NVIDIA Blackwell B200 / B300
The NVIDIA Blackwell architecture delivers a generational leap in AI performance. B200 offers 192GB HBM3e with 20 petaflops FP4, while B300 Ultra extends to 288GB for the most demanding AI reasoning workloads. Built on 208 billion transistors with 5th-gen Tensor Cores, Blackwell achieves 4X faster training and 30X faster inference than Hopper.
Generational Performance Leap
Blackwell delivers breakthrough improvements over Hopper architecture
Blackwell Configurations
Choose the right Blackwell GPU for your workload requirements
Technical Specifications
Complete Blackwell B200 and B300 technical details
| Specification | B200 SXM | B300 Ultra |
|---|---|---|
| Architecture | ||
| GPU Architecture | Blackwell | Blackwell Ultra |
| Process Node | TSMC 4NP | |
| Transistors | 208 billion | |
| Die Size | 814 mm² | 744 mm² |
| Compute | ||
| CUDA Cores | 18,432 | 32,768 |
| Tensor Cores | 576 (5th Gen) | 1024 (5th Gen) |
| RT Cores | 144 (4th Gen) | 256 (4th Gen) |
| Streaming Multiprocessors | 144 | 256 |
| Memory | ||
| Memory Capacity | 192GB HBM3e | 288GB HBM3e |
| Memory Bandwidth | 8TB/s | |
| Memory Bus Width | 8192-bit | |
| L2 Cache | 128MB | 192MB |
| ECC Memory | Yes | |
| Performance | ||
| FP64 | 40 TFLOPS | 45 TFLOPS |
| FP32 | 80 TFLOPS | 125 TFLOPS |
| FP16 Tensor | 5,000 TFLOPS | 2,500 TFLOPS |
| FP4 Tensor | 20,000 TFLOPS | 15,000 TFLOPS |
| INT8 Tensor | 10,000 TOPS | 7,500 TOPS |
| Connectivity | ||
| NVLink | 1.8TB/s bidirectional | |
| Network Bandwidth | 800Gbps | 1.6Tbps |
| PCIe | PCIe 5.0 x16 | PCIe 6.0 x16 |
| Multi-GPU Support | Up to 8 GPUs (NVLink) | |
| Power & Thermal | ||
| TDP | 1000W | 1400W |
| Max Operating Temp | 83°C | |
| Cooling | Liquid Required | Advanced Liquid Required |
| Enterprise Features | ||
| MIG Support | Up to 8 instances | |
| Confidential Computing | Yes | |
| vGPU Support | Yes | |
| Secure Boot | Yes | |
Ideal Use Cases
Blackwell excels at demanding AI workloads requiring maximum performance
LLM Training
Train trillion-parameter models with 4X faster throughput. 192-288GB memory handles massive model states without model parallelism overhead.
Real-Time Inference
30X faster LLM inference enables real-time conversational AI, code generation, and multimodal applications at scale.
AI Reasoning (B300)
B300's 288GB memory and 2X networking enables advanced multi-step reasoning and chain-of-thought processing at scale.
Multimodal AI
Process vision, language, and audio in unified models. HBM3e bandwidth supports complex attention mechanisms.
Scientific AI
Accelerate drug discovery, protein folding, and climate modeling with FP64 performance and massive memory capacity.
AI Data Centers
Deploy enterprise AI infrastructure with MIG partitioning for multi-tenant workloads and maximum GPU utilization.
Architecture Comparison
How Blackwell compares to previous NVIDIA data center GPUs
B200 vs H100
- Memory: 192GB vs 80GB (+140%)
- Bandwidth: 8TB/s vs 3.35TB/s (+139%)
- Training: 4X faster on LLMs
- Inference: 30X faster LLM inference
- Efficiency: 2.5X better perf/watt
- TDP: 1000W vs 700W
B300 vs B200
- Memory: 288GB vs 192GB (+50%)
- L2 Cache: 192MB vs 128MB (+50%)
- Network: 1.6Tbps vs 800Gbps (2X)
- CUDA Cores: 32,768 vs 18,432 (+78%)
- Target: Reasoning vs General AI
- TDP: 1400W vs 1000W
Frequently Asked Questions
What is the difference between NVIDIA B200 and B300?
B300 Blackwell Ultra is the flagship variant with 288GB HBM3e (50% more than B200's 192GB), 192MB L2 cache (vs 128MB), 2X faster networking (1.6Tbps vs 800Gbps), and optimized specifically for AI reasoning workloads. B200 offers excellent general AI training and inference at a lower price point and power envelope.
How does Blackwell compare to H100 (Hopper)?
Blackwell B200 delivers 4X faster AI training, 30X faster LLM inference, 2.4X more memory (192GB vs 80GB), and 2.4X more bandwidth (8TB/s vs 3.35TB/s) compared to H100. It achieves 2.5X better power efficiency despite a higher TDP due to dramatically improved performance.
What is the B200 and B300 price?
NVIDIA B200 GPUs are priced between $30,000-$40,000 depending on configuration and volume. B300 Blackwell Ultra is estimated at $40,000-$50,000. Pricing varies by system configuration and partner. Contact SLYD for current pricing.
What cooling infrastructure does Blackwell require?
B200 has a 1000W TDP and requires liquid cooling. B300 has a 1400W TDP and requires advanced liquid cooling infrastructure. Both require data center facilities with appropriate cooling capacity for these power envelopes.
When is Blackwell available?
B200 systems are available now through NVIDIA's OEM partners including Dell, HPE, Supermicro, Lenovo, and Gigabyte. B300 Blackwell Ultra is expected in H2 2025. SLYD provides enterprise procurement with configuration assistance and deployment support.
Should I choose B200 or B300?
Choose B200 for general AI training and inference workloads where 192GB memory is sufficient. Choose B300 for advanced AI reasoning, trillion-parameter models, and workloads that benefit from the extra memory (288GB) and faster networking (1.6Tbps). B200 is available now; B300 arrives H2 2025.
Deploy NVIDIA Blackwell
Get enterprise B200 and B300 systems through our OEM partnerships with expert configuration and deployment support.