Smart IOPS and H3 Platform have announced an AI compute storage platform targeting up to one billion random-read IOPS. The proposed system combines Smart IOPS’ Unobtanium T50 solid-state devices with an air-cooled H3 Platform appliance designed around NVIDIA accelerated computing and networking technologies.
The platform targets data-intensive AI inference and analytics workloads that require GPUs to access large datasets through highly parallel, fine-grained I/O. It is designed to support NVIDIA’s Storage-Next initiative and SCADA, or Scaled Accelerated Data Access, programming model. These technologies enable GPU-initiated access to NVMe storage when application working sets exceed local GPU memory.
By reducing the distance between GPU compute and storage, the architecture is intended to reduce CPU control-path overhead and help keep accelerators supplied with data. The approach is aimed at workloads such as graph neural networks, vector search, recommendation systems, retrieval-augmented generation, embedding stores, and other sparse analytics applications that generate large volumes of small, random requests.
“AI infrastructure is entering a phase in which storage must behave less like a passive repository and more like an active extension of the compute fabric,” said Ashutosh Das, CEO of Smart IOPS.
Smart IOPS Unobtanium T50
The Unobtanium T50 is a PCIe Gen6 x4, NVMe 2.0 device in an E3.S form factor. Smart IOPS specifies up to 50 million random-read IOPS and 10 million random-write IOPS at a 512-byte block size. Sequential performance is rated at up to 28 GB/s for reads and 24 GB/s for writes. Sequential throughput in that range matches PCIe Gen6 enterprise SSDs already entering mass production; the 512-byte random-read figure is the specification that stands apart.
Four T50 devices can provide a stated aggregate target of up to 200 million random-read IOPS at the device level. Smart IOPS positions that capability as a match for the I/O requirements of next-generation PCIe Gen6 x16 GPUs, including NVIDIA Rubin. Actual performance will depend on workload characteristics, software, PCIe topology, system configuration, and other system-level factors.
| Smart IOPS ACS Unobtanium T50 | |
| Preliminary Specification | |
|---|---|
| Performance | |
| Random read | Up to 50 million IOPS |
| Random write | Up to 10 million IOPS |
| Block size | 512 bytes |
| Sequential read | Up to 28 GB/s |
| Sequential write | Up to 24 GB/s |
| Hardware | |
| Capacity | 9 TB, 18 TB and 36 TB |
| Media | TLC NAND operated in pseudo-SLC mode; support for specialized low-latency SLC NANDs |
| Form factor | E3.S 2T |
| Interface | PCIe Gen6 x4; NVMe 2.0 |
| Availability | |
| Planned availability | Evaluation samples: Q1 2027; production: Q2 2027 |
| H3 Platform High IOPS Appliance | |
| Preliminary Specification | |
|---|---|
| Compute & Networking | |
| GPU | 4 × NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs |
| Networking | 4 × NVIDIA ConnectX-8 |
| Storage | |
| SSD bays | 20 × E3.S 2T slots for high-IOPS SSDs |
| Per-slot power | Up to 60 W per E3.S slot |
| System | |
| Cooling | Air-cooled |
| Availability | |
| Planned availability | Evaluation systems: Q1 2027; production: Q2 2027 |
| Preliminary specifications; subject to change without notice. |
The T50 uses the Smart IOPS TruRandom controller architecture with widely available TLC NAND operated in pseudo-SLC mode. The company says this approach allows the devices to use multiple qualified NAND suppliers while retaining access to the manufacturing scale and supply-chain capacity of the broader flash industry. The controller can also support specialized low-latency NAND where the workload or deployment economics justify it.
H3 Platform Appliance
H3 Platform is developing an air-cooled appliance with four NVIDIA RTX PRO 6000 Blackwell Server Edition GPUs, four NVIDIA ConnectX-8 network adapters, and 20 E3.S 2T storage slots. Each slot is designed to support up to 60 watts, providing the power and thermal capacity required by high-performance storage devices.
With 20 slots populated by T50 devices, the system is designed to reach a target of up to one billion random-read IOPS. The configuration is intended to balance GPU compute, networking, and storage connectivity in a single platform for evaluating and deploying GPU-initiated, small-block storage workloads.
“The next wave of AI systems must be designed as an integrated data path,” said Brian Pan, founder and CEO of H3 Platform, “not as disconnected compute, network and storage components.” The design places high-IOPS E3.S storage alongside GPUs and high-speed network adapters while retaining an air-cooled form factor.
High IOPS is relevant to these workloads because bandwidth alone does not describe how effectively a storage system handles irregular, concurrent accesses. Small-block requests generated by many GPU threads can expose queuing and synchronization overhead in CPU-orchestrated storage architectures. A higher-IOPS, lower-latency device can service more concurrent requests and potentially reduce the time GPUs spend waiting for data.
Smart IOPS and H3 Platform expect evaluation samples and systems to become available in the first quarter of 2027. Production availability is planned for the second quarter of 2027. The specifications, configurations, and schedules remain preliminary and may change. Customer qualification, software ecosystem readiness, and any NVIDIA validation or approval are separate processes and are not implied by the announcement.