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:

• Tagging and classification of my documents in Paperless
• Home Assistant (voice assistant)
• Translations (both text and image)
• Transcriptions
• Some light coding and debugging
• Avatar/Backdrop generation for DnD sessions

The Index did not have OLED screens, they used regular LCDs.

So excited for Bigscreen. Might just finally replace my Kodi setup.

Thanks! This might come in handy since I have the same issue with the generic “Thinking” in opencode.

It does? Guess I can finally yeet Chromium from my machine then.

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.

According to their now deleted Reddit account, it will use a custom Proton build on Intel and Zen 4 CPUs. For every other CPU you will need a kernel module.

You should be able to just stop Jellyfin, drag the new version into your Application folder and start it again.

How did you install Jellyfin?

I also started a Twilight Princess playthrough in dusklight recently. Even though I only wanted to take a quick look around, I’m already in the Arbiter’s Grounds right now.

I highly recommend dusklight, very well made decompilation: https://github.com/TwilitRealm/dusklight

Plasma Bigscreen is scheduled for its first release next month: https://plasma-bigscreen.org/

Ask again in a different support ticket.

Friend of mine just got told that it’s going to arrive soon and then asked again after he saw everyone got a free game and now he also got the offer.

As a side note, Qwen3.6-27B is much more capable than Qwen3.6-35B, even though it is much slower.

https://huggingface.co/unsloth/Qwen3.6-27B-GGUF

For coding tasks where you don’t mind waiting, you should be able to barely squeeze in the 8-bit quantized version with 32 GB RAM + 8 GB VRAM and have a pretty competent local model. 4-bit quants work but they have issues with complex tool calls.

If you use the MTP branch of llama.cpp (and a suitable model) you can even double or triple your token generation speed: https://github.com/ggml-org/llama.cpp/pull/22673

For easier tasks, disable reasoning for instant responses.

That looks pretty good. Looks like Portainer is getting replaced this weekend.

I share photos and videos through my Matrix/Signal bridge all the time just fine.

Calls don’t work but that’s about it.

Do you actually train the LLM or use RAG? I have been looking for a local LLM + Wikipedia RAG solution for a while now.

For now I just have kiwix-serve + searxng doing a simple search but the Kiwix search is…questionable.

I wrote an application which runs on my server and monitors my favorites on Tidal/Deezer/Qobuz. It downloads them in bulk whenever I have a premium account with one of them. Usually I purchase a month of premium every few months, at which point I get nice clean FLACs for local use.

The FLACs are moved to Jellyfin and I stream them using Finamp, which also supports transcoding, so I keep 128 kbps Opus files for offline playback and stream the raw FLAC files when bandwidth is no concern.

I have amassed a huge music library over the last decades, so even if all streaming websites go under tomorrow, I have enough music locally to last me a lifetime.

Miss it when tech updates were good.

Open source got your back.

Still excited every time I get a new KDE version.

Same, 8 heads is way overkill for my simple 0.4/0.6/0.8mm nozzle swap use case but I wanted to build something. :)