After pushing 1M+ tokens through Qwen 3.8 27B, here is my optimal llama.cpp config for 16GB VRAM (73k Context, Agentic Coding)
英文标题:After pushing 1M+ tokens through Qwen 3.8 27B, here is my optimal llama.cpp config for 16GB VRAM (73k Context, Agentic Coding)
Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance. Like many of you, I was refreshing the page waiting to download Qwen 3.8 27B the second it dro
中文
Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance. Like many of you, I was refreshing the page waiting to download Qwen 3.8 27B the second it dro
中文全文翻译正在补齐,可先查看下方英文原文。
English / 原文
Following up on my previous post about my budget server setup (Intel N100 + RTX 5060 Ti 16GB), a few of you asked for a deeper dive into my actual inference config and real-world agentic performance. Like many of you, I was refreshing the page waiting to download Qwen 3.8 27B the second it dro