About 200 t/s prompt processing and 10-20 t/s with MTP.
Greatly depends on the task, predictable things like code generates at 18-20 t/s. Creative writing more like 10-17 t/s.
About 200 t/s prompt processing and 10-20 t/s with MTP.
Greatly depends on the task, predictable things like code generates at 18-20 t/s. Creative writing more like 10-17 t/s.
Yes, I got a Strix Halo machine before the RAM price hike and use it to run all my ML stuff on it.
Currently using llama-swap with llama.cpp/ComfyUI and opencode/Open WebUI as frontend.
I’m running Qwen3.6-27b, Voxtral Mini 4b, Piper and Qwen Image. Also, some embedding and reranking models.
I use them for:
If you have trouble with outgoing mails, you can use a hybrid approach.
Receive mails directly to your server but use a mail service to relay your outgoing mails. Configuration for that is very simple in mailcow and there are a few dozen (free) transactional email providers (e.g. Scaleway).
That way you can keep receiving your mails privately and only have to give up some privacy when sending mails.
Q8 from unsloth.
My go to model for knowledge. Definitely much faster at Q5 but it lacks the tool calling quality of the Qwen3.6 models. Really hoping we see a Qwen3.6-122b soon…