NVIDIA Vera Rubin Explained: The Chip After Blackwell

At GTC 2026, during the keynote on March 16, 2026, NVIDIA pulled the cover off its next generation of AI hardware: the Vera Rubin architecture. It is the successor to Blackwell — the family that powers much of the AI compute in use today — and the numbers it claims are the kind that make any engineering team read twice. But before you start dreaming of buying one, it is worth understanding what actually changes in practice, and why, for most companies in Brazil, the smart path is still to rent that power by the hour rather than own it.

⚡ TL;DR

Vera Rubin is the GPU architecture that succeeds Blackwell. The flagship GPU, the Rubin R100, has roughly 336 billion transistors and ships paired with the new 88-core Vera CPU. NVIDIA promises ~5x the inference of Blackwell and roughly 10x lower cost per token. For Brazil, the takeaway is simple: you don't need to import fortune-priced hardware — just rent GPU by the hour in reais and tap into frontier compute.

What Vera Rubin is, in plain terms

The name honors astronomer Vera Rubin and describes a complete package, not just a graphics card. It combines two new components:

Rubin R100 GPU: the flagship, with roughly 336 billion transistors. This is the part that does the heavy lifting of training and inference.
Vera CPU (88 cores): NVIDIA's new processor, which replaces Grace. The CPU + GPU pairing is what gives the architecture its name.

Combined, NVIDIA claims the platform delivers about 10x performance-per-watt versus the previous Grace Blackwell pairing — a jump that matters for the power bill as much as for data-center density.

The numbers NVIDIA announced

Metric	NVIDIA's claim
Inference	~5x Blackwell's performance
Cost per token	~10x lower
Performance per watt	~10x vs. Grace Blackwell
Transistors (Rubin R100)	~336 billion
Vera CPU	88 cores (replaces Grace)

The top configuration is the VR200 NVL72 rack: 72 Rubin GPUs combined with the Vera CPU and 6th-gen HBM4 memory. It's the kind of beast built for the world's largest cloud providers — not for a server under your desk.

What comes next: Rubin Ultra (2027)

NVIDIA has already teased the next step. Rubin Ultra, slated for 2027, should bring around 500 billion transistors, 384GB of HBM4E, memory bandwidth in the order of 32 TB/s, and a new design called "Kyber." NVIDIA CEO Jensen Huang cited roughly $1 trillion in Blackwell + Vera Rubin orders through 2027 — a clear signal that demand for AI compute won't cool off any time soon.

When does it reach the cloud?

Full production of Vera Rubin began in the first quarter of 2026. The first cloud deployments — AWS, Google Cloud, Azure, and Oracle — are expected in the second half of 2026. In other words: within months, this hardware stops being a keynote headline and becomes something you can rent.

Why buying makes little sense for most companies in Brazil

Here is the point that matters most if you are reading from Brazil. A frontier GPU like Rubin isn't just expensive — locally it comes with extra layers of friction:

Import tax and FX: the list price is already high, and importing inflates the capex in reais even further.
Fast obsolescence: buy Rubin today and, in 2027, Rubin Ultra leaves it behind.
Physical infrastructure: the cooling, power, and rack class these cards require don't fit just any room.
Idle time: a GPU only pays off while it's processing; sitting idle, it's frozen capital.

Renting solves all of this at once. You access powerful GPUs over the cloud, pay by the hour in reais, settle via Pix, and spin up a model with 1-click templates. When you're done, you shut it down and stop paying. Frontier hardware becomes a variable cost line, not a risky investment.

💡 Capex vs. compute by the hour

Buying a frontier GPU is a bet that you'll use it 24/7 for years. Renting by the hour means paying for exactly what you consume — and riding each new hardware generation without having to resell the old card. For the vast majority of teams in Brazil, the cloud math wins.

How this changes your AI strategy

The message of Vera Rubin to the market is that the cost of running AI is heading down — up to 10x lower cost per token means tasks that are expensive today (agents, long reasoning, video) become viable. And as this hardware lands in the cloud, those who rent reap the benefit without paying for the transition.

In practice, the winning strategy for companies in Brazil is to:

Run leading open-source models (DeepSeek, Qwen 3, Llama 4) on GPU rented by the hour.
Keep data and latency in Brazil — good for user experience and for the LGPD.
Track new GPU generations as they arrive and simply migrate the instance, buying nothing.

Access frontier compute without buying hardware

Spin up a GPU in minutes. Pay by the hour in reais, via Pix.

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Frequently asked questions

What is the NVIDIA Vera Rubin architecture?

Vera Rubin is the GPU architecture that succeeds Blackwell, announced at NVIDIA GTC 2026. It pairs the Rubin R100 GPU, with roughly 336 billion transistors, with the new 88-core Vera CPU that replaces Grace. NVIDIA claims about 5x the inference performance of Blackwell and roughly 10x lower cost per token.

When does Vera Rubin reach the cloud?

Full production began in the first quarter of 2026, and the first cloud deployments (AWS, Google Cloud, Azure, and Oracle) are expected in the second half of 2026. The Rubin Ultra version, with around 500 billion transistors and 384GB of HBM4E, is slated for 2027.

Do I need to buy a Vera Rubin GPU to run frontier AI in Brazil?

No. Renting GPU by the hour in reais removes the capex and import tax of buying hardware. You access powerful GPUs over the cloud, pay via Pix for what you use, and run frontier models without tying up cash in a card that costs a fortune.

Conclusion

Vera Rubin is a milestone: more inference, lower cost per token, and a roadmap already pointing to Rubin Ultra in 2027. But the lesson for Brazil isn't "go buy a new GPU" — it's the opposite. The faster hardware evolves, the riskier it is to buy and the smarter it is to rent. On GPUBrazil you access powerful GPUs by the hour, in reais, with local latency and data sovereignty — and you move to the next generation when it arrives, with no headaches.