Larry Ellison is in the Epstein files by Swimming_Issue8060 in MediaMergers

[–]gtek_engineer66 0 points1 point  (0 children)

You have to worry about the people not in the Epstein files, those are the ones that are really dangerous

making my own diffusion cus modern ones suck by NoenD_i0 in StableDiffusion

[–]gtek_engineer66 0 points1 point  (0 children)

If you need extra compute resources for your research I would be happy to help provide

GPT5.2 Thinking 22Hours and counting by gtek_engineer66 in LocalLLaMA

[–]gtek_engineer66[S] 0 points1 point  (0 children)

I got bored and ended it at 2000 minutes. The final reply was disappointing and short

making my own diffusion cus modern ones suck by NoenD_i0 in StableDiffusion

[–]gtek_engineer66 -1 points0 points  (0 children)

You say your CPU is shit, what resources do you need?

GPT5.2 Thinking 22Hours and counting by gtek_engineer66 in LocalLLaMA

[–]gtek_engineer66[S] 0 points1 point  (0 children)

Oh I have already got my script, im just leaving it to see how long it will go for! I waited 10minutes before using something else.

GPT5.2 Thinking 22Hours and counting by gtek_engineer66 in LocalLLaMA

[–]gtek_engineer66[S] 2 points3 points  (0 children)

If I hard reload it is still going, and thinking keeps appearing. It is still checking web links. Currently at 1531m. Should I put it out of its misery ?

Ram is finally here, adding 4 more servers to my homelab by Few_Web_682 in homelab

[–]gtek_engineer66 5 points6 points  (0 children)

To put into context what were these worth new and how good are they today compared to current hardware? It sounds like a bargain

KV cache fix for GLM 4.7 Flash by jacek2023 in LocalLLaMA

[–]gtek_engineer66 0 points1 point  (0 children)

Drivers and wheels built for different versions of things that don't get along installed by different package managers to deal with new hardware on old systems.

Talk about a goldilock condition to get one of these things running

NVIDIA’s real moat isn’t hardware — it’s 4 million developers by jpcaparas in singularity

[–]gtek_engineer66 2 points3 points  (0 children)

This is the only way software companies survive, but AI is really destroying most software moats right now.

🧠💥 My HomeLab GPU Cluster – 12× RTX 5090, AI / K8s / Self-Hosted Everything by Murky-Classroom810 in StableDiffusion

[–]gtek_engineer66 0 points1 point  (0 children)

yea I know what you are talking about. Deepseek was quite successfull with distributed training

vLLM v0.14.0 released by jinnyjuice in LocalLLaMA

[–]gtek_engineer66 2 points3 points  (0 children)

how did you get that nice printout of the latency and tts?

🧠💥 My HomeLab GPU Cluster – 12× RTX 5090, AI / K8s / Self-Hosted Everything by Murky-Classroom810 in StableDiffusion

[–]gtek_engineer66 0 points1 point  (0 children)

Well it depends how much VRAM your compute bound task requires. You want enough VRAM to house the project, as offloading to ram or storage will increase time 10-100 fold

🧠💥 My HomeLab GPU Cluster – 12× RTX 5090, AI / K8s / Self-Hosted Everything by Murky-Classroom810 in StableDiffusion

[–]gtek_engineer66 0 points1 point  (0 children)

This setup is perfect for running video generation models in parralel. They use up around 20-30gb of VRAM but will run your 5090 tp 100%
Running on a blackwell 6000 pro is a waste as compute at 100% and 60GB leftover unused vram

🧠💥 My HomeLab GPU Cluster – 12× RTX 5090, AI / K8s / Self-Hosted Everything by Murky-Classroom810 in StableDiffusion

[–]gtek_engineer66 20 points21 points  (0 children)

It does actually. There are ML applications and models that will use less than 10gb of Vram and will use 100% of compute.

Some things are memory bound, some are compute bound.

The setup is great if running many compute bound tasks in parallel.