Skip to main content

One post tagged with "ML Infrastructure"

Machine learning infrastructure, GPU clusters, and deployment

View All Tags

NVIDIA Rubin at GTC 2026: Full Technical Breakdown for ML Engineers

· 18 min read
Dhayabaran V
Barrack AI

336 billion transistors. 288 GB of HBM4 per GPU. 22 TB/s memory bandwidth. 50 petaFLOPS of FP4 inference per chip.

Those are the numbers NVIDIA is putting behind Rubin, the successor to Blackwell, announced at CES 2026 and entering production for H2 2026 deployment. GTC 2026 kicks off March 16 in San Jose, where Jensen Huang is expected to go deep on Rubin's architecture, pricing signals, and the software stack updates that make these numbers real.