ASUS QSFP QUAD 400G Pluggable GX10 Cable, 0.4m Length, Stacking & AI/Supercomputer, High-Speed Data Center Interconnect | 90MA0000-P01000

The ASUS QSFP QUAD 400G Pluggable GX10 Cable is a high-speed interconnect solution essential for modern high-performance computing (HPC) and artificial intelligence (AI) infrastructures. This cable provides a massive 400G data transfer rate over a short 0.4m distance, making it ideal for rack-based connections. Specifically designed for use as a GX10 Stacking cable, it ensures ultra-low latency and high-bandwidth connectivity between devices like the ASUS GX10 system, AI topologies, and DGX spark environments. Its pluggable nature ensures simple, reliable installation and maintenance.

Ultra-High Bandwidth Interconnect: ASUS QSFP QUAD 400G GX10 Cable

Maximize the performance of your data center, supercomputer, or AI cluster with the ASUS QSFP QUAD 400G cable. Engineered for extreme speed and reliability, this cable is a critical component for next-generation network architecture.

Extreme Performance and Application:

• 400G Data Rate: Supports an astonishing 400 Gigabits per second data transfer rate, vital for handling massive datasets and the intense communication demands of AI and machine learning models.
• QSFP QUAD Technology: Utilizes the Quad Small Form-factor Pluggable (QSFP) standard, a dense, high-performance interface widely adopted in high-speed networking.
• GX10 Stacking: Specifically validated for connecting ASUS Supercomputer systems, acting as a direct GX10 Stacking cable to maintain cohesive cluster performance.
• HPC and AI Use: Perfect for connecting mission-critical hardware such as AI training systems, supercomputers, and high-density GPU nodes (e.g., DGX spark).

Optimized for Data Center Density:

• Short 0.4m Length: The compact length is optimized for intra-rack connections and stacking, minimizing cable clutter and signal loss within dense server environments.
• Pluggable Design: Simplifies installation and removal, reducing downtime and maintenance complexity in large-scale deployments.