How Small-Model Inference Can Cut Latency and Energy with KV Cache
This story is from 2026-09-08. It is preserved in the archive; the latest stories are on the live feed.
The latency and energy bottleneck in small-model inference often lies not in compute but in memory access and VRAM management. A well-designed KV Cache tiering and disaggregated storage architecture can improve both time-to-first-token (TTFT) and energy per unit of throughput. Measured on Mingxin F…
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- 2026-09-08 12:10 · DEV Community — AI
How Small-Model Inference Can Cut Latency and Energy with KV Cache