Key Takeaways
- Nvidia’s Blackwell Ultra B300 GPU delivers 2.5x inference throughput vs the B200.
- HBM4 memory bandwidth increases to 9.6 TB/s critical for running frontier-scale language models.
- Microsoft, Google, and Amazon placed estimated $40B in combined orders in the first 30 days.
- NVDA shares are up 4.8% on the launch week, pushing market cap past $4.2 trillion.
Nvidia’s Blackwell Ultra architecture specifically the B300 GPU represents the company’s most significant performance leap since the original Hopper launch. The chip, built on TSMC’s advanced packaging technology, delivers 2.5 times the inference throughput of the B200 while keeping power consumption within manageable data center bounds. For AI infrastructure buyers who have been waiting for the next generation before placing large orders, the launch has triggered a procurement frenzy.
The Technical Leap
| Metric | B200 (Blackwell) | B300 (Blackwell Ultra) | Improvement |
|---|---|---|---|
| FP8 Inference (PFLOPS) | 9.0 | 22.5 | +2.5x |
| HBM Bandwidth (TB/s) | 8.0 | 9.6 | +20% |
| HBM Capacity (GB) | 192 | 288 | +50% |
| TDP (Watts) | 1,000 | 1,200 | +20% |
| NVLink Bandwidth (TB/s) | 1.8 | 2.4 | +33% |
The Canadian Connection
For Canadian investors, Nvidia’s dominance is relevant in multiple ways. Shopify’s AI infrastructure runs substantially on Nvidia GPUs; the company’s AI commerce features depend on fast inference that the Blackwell Ultra enables. Coveo, a Quebec-based AI search company (CVE.TSX), recently announced it is migrating its inference infrastructure to Nvidia’s NIM (Nvidia Inference Microservices) platform. And several Canadian pension funds CPPIB, OTPP, OMERS hold Nvidia as a top-five technology holding.