Back to Analytics Overview The Performance Analytics page provides comprehensive insights into LLM performance across models, features, and requests, enabling data-driven decisions for optimization and enhanced user experience. To access the report, go to Analytics > Gen AI Analytics > Performance Analytics. You can also access this report from the dashboard by selecting a model or feature in its corresponding widget.Documentation Index
Fetch the complete documentation index at: https://koreai.mintlify.app/llms.txt
Use this file to discover all available pages before exploring further.

Field Descriptions
You can sort the data alphabetically or by values in ascending or descending order. Click any record to view detailed model performance metrics, including request trends, token consumption patterns, and latency analysis.
| Field | Description |
|---|---|
| Model | The Large Language Model to which the request was made. |
| Feature | The platform feature making calls to the LLM models. |
| Requests | Total number of LLM calls made for that model-feature combination. |
| Successful Requests | Number of LLM calls that executed without errors. |
| Failed Requests | Number of LLM calls that encountered errors. Together with successful requests, provides an execution breakdown to monitor system reliability. |
| Total Tokens | Combined token count for request and response. |
| Request Tokens | The individual parts of input text (words, punctuation) given to the model to create a response. These tokens form the basis for the model’s understanding. |
| Response Tokens | The pieces of generated output (words, punctuation) showing the model’s response. These tokens form the structured output of the model. |
| Avg. Tokens per Request | Average token consumption for each request. |
| Avg. Tokens per Response | Average token consumption for each response. |
| Average Response Time | The mean time taken by the model to return a response. |
| Median Latency | Median processing time, useful for understanding response consistency. |