaustion in the [Azure](https://azure.status.microsoft/en-us/status) portal.
- - No signs of problems with the model starting up cold.
- Some people online say this can happen because of regional load, hidden [rate](https://platform.openai.com/docs/guides/rate-limits) limits, or shared backend capacity, but no one really knows why.
- Has anyone looked into this in depth or found a solution that works?
- Is this a problem with Azure, or is there something developers need to set up differently?
#1: Initial revision
by
MariaAllen
·
2025-11-25T11:40:43Z (10 months ago)
Why Does My Azure OpenAI Deployment Occasionally Return a '429 Too Many Requests' Error Even When I Am Under the Documented Rate Limits, How to solve?
I am using the Python SDK to access Azure OpenAI (GPT-4o / GPT-4o-mini). My usage logs show that I'm well below the Tokens-per-Minute and Requests-per-Minute limits for my instance. Even so, I sometimes get: 429 Too Many Requests Please try again later. This happens randomly in small batches of requests, even when exponential backoff is turned on. I checked: No other deployments are using the same quota. No spikes in use. No quota exhaustion in the [Azure](https://azure.status.microsoft/en-us/status) portal. No signs of problems with the model starting up cold. Some people online say this can happen because of regional load, hidden [rate](https://platform.openai.com/docs/guides/rate-limits) limits, or shared backend capacity, but no one really knows why. Has anyone looked into this in depth or found a solution that works? Is this a problem with [Azure]( https://imatix.com/what-is-microsoft-azure/), or is there something developers need to set up differently?