NVIDIA Blackwell represents a generational leap in AI computing, delivering unprecedented performance for training and inference workloads.

Architecture Innovations

Key Specifications

• 208 billion transistors (2.5x Hopper H100)
• Dual-die design connected by 10TB/s chip-to-chip interconnect
• 20 petaFLOPS FP4 AI performance per GPU
• 192GB HBM3e memory at 8TB/s bandwidth
• Fifth-generation NVLink at 1.8TB/s per GPU

Compute Capabilities

• FP4 Precision: 20 petaFLOPS for inference
• FP8 Training: 10 petaFLOPS for model training
• FP16 Mixed Precision: 5 petaFLOPS for legacy workloads
• INT8 Inference: Ultra-fast quantized model serving

Memory Architecture

• 192GB HBM3e per GPU (up from 80GB in H100)
• 8TB/s memory bandwidth (60% increase)
• Larger context windows for LLMs
• Support for trillion-parameter models

Transformer Engine 2.0

Hardware-Accelerated Transformers

• Dedicated hardware for attention mechanisms
• 4x faster transformer inference vs H100
• Dynamic FP8 quantization during training
• Automatic mixed-precision optimization

Benefits for LLMs

• Train GPT-4 scale models 2x faster
• Serve models with 4x lower latency
• Handle 2x longer context windows
• Reduce memory footprint by 50%

NVLink and Networking

Fifth-Gen NVLink

• 1.8TB/s bidirectional bandwidth per GPU
• Connect up to 576 GPUs in single system
• GPU-to-GPU communication without CPU
• Essential for multi-GPU model parallelism

InfiniBand Integration

• 400Gbps network connectivity
• RDMA for ultra-low latency
• Scale to thousands of GPUs across nodes
• Optimized for distributed training