BIWIN SP5002 / SP509 / SP50Y — PCIe 5.0 Enterprise SSDs for AI Infrastructure

Specifications

Overview

BIWIN's PCIe 5.0 enterprise SSD family is aimed at the storage tier that AI infrastructure has made newly critical. Training and inference clusters do not just need capacity; they need model loading and KV-cache access to happen fast enough that the accelerator is never waiting on storage. Three product lines occupy different points on that trade-off, and a customer can mix them within one deployment.

The SP5002 is the capacity and bandwidth play, offered in E3.S and E1.L form factors up to 61.44 TB with sequential read up to 14.7 GB/s, targeted at AI datasets, data lakes and read-intensive cloud storage. EDSFF form factors matter here because they deliver higher density and better airflow than 2.5-inch carriers, which is how an SSD tier replaces racks of spinning disks — BIWIN claims deployments can require substantially fewer racks than equivalent HDD configurations, with the attendant cuts in cooling and power.

The SP509 and SP519 are the latency-critical pair, and the differentiator is an integrated hardware compression engine. It applies transparent 2:1 compression with zero CPU overhead — the host does not pay for the compression — which directly reduces NAND write amplification and therefore extends endurance at scale. Specifications read as 14,700 / 13,000 MB/s sequential, 3,200K / 1,000K IOPS random at 4K, read and write latency as low as 55 / 7 microseconds and 99.99% QoS held within 15 / 100 microseconds. Capacities run 3.2 TB to 15.36 TB with a choice of 1 DWPD for inference or 3 DWPD for training, so the drive can be matched to whether the workload reads models or writes checkpoints. The SP50Y covers the same ground with Xtacking 4.0 NAND at up to 14.2 GB/s and 1 DWPD, aimed at AI training, cloud computing, core databases and virtualization.

Key Benefits

Three products, one PCIe 5.0 platform — capacity-optimised SP5002, latency-optimised SP509/SP519 and Xtacking 4.0 SP50Y. 61.44 TB in E3.S and E1.L for AI datasets and data lakes at 14.7 GB/s. Transparent 2:1 hardware compression with zero CPU overhead reducing NAND write amplification and host load. Microsecond-class latency at 55 / 7 microseconds read / write with 99.99% QoS within 15 / 100 microseconds. Endurance selectable by workload — 1 DWPD for inference, 3 DWPD for training. KV-cache and model-loading optimisation to keep accelerators fed. Density that displaces HDD tiers with fewer racks, less cooling and lower power.

Applications

AI training clusters with checkpoint-heavy write patterns. Inference fleets and KV-cache tiers. Cloud storage and data lakes needing high-throughput read tiers. Core databases and virtualisation hosts. Content delivery and streaming origin storage. Any deployment replacing HDD capacity tiers where rack density, cooling and power are the binding constraints.

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