Specifications

Part Number

MTFDLAL7T6THA-1BK1DABYYR

Series

Micron 9550 PRO

Capacity

7.68 TB

Form Factor

U.2 (2.5-inch, 15 mm); E3.S 1T 7.5 mm available

Interface

PCIe 5.0 x4, NVMe

NAND

Micron G8 NAND

Sequential Read

Up to 14.0 GB/s

Sequential Write

Up to 10.0 GB/s

Random Read

Up to 3,300K IOPS

Random Write

Up to 400K IOPS

Capacities in family

3.2 TB to 30.72 TB

Security

SPDM 1.2, SHA-512, RSA, Micron SEE

OCP

Compliant with most of OCP Datacenter NVMe SSD spec 2.0r21; partial OCP 2.5 telemetry

Certification

TAA Compliant

Platform

Qualified for NVIDIA GB200 NVL72 recommended vendor list

AI Workload Gain

Up to 60% faster and 43% less energy for GNN training vs comparable drives

Family SKUs

MTFDLAL3T8THA / 7T6THA / 15T3THA / 30T7THA (single pack)

Overview

The Micron 9550 PRO MTFDLAL7T6THA-1BK1DABYYR is a 7.68 TB PCIe Gen5 data center SSD positioned by Micron as the fastest data center SSD in production. It delivers up to 14.0 GB/s sequential read and 10.0 GB/s sequential write, with 3,300K random-read and 400K random-write IOPS.

The AI claim is specific rather than generic: Micron measures up to 60% faster performance and 43% lower energy for Graph Neural Network training against comparable drives. For AI-recommendation and GNN workloads, where access patterns are irregular and pointer-chasing dominates, random-read headroom and latency consistency matter more than streaming bandwidth - which is the axis this drive is tuned on.

The 9550 is built on Micron G8 NAND and is on the recommended vendor list for NVIDIA GB200 NVL72 systems, so it can be specified inside a Blackwell-class rack without a separate qualification exercise. The family spans 3.2 TB to 30.72 TB across U.2 15 mm and E3.S 1T, with SPDM 1.2 attestation, SHA-512/RSA and Micron's Secure Execution Environment.

Key Benefits

14.0 GB/s sequential read — Gen5 line-rate class throughput in a 15 mm U.2 bay. 3.3M random-read IOPS — built for pointer-chasing AI access patterns. GB200 NVL72 qualified — pre-validated for Blackwell racks. 60% faster GNN training with 43% less energy vs comparable drives.

Applications

AI training and inference storage tiers, graph neural network and recommendation workloads, HPC scratch and checkpoint volumes, high-frequency trading, caching, and performance-focused databases.

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