Inference cost refers to the cost of running an AI model, including electricity costs, server time, and processing costs, every time it receives a request from a user. As a model’s userbase grows, it becomes critical to keep inference costs under control.
Because each query consumes a specific amount of expensive compute power, models become significantly more expensive to run as the userbase expands from a few people within an organization to an entire workforce or customer base. The inference cost can quickly become the largest ongoing expense in a project. Planning for these rising costs is essential to maintaining a healthy ROI and ensuring that the model stays affordable to provide as it becomes more popular.
