爱好者调优 Strata 提升 Qwen 解码速度
一名爱好者在配备 RTX 4090、48 GB 内存和 Ryzen 9 3900X 的设备上，用 Strata 0.1.43 运行 IQ3_S Qwen3.8-Flash-Next；在 20 万 token 上下文下，测得 2076 token 预填充和平均 95–105 token/s 解码速度。其网格搜索显示，启用 --adapt-async 1、--kv-resident 20480 和 STRATA_ADAPT_LAG=2 后，速度从 97 提升至 142 token/s。作者还发现，--ple-io ram、显式设置大型 --expert-cache 以及 --no-prefill-borrow 分别令吞吐下降 90%、72% 和 46%。
这份报告为使用 Strata 运行 Qwen3.8-Flash-Next 长上下文任务的本地用户提供了详细且可复现的配置起点，但单一且非官方的测试限制了更广泛的可信度。
TLDR: IQ3_S Qwen3.8-Flash-Next, RTX 4090 + 48 GB + Ryzen 3900X, Windows, 200k context. Ran essentially a grid search on a ton of flags: decode 97 → 142 tok/s (+45%) for three flags. Most relevant: --adapt-async 1, --kv-resident 20480, STRATA_ADAPT_LAG=2. Worst: --expert-cache is in MiB not slots (−72% if you fill the card), --ple-io ram (−90% on 48 GB), --no-prefill-borrow (−46%). One lever still locked: Windows sucks and doesnt pin memory w cuda , so every host -> GPU expert copy is CPU-driven.
Been using strata for a few weeks since thats all the rage (waiting until llama.cpp catches up, but tbh the age of specialized inference engines might just be how it is). Version 0.43, so im probably missing some newer flags. It updates so frequently and i hear that people were pretty mad with version 0.2.0 so im just holding off. if it aint broke dont fix it
I basically told Qwen 3.8 FN to tune itself and took a very hands-off approach. I let it do web research + spawn sub-agents to search thru strata's code.
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#Strata#Qwen3.8-Flash-Next#NVIDIA RTX 4090#AMD Ryzen 9 3900X#Windows#llama.cpp