Hello Akinropo Taiwo,
Greetings and Welcome to Microsoft Q&A! Thanks for posting the question.
I understand that you're experiencing a issue with the DeepSeek-R1 model on Azure AI Foundry, such as slow response times and occasional lack of output,
I attempted to reproduce the scenario in my environment and encountered the same lagging issue. In some cases, the output was not generated at all.
This could be due to quota limitations or capacity constraints. If your deployment has exceeded its assigned quota, it may result in throttling or significant delays in processing requests. Checking your quota limits and requesting an increase, if necessary, could help mitigate this issue.
Additionally, capacity issues within Azure AI Foundry, such as high demand for resources or insufficient replicas and partitions, might be contributing to the performance degradation. If resource allocation is limited, it can lead to lags and unresponsiveness. To improve performance, consider scaling up your deployment by increasing the number of replicas and partitions.
For further troubleshooting, check the Azure AI Foundry portal for any error messages, logs, or warnings that may indicate specific deployment issues.
Please refer this https://github.com/nicholasdbrady/cookbook/blob/main/examples/deepseek/deepseek-r1-with-azure-ai-foundry-and-gradio.ipynb,
I Hope this helps. Do let me know if you have any further queries.
If this answers your query, do click Accept Answer
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