On-Prem or Cloud?

Let’s be honest: deciding between on-premise GPUs and the cloud isn’t just about tech specs—it’s about survival. For AI startups, every dollar and every week counts. The choice you make here can shape your runway, your pace of innovation, and even your team’s sanity.

The Hidden Tax of Owning Your Own Gear

Buying your own servers feels bold. You see the price tag—maybe $250,000 for a cluster with 8 NVIDIA A100s, racks, and networking gear. It’s a big number, but it’s concrete. You pay it, you own it. Simple, right?Not quite. The real costs sneak in after you swipe the company card. Suddenly, you need two engineers just to keep things running—think setup headaches, security updates, and the occasional “why won’t this boot?” crisis. That’s another $300,000 a year, easy. Power and cooling? Add $40,000, if you’re lucky. And if you don’t have a data center, you’ll be paying $15,000 a month for colocation, or you’ll be turning your office into a server sauna.

And here’s the kicker: AI hardware ages fast. Your shiny new GPUs start feeling old in two years. Upgrading? That’s another six-figure bill. Need to scale up for a big training run? Hope you like waiting—hardware orders and setup can take weeks, while your competition is already training in the cloud.

Why GPU Cloud Changes the Game

Now, picture this: you log into Oblivus Cloud. No upfront costs, no surprise fees. You pay by the hour for the latest NVIDIA H100s or A100s. Power, cooling, and maintenance? All baked into the price. Need 100 GPUs for a week? Click a button. Done. When you’re finished, you scale down and your costs drop to zero.

Cloud isn’t just about convenience. It’s about staying current. When NVIDIA drops a new chip, you get access right away—no more waiting a year for your next hardware refresh. Training a massive language model? On-premise, you’d be looking at $1.2 million upfront and $200,000 a year in upkeep. In the cloud, you might spend $68,000 for a month-long run, then nothing until your next project.

Let’s Crunch the Numbers

Say you need 32 GPUs for three years. On-premise, you’re out $950,000 for hardware and setup. Add $900,000 for IT staff, $180,000 for power and space, and $450,000 for a mid-cycle upgrade. That’s $2.48 million, all in.

With Oblivus Cloud, it’s a different story. No hardware, no IT salaries, no upgrades. Even if you run jobs non-stop, you’re looking at around $500,000. That’s a savings of nearly $2 million—enough to double your engineering team or extend your runway by a year or more.

Why Cloud Wins for Startups

Cloud GPUs aren’t just cheaper. They’re smarter for startups. You can pivot without worrying about sunk costs. You can experiment quickly—spin up proof-of-concepts in hours, not months. And your engineers? They’ll be building models, not fighting server fires at midnight.

What's the Takeaway?

On-premise makes sense if your workload never changes and you have deep pockets. But for most AI startups, the cloud isn’t just a better deal—it’s a lifeline. You get flexibility, speed, and the freedom to focus on what matters: building something great.

Oblivus Cloud is built for this. No lock-in, no waiting. Just enterprise-grade NVIDIA GPUs, ready when you are. Launch your GPU cloud today.

Reserve your hardware

Instant cluster provisioning | Flexible Infrastructure | Simple Billing