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Joined 5 months ago
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Cake day: May 11th, 2026

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  • Search lists in qbit are how most people manage.

    I personally use torrentleech which is a private tracker but has basically everything and super permissive rules. Very very easy to maintain ratio and to also get invited and started. I have 4.8TB of upload credit. Searching in qbittorrent or manually across public sites took too long for me when i usually want to find a higher res or higher bitrate version of something. I also always saturate my download speed even with only a few seeds since they’re almost always seedboxes.











  • I’m in the same boat and i rent the place. Both bedrooms are on the same breaker and I’m upgrading my GPU (215W to 415W) and might get a Mi50 as a second card in my desktop for local LLMs.

    At full power on both machines i’m already close to tripping the breaker. Witj these new card(s) i don’t think it’ll fly. My server uses around 700W at max, 450W idle if it’s nice and cool in the spare room. Mostly due to loooots of spinning rust. I’m a datahoarder and have a full 18 disk 3.5" JBOD, and 24/25 drives in my 2.5" JBOD.

    I’ll figure something out I guess…





  • “Yes, i was wrong. You don’t actually need to remove the engine to get the battery out. Let’s put the engine back in and i’ll show you how to remove the battery”

    Although i wouldn’t blame AI for a mistake like this… by now blindly trusting them is asking for trouble…

    For those that do, All quiet on the frontal lobe


  • Qwen3.8-flash-next is making waves since its near frontier or frontier (according to some i havent used it) that can be run on an ancient 8GB video card (12GB or more is recommended. 16GB is best.) with around 32GB of RAM using Strata.

    Strata

    It’s a mixture of experts MoE model, so while it’s around 66GB (depending on which quantization you decide to run) you’re only really using about 6B parameters per token processed, meaning the VRAM requirements are a lot lower.

    I personally don’t see the value proposition in paying $4/1M tokens when i can generate around 30tok/s on 500W of power. I pay ¢13/kWh so to generate 1M output tokens takes me 9.25 hours and costs $0.60.

    I’m also running an ancient video card and have a new one in the mail. If i got 200 tok/s even at higher power use i’m still a fraction of the cost of paying for API access and I want that GPU for other things regardless.

    I feel lile medium and large businesses have a strong incentive to rent or buy inference using open weight models for a fraction the cost of paying OpenAI or Anthropic. Especially if you can pre load them with everything about your org to make them better suited for internal use.

    The vast majority of uses can use a open weight locally run model. I think you would only want to pay for frontier models for really complex tasks with lots of steps, and even then there are usually ways to be smart about how you task agents with work to get better output and use less money.