📄 中文摘要
边缘推理仍处于初期阶段。Zenlayer的工作使得公司能够在难以到达的地方部署计算资源，用户可以快速启动虚拟机并运行推理。然而，了解这些节点实际运行情况的指标仍在追赶。作者在周末开发的Wicklee是一个用Rust编写的GPU监控工具，结合了React仪表板，旨在解决标准指标不足的问题。AI领域普遍关注数据中心级别的效率，但现有的度量标准无法全面反映边缘推理的真实表现，这促使了WES的诞生。
WES：每瓦特令牌数不足以满足边缘推理需求
出处: WES: Why Tokens Per Watt Isn't Enough for Edge Inference
发布: 2026年3月11日
📄 English Summary
WES: Why Tokens Per Watt Isn't Enough for Edge Inference
Edge inference is still in its early stages. Zenlayer enables companies to deploy computing resources in hard-to-reach locations, allowing users to quickly spin up VMs and run inference. However, the metrics for understanding the actual performance of these nodes are still lagging. The author has been developing Wicklee, a sovereign GPU fleet monitor written in Rust with an embedded React dashboard, to address the inadequacies of standard metrics. While efficiency at the data center level is a common focus in AI, existing measurement standards fail to capture the true performance of edge inference, leading to the creation of WES.