Massive Performance Leap Over Previous Generation

• 3X training performance vs DGX H100
• 15X inference performance vs DGX H100 (per GPU comparison)
• 72 petaFLOPS training / 144 petaFLOPS inference per system
  Particularly dominant for real-time LLM inference: 58 output tokens/sec/GPU vs 3.5 for H100
• Particularly dominant for real-time LLM inference: 58 output tokens/sec/GPU vs 3.5 for H100

Unprecedented Memory Capacity and Bandwidth

• 1.4TB total GPU memory across 8 GPUs (180GB per GPU)
• 64TB/s memory bandwidth
• This massive memory footprint enables handling the largest enterprise AI workloads, including trillion-parameter models and multi-modal applications that would struggle on previous generations

Unified Platform for Complete AI Lifecycle

Single system handles training, fine-tuning, AND inference without needing separate infrastructure. This consolidation reduces:

• Data movement between systems
• Infrastructure complexity and cost
• Time-to-production for AI models
• Operational overhead