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Joined 1 year ago
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Cake day: March 22nd, 2024

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  • 1548 RPM should be slow for a small GPU fan, no? My Nvidia 3090 behaves exactly the same, switching the fan on and off as it hovers around 60C or so.

    Looks like it’s working fine to me.

    Also, take linux GPU monitors with a grain of salt. It’s possible the GPU fan RPM measurement is totally borked, and it basically represents “on” or “off.” Check it with your eyes and ears instead, see if the fan is screaming or not. It shouldn’t be below 76C (as modern GPUs are configured to operate above 80C or so).



  • I mean, you are right, and way more people should be using openSUSE :P

    I will say Arch-derived distros are a good experience if you want to learn how the terminal and other systems work. They’re engineered to be configurable; the documentation is great. But if you just want to use your computer without opening too many hoods, it’s fundamentally not an optimal system.

    Another thing is that many people just want their new laptop to work, and for it to game on linux. Sometimes it does not just work. If you start pulling in fixes and packages that are not supported on your distro, you can screw up any distro very quickly (and this includes the AUR, unofficial Fedora repos and such). If the community packages these, stages them, tests them against all official packages, and they work out-of-the-box… that’s one less hazard.





  • Actually I had this one!

    Something about their swap config makes it very fragile unless you use RAM swap as enabled by default, and I kept having this when I disabled it for reasons. It was much better once I re enabled it, though occasionally I still have severe issues going way, way, over my RAM pool.

    I don’t mention that much because swapping to like 64GB on a 32GB system seems like an uncommon use case.


  • I see people saying CachyOS is finicky, but I’ve had almost no issues in two years of extensive use.

    And anything that pops up gets fixed extremely quickly.

    What’s better, everything you need for gaming is in the repos by default and pre-tweaked, no need to fuss with it like other distros. This is my nitpick with Fedora or Arch AUR: once you go outside the curated, officially supported packages, you are asking for trouble.









  • I mean, if you have huge GPU, sure. Or at least 12GB free vram or a big Mac.

    Local LLMs for coding is kinda a niche because most people don’t have a 3090 or 7900 lying around, and you really need 12GB+ free VRAM for the models to start being “smart” and even worth using over free LLM APIs, much less cheap paid ones.

    But if you do have the hardware and the time to set a server up, the Deepseek R1 models or the FuseAI merges are great for “slow” answers where the model thinks things out for replying. Qwen 2.5 32B coder is great for quick answers on 24GB VRAM. Arcee 14B is great for 12GB VRAM.

    Sometimes running a small model on a “fast” less vram efficient backend is better for stuff like cursor code completion.


  • My friend, the Chinese have been releasing amazing models all last year, it just didn’t make headlines.

    Tencent’s Hunyuan Video is incredible. Alibabas Qwen is still a go to local model. I’ve used InternLM pretty regularly… Heck, Yi 32B was awesome in 2023, as the first decent long context local model.

    …The Janus models are actually kind of meh, unless you’re captioning images, and FLUX/Hunyuan Video is still king in diffusion world.


  • As implied above, the raw format fed to/outputed from Deepseek R1 is:

    <|begin▁of▁sentence|>{system_prompt}<|User|>{prompt}<|Assistant|><think>The model rambles on to itself here, “thinking” before answering</think>The actual answer goes here.

    It’s not a secret architecture, theres no window into its internal state ehre. Thi is just a regular model trained to give internal monologues before the “real” answer.

    The point I’m making is that the monologue is totally dependent on the system prompt, the user prompt, and honestly, a “randomness” factor. Its not actually a good window into the LLM’s internal “thinking,” you’d want to look at specific tests and logit spreads for that.