GPU Utilization
The proportion of time within a given window during which a GPU is actually performing effective computational tasks; it is a core metric by which large-model companies measure compute utilization efficiency. The industry average utilization is about 25%–27%, and after optimization it can be raised above 40%, directly reducing compute costs.
Timeline (last 90 days)
If the GPU is processing requests only 30% of the time, the actual cost per token is about 3.3 times that under the full-load assumption (nominal cost ÷ utilization).
Identifying stragglers requires end-to-end observability: collecting metrics such as GPU utilization, communication wait time, CPU reduction time and frontend queuing delay separately to locate the shortest stave of the barrel.
Utilization data itself lacks a unified disclosure standard, and the calibers cited by different parties vary considerably.
GPU utilization is the decisive factor in the buy-versus-rent decision; if cluster utilization is only 30%, the break-even time must be multiplied by three.
All Facts (4)
If the GPU is processing requests only 30% of the time, the actual cost per token is about 3.3 times that under the full-load assumption (nominal cost ÷ utilization).
50%UnverifiedIdentifying stragglers requires end-to-end observability: collecting metrics such as GPU utilization, communication wait time, CPU reduction time and frontend queuing delay separately to locate the shortest stave of the barrel.
50%UnverifiedUtilization data itself lacks a unified disclosure standard, and the calibers cited by different parties vary considerably.
50%UnverifiedGPU utilization is the decisive factor in the buy-versus-rent decision; if cluster utilization is only 30%, the break-even time must be multiplied by three.
50%