SSD-asema Team Group 1 TB M.2 PCI Express 3.0 NVMe MP33 PRO

The Team Group MP33 PRO 1 TB M.2 PCI Express 3.0 NVMe SSD delivers PCIe performance in a compact M.2 2280 form factor. With PCIe Gen3 x4 interface and 3D NAND technology, this 1 TB drive provides fast sequential read/write speeds up to 2100/1700 MB/s and a high level of random IOPS, suitable for use in PCs and laptops for storage, gaming, and content creation.

Advantages

This M.2 PCIe NVMe SSD offers significantly higher throughput than SATA drives thanks to the PCIe Gen3 x4 interface, enabling faster boot times and reduced load times for applications and games. The drive supports high random read/write performance and uses smart algorithm management to maintain operational efficiency and extend service life. Available capacities up to 2 TB allow ample space for large files and projects.

Suitable for

• Gaming PCs and laptops where reduced load times are important
• Video and audio content creators who need fast access to large files
• Graphic design and multimedia workstations requiring high-capacity, high-speed storage
• System drives for faster boot and application launch

Key specifications

• Form factor: M.2 2280
• Interface: PCIe 3.0 x4, NVMe
• Capacity: 1 TB (up to 2 TB available in the product line)
• Sequential read speed: up to 2100 MB/s
• Sequential write speed: up to 1700 MB/s
• Random 4K IOPS (approx.): up to 220,000
• Weight: 0.006 kg

How to use

Install the M.2 SSD into an available M.2 2280 slot on a compatible motherboard or laptop following the device manufacturer's instructions. Ensure the system supports PCIe Gen3 x4 NVMe storage for full performance. After physical installation, initialize and format the drive in the operating system, then migrate or install the OS and applications if required.

Recommendations

For sustained high performance, enable any available NVMe drivers provided by the system vendor and keep firmware up to date. Use adequate cooling or a motherboard heatsink if the platform is subjected to prolonged heavy workloads.