$1,874.50 cheaper than the new price!!
Management number | 202063263 | Release Date | 2025/09/19 | List Price | $1,874.50 | Model Number | 202063263 | ||
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The Intel E810CQDA1OCPV3 is an OCP 3.0 Ethernet network adapter that gives a single server access to up to 100 gigabits per second of bandwidth through one QSFP28 port. The design targets modern data centers where every rack unit must handle heavier traffic, larger datasets, and an expanding mix of applications without a performance dip.
Inside the adapter, the Intel Ethernet Controller E810 teams up with a PCIe 4.0 host interface. This pairing moves packets quickly between the network and the server’s CPUs or GPUs, which helps prevent I/O bottlenecks on virtualization hosts, high-performance storage nodes, and AI inference systems. Whether you attach a direct-attach copper cable, active optical cable, or an optical transceiver, the QSFP28 cage supports them all so you can match the link to your cabling strategy.
For workloads that live and die by latency, the card supports RDMA using both iWARP and RoCEv2. These technologies move data directly between memory spaces, trimming CPU cycles and shortening response times for distributed databases, real-time analytics, and GPU clusters that train machine-learning models.
Traffic is further optimized through Dynamic Device Personalization, which lets you fine-tune packet handling to match specific protocols, and Application Device Queues that assign dedicated queues to critical workloads. Together, these features keep jitter low and throughput predictable, even when the server juggles many tenant or container networks.
Installation is straightforward thanks to the OCP 3.0 form factor, which slides into compatible sleds without tools. Once in place, the adapter supports standards like iSCSI and NFS, allowing you to build fast storage fabrics over Ethernet without extra hardware. From cloud service providers scaling multi-tenant environments to enterprises refreshing on-prem clusters, this card delivers the speed, flexibility, and efficiency demanded by today’s compute-intensive tasks.
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