NVIDIA Rubin SXM vs NVIDIA Rubin CPX
Side-by-side specifications, performance, and rental pricing for datacenter AI workloads.
Rubin: Rubin, 2026 Rubin CPX: Rubin, 2026
VRAM
288 vs 128 GB
160 GB more for the Rubin
NVIDIA Rubin SXM
Full specs →Architecture
Rubin
Year
2026
VRAM
288 GB
NVIDIA Rubin CPX
Full specs →Architecture
Rubin
Year
2026
VRAM
128 GB
Specifications
Rubin Rubin CPX
Architecture
RubinRubin
Launch Year
20262026
Form Factor
SXM—
VRAM
288 GB128 GB
Memory Bandwidth
22.0 TB/s—
TDP
——
Process Node
——
Spec Rubin Rubin CPX
Architecture RubinRubin
Launch Year 20262026
Form Factor SXM—
VRAM 288 GB128 GB
Memory Bandwidth 22.0 TB/s—
TDP ——
Process Node ——
Performance (TFLOPS)
Rubin Rubin CPX
FP64
33.0 TFlops —
FP32
130.0 TFlops —
FP16
4000.0 TFlops
sparse not published
—BF16
4000.0 TFlops
sparse not published
—FP8
17500.0 TFlops
sparse not published
—INT8
250.0 TFlops
sparse not published
—Tensor Core
FP64 (TC)
200.0 TFlops —
Precision Rubin Rubin CPX
FP64 33.0 TFlops —
FP32 130.0 TFlops —
FP16 4000.0 TFlops
sparse not published
—BF16 4000.0 TFlops
sparse not published
—FP8 17500.0 TFlops
sparse not published
—INT8 250.0 TFlops
sparse not published
—Tensor Core
FP64 (TC) 200.0 TFlops —
FLOPS by Precision
What actually differs
Both GPUs launched in 2026: the Rubin on Rubin and the Rubin CPX on Rubin.
Memory is 288 GB against 128 GB. More memory per GPU means larger models fit before you have to shard across cards, which often matters more than raw TFLOPS for inference.
For LLM training and inference, weight the FP8 and FP16 rows and memory capacity most heavily. For scientific and HPC workloads, the FP64 row is the one to read.
Frequently asked questions
Which has more memory, the Rubin or the Rubin CPX?
The Rubin carries 288 GB of VRAM versus 128 GB for the Rubin CPX.
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