Nvidia trims Vera Rubin memory and NVLink bandwidth specs without announcement
Nvidia's product pages now list lower HBM4 and NVLink 6 bandwidth for Vera Rubin, and the edit sat unnoticed for roughly six weeks.
Edited by Dot Matrix, Editor-in-Chief

Here is what physically changed: nothing visible, only the spec sheet. Each Rubin GPU is now rated at 19.2 TB/s of HBM4 memory bandwidth, down from 22 TB/s, and 3 TB/s of NVLink 6, the chip-to-chip link, down from 3.6 TB/s. That is roughly 13% and 17% less. Capacity holds at 288 GB, and the 50 PFLOPS sparse NVFP4 inference figure is unchanged. 1
At rack scale, the Vera Rubin NVL72 drops from 1,580 TB/s to 1,400 TB/s of aggregate memory bandwidth and from 260 TB/s to 216 TB/s of NVLink. The eight-GPU HGX Rubin NVL8 board takes the worst hit: 2 TB of HBM4 at 130 TB/s, versus 2.3 TB at 176 TB/s before, a 26% bandwidth cut. 1
The edit landed between September 1 and September 11, and no announcement followed. 1 Some pages still show the old numbers, so the math no longer adds up across Nvidia’s own documents. 1
The likely reason is memory. The HBM4 standard tops out at 8 Gb/s per pin, or 2 TB/s per stack, while Nvidia had been pushing suppliers toward 10 Gb/s and beyond. Reports said SK hynix and Samsung struggled to hit the 22 TB/s target. 1 Nvidia has not said whether it used smaller stacks or disabled one. 1
The competitive picture shifts on paper. AMD’s Instinct MI455X lists 23.3 TB/s using 12 stacks at standard speeds, so it never needed exotic memory. Against the revised numbers, AMD’s Helios rack leads by about 19% on memory bandwidth and about a fifth on scale-up bandwidth. None of these figures are benchmarked. 1
Rubin is still quick: 19.2 TB/s is about 2.4 times Blackwell’s 8 TB/s, short of the 2.8x Nvidia’s blog still claims. 1
Our read: This looks like a company choosing shipping hardware over a chase for a memory target that suppliers could not deliver. That is sensible engineering, but quiet edits are a poor way to tell customers, and the “10x tokens per megawatt” marketing now rests on figures Nvidia has not said it rerun. 1
On the bench: if you are budgeting inference racks, ask for measured memory-bound throughput, not the old spec sheet, because bandwidth is the line that decides decode speed.
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