Cross-layer sharing, rank-1 projections, sparse gate, low-rank head, frozen scaling params
Under load, this creates GC pressure that can devastate throughput. The JavaScript engine spends significant time collecting short-lived objects instead of doing useful work. Latency becomes unpredictable as GC pauses interrupt request handling. I've seen SSR workloads where garbage collection accounts for a substantial portion (up to and beyond 50%) of total CPU time per request — time that could be spent actually rendering content.
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litertlm — 这是 Google 推出的一种新格式,是 .task 的升级版,具有更好的压缩效果和额外的元数据。MediaPipe 也可以在 iOS、Android 和 Web 上运行 .litertlm,但不具备 NPU 等额外功能。 .litertlm 的主要优势在于其独立的运行时 LiteRT-LM:它支持 NPU(神经处理单元),可实现更强大的加速,并支持桌面平台——Linux、macOS、Windows,甚至 Raspberry Pi。但 LiteRT-LM 运行时目前仍处于早期预览阶段:iOS 和 Web 平台暂不支持(即将推出)。