NVIDIA DGX Spark 200G QSFP56 to QSFP56 Passive DAC Cable, 0.5m, 30AWG, 200GbE, Low Power & Mellanox MCP1650 Compatible

High-Speed 200GbE Direct Attach Connectivity

Connect compatible networking equipment with the NVIDIA DGX Spark 200G QSFP56 to QSFP56 Passive Direct Attach Copper (DAC) Cable. Designed for high-speed 200GbE connections, this 0.5-metre cable provides a reliable, power-efficient interconnect solution for NVIDIA DGX Spark dual-system configurations and other compatible QSFP56 devices.

200G QSFP56 to QSFP56 Connection

Supporting data rates of up to 200Gbps, this passive DAC cable connects equipment equipped with QSFP56 ports. It is designed for short-distance, high-bandwidth connections in professional networking environments, data centres and AI workstation setups.

Low Power Consumption

With maximum power consumption of less than 0.1W, the passive copper design provides an energy-efficient alternative to active optical connectivity for suitable short-distance applications. It also helps reduce electromagnetic interference and power requirements.

Reliable 30AWG Copper Construction

Featuring 30AWG copper cabling and a compact 0.5m length, this cable is suitable for direct connections between closely positioned systems. Its black LSZH construction and pull-tab design support practical installation and cable management.

Broad Compatibility & Industry Standards

Compatible with NVIDIA/Mellanox MCP1650-V00AE30 specifications and designed for use with compatible QSFP56 equipment, including selected Cisco, Arista and Broadcom devices. It complies with QSFP56 MSA, IEEE 802.3bj, IEEE 802.3cd and RoHS environmental standards.

Tested for Professional Networking Applications

Designed for dependable high-speed interconnects, this cable is supplied with professional compatibility and parameter test reports to support installation and equipment verification.

The NVIDIA DGX Spark 200G QSFP56 Passive DAC Cable delivers high-bandwidth 200GbE connectivity, low power consumption and reliable short-range connections for compatible AI and networking systems.