I placed a low bid on an auction for 25 Elitedesk 800 G1s on a government auction and unexpectedly won (ultimately paying less than $20 per computer)
In the long run I plan on selling 15 or so of them to friends and family for cheap, and I’ll probably have 4 with Proxmox, 3 for a lab cluster and 1 for the always-on home server and keep a few for spares and random desktops around the house where I could use one.
But while I have all 25 of them what crazy clustering software/configurations should I run? Any fun benchmarks I should know about that I could run for the lolz?
Edit to add:
Specs based on the auction listing and looking computer models:
- 4th gen i5s (probably i5-4560s or similar)
- 8GB of DDR3 RAM
- 256GB SSDs
- Windows 10 Pro (no mention of licenses, so that remains to be seen)
- Looks like 3 PCIe Slots (2 1x and 2 16x physically, presumably half-height)
Possible projects I plan on doing:
- Proxmox cluster
- Baremetal Kubernetes cluster
- Harvester HCI cluster (which has the benefit of also being a Rancher cluster)
- Automated Windows Image creation, deployment and testing
- Pentesting lab
- Multi-site enterprise network setup and maintenance
- Linpack benchmark then compare to previous TOP500 lists
Ah, that’s good to know! I’ll give those other options a shot. Thank you so much for taking the time to help me with that! I’m very new to the whole LLM things, and sorta figuring it out as I go
Completely forgot to tell you to only use quantized models. Your pc can run 4bit quantized versions of the models I mentioned. That’s the key for running llms on at consumer level hardware. You can later read further about the different quantizations and toy with other ones like Q5_K_M and such.
Just read phi-3 got released and apparently it’s a 4B that reach gpt 3.5 level. Follow the news and wait for it to be add to ollama/llama.ccp
I became fascinated with llms after the first AI booms but all this knowledge is basically useless where I live, so might as well make it useful by teaching people what i know.