There are two principal rate limiting strategies within Azure OpenAI Service which we need to understand: Let’s delve into the details of these: TPMs are allocated to a model deployment (like gpt-35-turbo), defining the maximum。
Tokens-per-minute (TPM) is a configurable limit set per model per region within the API that provides a best prediction of your expected token usage over time. The requests-per-minute (RPM) rate limit is also set proportionally。
Yes, your babbage limit would effectively be 25M tokens per minute. If you are limited to 3,000 RPM at 2048 tokens per prompt, without batching you are correc6 tokens per minutet that you。
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