NVIDIA GTC 2026 Preview: Blackwell Ultra B300 vs. The First Look at Rubin

SAN JOSE, MARCH 3, 2026 — The "Leather Jacket" season is officially here. In exactly 13 days, Jensen Huang will take the stage at the SAP Center for the GTC 2026 Keynote. Today, Artifgo is breaking down the finalized specs for the hardware that will power the next year of global intelligence: the Blackwell Ultra B300 and the mysterious Rubin successor.

Naming Update: What was previously the "B200 Ultra" has been officially rebranded as the B300 series, signaling a massive architectural leap rather than a simple refresh.

1. Blackwell Ultra (B300): The Reasoning Beast

The B300 is designed for "Agentic AI"—systems that don't just predict text but reason through complex multi-step problems. With a staggering 288GB of HBM3e memory, a single B300 can now host 300B+ parameter models that previously required multiple GPUs.

• 15 PetaFLOPS: Dense FP4 compute performance, representing a 50% jump over the standard B200.
• Liquid Cooling by Default: To handle the 1,400W TDP, the high-end GB300 NVL72 racks are moving exclusively to Direct Liquid Cooling (DLC).
• 800G Networking: Integrated ConnectX-8 NICs provide the massive bandwidth needed for "AI Factories" to stay in sync.

Feature	Blackwell (B200)	Blackwell Ultra (B300)
Memory Capacity	192GB HBM3e	288GB HBM3e
Memory Bandwidth	8 TB/s	8 TB/s (12-Hi Stacks)
Compute (FP4)	9 PetaFLOPS	15 PetaFLOPS
Power Consumption	1,000 Watts	1,400 Watts

2. The "Rubin" Tease: 2027 and Beyond

While the B300 is the star for 2026, the GTC rumor mill is spinning over Rubin. Jensen Huang recently teased that all six Rubin chip designs are back from TSMC's fabs. Expected to utilize the 1.6nm process, Rubin aims to provide 5x the power of Blackwell for training workloads. We expect a "one more thing" glimpse of the Vera Rubin Superchip at the end of the keynote.

The B300 Ultra: A single rack-scale system now delivers over 1 Exaflop of AI power.

Why This Matters for You

Even if you aren't building a data center, the B300's efficiency determines how fast your favorite AI apps respond. By cutting the "cost per token" by 10x compared to last year's Hopper chips, NVIDIA is making free, real-time AI viable for billions more users.

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Reporting by Artifgo Hardware Desk. Data sourced from NVIDIA Newsroom and TSMC supply chain leaks.