:) Soy Futbolista Estuve Jugando Por La Seleccion De Mi Ciudad tambien Juge En Union Temuco Pero Espero Algun Dia Llegar A La Gloriosa Universidad De Chile
NVIDIA just turned an 8-GPU workstation into something that used to require a datacenter.
For years, running frontier open models meant renting DGX clusters by the hour.
Not anymore.
8× RTX PRO 6000 Blackwell GPUs.
768GB of GDDR7.
Dual AMD EPYC CPUs.
1TB ECC RAM.
InfiniBand networking.
One machine.
One owner.
No cloud.
The crazy part isn't the hardware.
It's what it replaces.
Instead of paying cloud providers every month for inference, fine-tuning, research, or agent workloads...
the compute sits in your office.
Running 24/7.
Waiting for nobody.
Llama 405B.
DeepSeek R1.
Massive coding agents.
Long-context research.
Multi-agent pipelines.
Everything stays local.
No API limits.
No queue.
No per-token bill growing in the background.
Five years ago, this kind of setup belonged inside enterprise AI labs.
Today it's becoming something well-funded startups, research teams and private companies can actually own.
That's the shift most people still underestimate.
The future isn't just better AI models.
It's owning the hardware that runs them.
Cloud won't disappear.
But every new generation of local AI hardware makes renting compute a little harder to justify.
The question is changing from:
"Which API should I use?"
to
"How much of my AI stack should I own?"