Batch Api Openai. So in short, there is no point in creating an OpenAI model deploym

So in short, there is no point in creating an OpenAI model deployment in Azure if you are looking to use the batch API. . Could someone help me with this? Please note: I currently have over 100 batch requests in validating status, so cancelling and restarting them is not a feasible option. Jul 22, 2025 · Welcome to the community @harnoor_singh. The endpoints provided for batch operations in the OpenAI API allow users to efficiently manage large-scale asynchronous processing of API requests, which can be crucial for applications requiring bulk data processing or batch inference tasks. It allows me to apply the magic of LLMs to a range of use cases that were not cost effective in the past. Learn how to optimize costs for asynchronous tasks with flex processing. One of: assistants: Used in the Assistants API batch: Used in the Batch API fine-tune: Used for fine-tuning vision: Images used for vision fine-tuning user_data: Flexible file type for any purpose evals: Used for eval data sets Complete reference documentation for the OpenAI API, including examples and code snippets for our endpoints in Python, cURL, and Node. Then what were the ways to do that ? We would like to show you a description here but the site won’t allow us. One batch (2M tokens per batch) tooks 20minutes but now, one batch not finished during 12hours.

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