I think I only had pliers at hand, so gnawed off.

I still have an AMD 7970 laying around with a cutoff shroud for this reason.

I was young and wanted to play…

The times we live in…

Got my mail:

You’re officially in the reservation queue for Steam Machine 512GB with Controller

When your Steam Machine 512GB with Controller becomes available, we will send you a separate email with the option to purchase. You’ll then have 3 days to complete the purchase before we cancel your reservation and move on to the next person in the queue.

This is the only email you will receive about the results of the randomization. If you ended up with a reservation queue spot for more than one model, you were allocated a reservation for the highest end model, and were removed from all the others.

How old are your kids? Prusa Core One kits are very fun and educational to build and you save some money by getting the kit over the pre-built.

They are also built in the EU, very reliable and servicable. More expensive than the Chinese counterparts but they make up for it with good support, parts availability and open source software. Their hardware is mostly open but not entirely anymore sadly.

Curious about the quant tho.

Q8 from unsloth.

Something like Qwen3.5-122b

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…

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.