Mellanox BlueField-2 DPU 25GbE 2-Port SFP56 PCIe 4.0 x8

MBF2H332A-AECOT / BF2H332A

The Mellanox BlueField-2 Data Processing Unit (DPU), model MBF2H332A-AECOT, is a high-performance, Arm-based SmartNIC/DPU designed to offload, accelerate, and isolate infrastructure services such as networking, storage, and security. Combining an 8-core Arm CPU with dual 25GbE SFP56 connectivity, BlueField-2 enables advanced software-defined data center architectures using the NVIDIA DOCA framework.

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Part Number Identification

The following part numbers refer to the same BlueField-2 DPU platform:

• MBF2H332A-AECOT – Mellanox / NVIDIA Model (P-Series)

• BF2H332A – Series / Chipset Identifier

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Device Type & Classification

• Device Type: Data Processing Unit (DPU) / SmartNIC

• Series: Mellanox BlueField-2 (P-Series)

• Primary Use: Infrastructure offload, SDN, SDS, and zero-trust security

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Network & Host Interface

Attribute	Specification
Network Ports	2 × 25GbE SFP56
Supported Speeds	1GbE / 10GbE / 25GbE
Host Interface	PCI Express 4.0 x8 (backward compatible with PCIe 3.0 / 2.0 / 1.1)
Form Factor	Half-Height, Half-Length (HHHL)
Bracket	Full-height (tall) bracket included

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Compute & Memory

Component	Specification
Processor	8-core Armv8-A72, 64-bit, 2.5 GHz
System Memory	16 GB DDR4 ECC (3200 MT/s)
On-Board Storage	64 GB eMMC

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Offload & Acceleration Features

• NVMe-over-Fabrics (NVMe-oF) offloads

• RoCE (RDMA over Converged Ethernet)

• ASAP² accelerated switching and packet processing

• TCP/IP & UDP/IP offloading

• VLAN and SR-IOV support

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Security Capabilities

• Crypto-enabled DPU

• IPsec / TLS data-in-motion encryption

• Secure Boot & Hardware Root of Trust

• AES-GCM, AES-XTS, SHA hardware acceleration

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Management & Power

• Out-of-Band Management: 1 × 1GbE OOB port

• Power Source: PCIe slot (12V)

• Operating Temperature: 0°C to 55°C (32°F to 131°F)

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Software & Ecosystem

• Supported via: NVIDIA DOCA software framework

• Compatible with Linux-based Arm ecosystems for custom application development, infrastructure services, and cloud-native workloads