The Most Powerful AI Chip Yet
NVIDIA has begun shipping Blackwell B300 GPUs, the most powerful AI accelerators ever created. With 208 billion transistors and revolutionary memory architecture, B300 is reshaping what's possible in AI training and inference.
Technical Specifications
B300 Architecture
| Specification | B300 | H100 (Previous) |
|---|---|---|
| Transistors | 208 billion | 80 billion |
| Process | TSMC 4NP | TSMC 4N |
| FP8 Performance | 20 PFLOPS | 4 PFLOPS |
| HBM3e Memory | 192 GB | 80 GB |
| Memory Bandwidth | 8 TB/s | 3.35 TB/s |
| TDP | 1200W | 700W |
Key Innovations
- Second-Gen Transformer Engine: Native FP4 support
- NVLink 5: 1.8 TB/s GPU-to-GPU bandwidth
- Decompression Engine: Real-time data decompression
- Confidential Computing: Hardware-based security
Performance Benchmarks
Training Performance
Model: GPT-4 class (1.8T parameters)
Time to Train:
- H100 x 8192 GPUs: 90 days
- B300 x 4096 GPUs: 45 days
Cost Reduction: 55%
Energy Reduction: 40%
Inference Performance
| Model | H100 | B300 | Improvement |
|---|---|---|---|
| GPT-4 | 150 tok/s | 1,500 tok/s | 10x |
| Llama 70B | 800 tok/s | 8,000 tok/s | 10x |
| Mixtral 8x22B | 400 tok/s | 6,000 tok/s | 15x |
System Configurations
DGX B300
| Configuration | Specs |
|---|---|
| GPUs | 8x B300 |
| Total Memory | 1.5 TB HBM3e |
| NVLink Bandwidth | 14.4 TB/s |
| Network | 400Gb InfiniBand |
| Power | 14.3 kW |
| Price | ~$500,000 |
GB300 NVL72
The new "AI Factory" configuration:
- 72 Blackwell GPUs
- 864 GB per GPU pair
- 130 TB/s aggregate bandwidth
- For frontier model training
Market Impact
Cloud Availability
| Provider | Availability | Pricing |
|---|---|---|
| AWS | Q1 2026 | ~$90/hour |
| Azure | Q1 2026 | ~$85/hour |
| GCP | Q2 2026 | TBD |
| Oracle | Available | $65/hour |
| CoreWeave | Available | $55/hour |
Supply Situation
NVIDIA reports:
- Q1 2026 production: Sold out
- Q2 2026 production: 80% allocated
- 2026 revenue forecast: $150B+
Competition Response
AMD MI400 (Coming)
- Target: Late 2025
- Expected performance: 80% of B300
- Price: 60% of B300
- Key advantage: Availability
Intel Falcon Shores
- Delayed to 2026
- Focus on enterprise market
- Software ecosystem challenges
Customer Adoption
Major Deployments
| Customer | Order | Application |
|---|---|---|
| Microsoft | 100,000+ | Azure AI |
| Meta | 150,000+ | Llama training |
| 50,000+ | TPU complement | |
| xAI | 100,000+ | Grok training |
| OpenAI | TBD | GPT-5 training |
What This Means for AI
"Blackwell B300 makes previously impossible AI workloads routine. Models that would have taken years to train can now be developed in months."
Impact Areas
- Larger Models: 10T+ parameter models feasible
- Real-Time AI: Sub-100ms latency for complex tasks
- Cost Reduction: Enterprise AI more accessible
- New Applications: Previously compute-limited uses
The B300 represents not just an incremental improvement but a generational leap in AI computing capability.
