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What formulas determine cost per token and yearly depreciation for LLM inference?

To estimate the amount of hardware and software licenses required and the associated cost, follow these steps and a hypothetical example First, collect and identify the cost information corresponding to both hardware and software. Next, calculate the total cost following the steps: Number of servers is calculated as the number of instances times the GPUs per instance, divided by the number of GPUs per server. Yearly server cost is calculated as the initial server cost divided by the depreciation period (in years), adding the yearly software licensing and hosting costs per server. Total cost is

LLM Inference Benchmarking: How Much Does Your LLM Inference Cost? | NVIDIA Technical Blog
How do you calculate required server capacity for peak LLM request volumes?

To calculate the required infrastructure for a given LLM application, we need to identify the following constraints:  Latency type and maximum value. This typically depends on the nature of the applications. For example, for chat applications with live interactive responses, keep the average time to first token at or below 250 ms to ensure responsiveness. Planned peak requests/s. Account for how many concurrent requests the system is expected to serve. Note that this isn’t the same as the number of concurrent users, because not all will have an active request at once.  Using this information,

LLM Inference Benchmarking: How Much Does Your LLM Inference Cost? | NVIDIA Technical Blog