#nobridge

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Joined 1 year ago
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Cake day: March 14th, 2025

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  • anamethatisnt@sopuli.xyztoPrivacy@lemmy.worldIce Privacy
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    1 hour ago

    Yeah, sorry, I read your “will you give them a chance” as asking for my personal thoughts on the matter. That not everyone has the know-how doesn’t stop me from self-hosting. ;-)
    My advice when it comes to external services - never trust them to keep your data safe. If the data is important to you keep your own backups.
    An example is when TietoEvry, one of the largest IT service providers in the Nordics, lost up to 20 years of archived data for their customers.







  • I usually end up doing it very simple with huge /24 ipv4 networks, f.e.
    10.100.10.0/24 = VLAN 10 = User devices and purely internal servers
    10.100.20.0/24 = VLAN 20 = IoT
    10.100.30.0/24 = VLAN 30 = Servers that are reachable from outside
    10.100.40.0/24 = VLAN 40 = Guests

    The main thing for me is to ensure that traffic that wants to pass between VLANs go through my firewall/router and allow Suricata to do its IPS work.












  • When it comes to Nvidia GPUs the VRAM is the main thing to look for.
    For consumer cards it is:
    Entry level - RTX 5060 Ti 16GB RAM with a price point around 500-550 euro
    Mid - Buying a used RTX 3090 24GB RAM with a price point around 830 euro when I look at swedish second hand markets
    High - RTX 5090 32GB RAM with a price point around 3500 euro

    After that you end up looking at the RTX Pro Blackwell cards:
    Entry - RTX PRO 5000 Blackwell 48GB RAM ~5300 euro
    Mid - RTX PRO 6000 Blackwell 96GB RAM ~10100 euro

    It all depends on which models you want to run, you can definitely start playing around with Llama 3 8B and similar models with a 5060 Ti 16GB.

    If you’re looking at 24B-30B models you need the 24GB VRAM that RTX 3090 offers and get a larger context window if you go for the RTX 5090.

    If you’re looking to run Llama 3 70B then you need to go into the RTX Pro level of vram.

    All of this is based on running it with Nvidia cards, there’s also other setups such as Mac Studios with huge amount of RAM. They’re slower but allow for much larger models at the same price point.
    You could also run with AMD/Intel gpus but much software is built primarily for running CUDA (and Nvidia) gpus so it’s more work and not always compatible.

    I know you said no “monster rack” but I don’t really know what you classify as a monster. :)
    An ordinary gaming pc is also a good starter AI pc, so something like this allows you to do both:
    https://pcpartpicker.com/list/sFp4qd