Vera Rubin vs GB300: how much faster it is, and what it asks of your data centreWe compare the Vera Rubin NVL72 with the GB300 NVL72, the latest Blackwell, rack against rack, using the figures on NVIDIA's own datasheets.
The Vera Rubin NVL72 is the rack that replaces the GB300 NVL72, and from the outside you would struggle to tell them apart: the same cabinet, 72 GPUs and 36 CPUs. Inside, Rubin delivers around 2.5 times the FP4 compute (2.3 for training) and memory almost two and a half times faster, with the same 288 GB per GPU.
The data centre pays for that leap: power goes from around 135 kW per rack to as much as 227 kW, and there is no air cooling left, everything is liquid. And be wary of the "ten times more" figures doing the rounds, because almost all of them compare it with the GB200, not the GB300.
Two racks that look like twins
Both are what NVIDIA calls a rack-scale system: a 48U cabinet in which 18 compute trays and 9 switch trays behave as one enormous computer. Each tray holds two CPUs and four GPUs, so the rack adds up to 36 CPUs and 72 GPUs, all joined by NVLink (NVIDIA's own network for connecting GPUs to each other), so the software sees them as a single block of memory and compute.
The parts inside are different. The GB300 uses Grace CPUs, with 72 Arm cores, and Blackwell Ultra GPUs; the Vera Rubin uses Vera CPUs, with 88 cores designed by NVIDIA itself, and Rubin GPUs. On the outside they are almost identical, with the same MGX cabinet, the same number of trays and the coolant coming in at the same temperature, 45 °C, hence the temptation to think you only need to swap the trays. As we will see, you don't.
If the names have confused you, that is not your fault. Throughout 2025 NVIDIA called this system the Vera Rubin NVL144, because each Rubin GPU carries two dies and it seemed a good idea to count dies rather than GPUs; it then went back to counting GPUs and renamed it NVL72. To round it off, in 2026 news "NVL144" usually refers to a different product altogether, the Kyber rack with Rubin Ultra, which NVIDIA places in 2027.
The figures, rack against rack
All of them are per full rack and come from the current datasheets for the GB300 NVL72 and the Vera Rubin NVL72. FP4 is the four-bit number format used today to serve large models, and a petaflop is a thousand million million operations per second.
The row that matters most is memory, even if it looks the dullest. Rubin brings no more memory per GPU, since both carry 288 GB, but what it brings is a great deal faster: the jump from HBM3e to HBM4 takes the rack's bandwidth from 576 to 1,400 TB/s. That matters more than it seems, because when a model generates text the GPU spends much of its time sitting idle, waiting for data to arrive from memory.
The announcements, mind you, are worth reading closely. In January NVIDIA gave NVLink and memory figures higher than those on its October datasheet, which are the ones we use here. The promises of "a tenth of the cost per million tokens" or "ten times more tokens per megawatt" are measured against the GB200 NVL72, the grandparent of the family, not against the GB300. And since each generation's inference figure is measured under different conditions, the cleanest comparison is training, which goes from 1,080 to 2,520 petaflops.
What changes in the data centre
This is where the resemblance ends. The GB300 NVL72 draws around 135 kW per rack, with peaks of 155 kW, while NVIDIA publishes three power profiles for Rubin, ranging from 156 kW in the most restrained to 227 kW in the one built for maximum performance. To put that in perspective, 227 kW is about seventy-five 3 kW kettles boiling at once, all in a single cabinet. The trays that distribute the power change too, from 33 kW units to four of 110 kW, so the sums on how many racks fit in your room have to be redone.
Cooling is a similar story. The GB300 removes around 90% of its heat with liquid and the rest with air, but in Rubin everything goes through liquid, even the bars that carry the power, and the trays do not even have fans. That is why the first thing to check is the CDU (the unit that distributes coolant between racks) and the flow rate, figures we have not yet found published for Rubin.
Who each one suits
Manufacturers began shipping it in October 2026 and aim it at cloud and AI infrastructure providers, who are the ones able to keep 72 GPUs busy day and night and to have rooms ready for more than 150 kW per cabinet. The GB300 NVL72 is still on sale, and it is the logical choice if your room is already designed for it or if you need capacity now.
For a company that wants to run its own models in-house, neither is usually the place to start: if the idea is for the legal department to summarise contracts with its own model, a 72-GPU rack is like buying an Airbus to pop out for a loaf of bread. An eight-GPU server with B300 and air cooling, which almost every brand now builds, serves large models without any liquid cooling, although it needs far more power per cabinet than an ordinary server. If the workload grows, you add more. The full rack makes sense when a single model needs more memory than fits in eight GPUs, or when you sell compute capacity to third parties.
Frequently asked questions
What is the Vera Rubin NVL72 for?
For training and serving very large AI models at data centre scale: its 72 GPUs work as a single block of memory and compute. It is bought mainly by cloud and AI infrastructure providers. For a company running its own models, an eight-GPU server is usually enough.
Are the Vera Rubin NVL144 and the Vera Rubin NVL72 the same thing?
Yes. NVIDIA called it NVL144 because it counted the two dies in each Rubin GPU, and later renamed it NVL72 to count GPUs, just as with the GB300. It is 72 Rubin GPUs and 36 Vera CPUs in one rack.
Can I swap a GB300 NVL72 for a Vera Rubin in the same space?
The cabinet has the same format and the same 45 °C coolant inlet, but Rubin draws more power per rack, is cooled entirely by liquid and uses different power trays. Before planning it you need to check your contracted power, the CDU and the coolant flow rate.
Is Rubin ten times cheaper per token than the GB300?
No. That NVIDIA figure compares Rubin with the GB200 NVL72, the generation before the GB300. Against the GB300 the improvement is smaller, and the real one depends on the model and on how many users you serve at once.
How much does a Vera Rubin NVL72 rack cost?
Neither NVIDIA nor the manufacturers that build it publish a price. It is sold per project, together with the network, storage, installation and services, and the price comes from all of that.
How much GPU do you really need?
Tell us which models you want to serve, for how many users and what data centre you have, and we will tell you whether an eight-GPU server is enough or you need a whole rack.
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