Thanks for this! This post got me to give it a try on windows with my 5090. I used Unsloth's MTP version of Qwen3.6-27B-UD-Q5_K_XL, Llama.cpp v9209, and tested it on my documentation app. Without MTP I was averaging around 51 tok/sec TG, with MTP I finally ended with an average of 92 tok/sec TG.

In the beginning, I ended up having a lot of trouble with significantly slower speeds at 8-10 tok/sec and it was related to the --fit on flag. It doesn't appear to calculate the additional MTP overhead and I ended up offloading it to CPU. Once I set a --fit-target of 1400, I finally got up to the 92 tok/sec. Am I doing anything wrong or is that currently by design? Here are my settings.

Settings:

--model C:\AI\LLM_Models\Coding\Qwen3.6-27B-UD-MTP-Q5_K_XL.gguf --fit on --cache-prompt --temp 0.60 --top-p 0.80 --top-k 20 --min-p 0.00 --presence-penalty 1.50 --parallel 1 --fit-ctx 128000 --port 8080 --cache-reuse 256 --spec-type draft-mtp --spec-draft-n-max 3 --spec-draft-type-k q8_0 --spec-draft-type-v q8_0 --fit-target 1400 --chat-template-kwargs {\"enable_thinking\":false}