5m (16ft) NVIDIA/Mellanox MCA7J75-N005 Compatible 800G Twin-port OSFP 8 x 100G PAM4 Finned Top to 4 x 200G QSFP112 2 x 100G PAM4 InfiniBand NDR Active Direct Attach Copper Breakout Cable for Quantum-2 Switches and ConnectX-7 HCA

5m (16ft) NVIDIA/Mellanox MCA7J75-N005 Compatible 800G Twin-port OSFP 8 x 100G PAM4 Finned Top to 4 x 200G QSFP112 2 x 100G PAM4 InfiniBand NDR Active Direct Attach Copper Breakout Cable for Quantum-2 Switches and ConnectX-7 HCA

5m (16ft) / NVIDIA (IB)
Dhs. 4,510.43
Sale price  Dhs. 4,510.43 Regular price  Dhs. 6,314.60
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5m (16ft) NVIDIA/Mellanox MCA7J75-N005 Compatible 800G Twin-port OSFP 8 x 100G PAM4 Finned Top to 4 x 200G QSFP112 2 x 100G PAM4 InfiniBand NDR Active Direct Attach Copper Breakout Cable for Quantum-2 Switches and ConnectX-7 HCA

5m (16ft) NVIDIA/Mellanox MCA7J75-N005 Compatible 800G Twin-port OSFP 8 x 100G PAM4 Finned Top to 4 x 200G QSFP112 2 x 100G PAM4 InfiniBand NDR Active Direct Attach Copper Breakout Cable for Quantum-2 Switches and ConnectX-7 HCA

Dhs. 4,510.43
Sale price  Dhs. 4,510.43 Regular price  Dhs. 6,314.60
Length5m (16ft)
Compatible BrandsNVIDIA (IB)
Description
The NVIDIA/Mellanox InfiniBand MCA7J75-N005 is an 800Gb/s twin-port OSFP finned top to 4x 200Gb/s QSFP112 Active Copper Cable (ACC) quad breakout (aka splitter) cable for InfiniBand NDR networking. The ACC contains eight high-speed electrical copper pairs, each operating at data rates of up to 100Gb/s using 100G-PAM4 modulation. It is compliant with OSFP MSA, QSFP112 MSA (Multi-Source Agreement) and IEEE 802.3ck standards. The OSFP end has a finned top for additional cooling, while the QSFP112 end is without cooling fins on top and uses the cooling fins located on the adapter cages. It is primarily used to link an 800Gb/s Quantum-2 switch to four QSFP112-based 200Gb/s ConnectX-7. ACC cables integrate a Redriver chip that extends reach up to 5 meters while ensuring latency, enhancing port bandwidth, density, and configurability. These power-efficient links are ideal for medium-distance connectivity in data centers, AI/HPC clusters, and cross-rack deployments.

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