NVIDIA Mellanox 920-9B110-00FH-0D0: The High-Efficiency InfiniBand Switch for Demanding HPC and AI Clusters

January 4, 2026

NVIDIA Mellanox 920-9B110-00FH-0D0: The High-Efficiency InfiniBand Switch for Demanding HPC and AI Clusters

As the computational demands of artificial intelligence and high-performance computing continue to surge, the need for a robust, low-latency network fabric has never been greater. Addressing this critical requirement, NVIDIA Mellanox proudly introduces the 920-9B110-00FH-0D0 InfiniBand switch OPN solution. This platform is meticulously engineered to deliver the optimal balance of high bandwidth, extreme efficiency, and simplified management for modern accelerated computing environments.

Architected for Performance and Scalability

The NVIDIA Mellanox 920-9B110-00FH-0D0 is designed as a foundational building block for scalable cluster interconnects. Its core is powered by the advanced 920-9B110-00FH-0D0 MQM8790-HS2F 200Gb/s HDR InfiniBand technology, providing exceptional data throughput essential for parallel workloads. This 920-9B110-00FH-0D0 InfiniBand switch OPN excels in environments where reducing communication overhead directly translates to faster results and lower operational costs.

The switch's architecture delivers several pivotal advantages for cluster optimization:

  • Ultra-Low Latency RDMA: Enables true Remote Direct Memory Access (RDMA), allowing data to bypass CPU and OS kernels for direct application-to-application transfer, drastically cutting latency and freeing server resources for computation.
  • Intelligent In-Network Computing: Features SHARP (Scalable Hierarchical Aggregation and Reduction Protocol) technology, offloading collective operations from servers to the switch network. This accelerates MPI operations and reduces data movement for AI training and scientific simulations.
  • Advanced Congestion Control: Implements adaptive routing and congestion control mechanisms to maintain high throughput and predictable performance even in densely populated, multi-tenant cluster deployments.
Detailed Specifications and Primary Use Cases

Engineers and procurement specialists can find comprehensive performance metrics and integration details in the official 920-9B110-00FH-0D0 datasheet. The 920-9B110-00FH-0D0 specifications confirm high port density, non-blocking internal bandwidth, and robust management capabilities. Importantly, the switch is designed to be 920-9B110-00FH-0D0 compatible with a wide ecosystem, ensuring smooth integration into both new builds and expansions of existing InfiniBand infrastructures.

The 920-9B110-00FH-0D0 InfiniBand switch OPN solution is ideally suited for several high-impact deployment scenarios:

  • Mid to Large-Scale AI/ML Training Clusters: Serves as the high-performance interconnect for GPU server racks, enabling efficient data parallelism and model parameter synchronization critical for rapid AI development cycles.
  • University and Enterprise HPC Centers: Provides a cost-effective, high-bandwidth backbone for research computing clusters used in engineering simulations, financial modeling, and life sciences research.
  • High-Performance Storage Fabrics: Connects compute nodes to parallel file systems and storage arrays, minimizing I/O wait times and accelerating data-intensive workflows.
A Strategic Enabler for Accelerated Computing

The launch of the 920-9B110-00FH-0D0 provides a compelling value proposition for organizations investing in computational excellence. For teams evaluating a 920-9B110-00FH-0D0 for sale, the total cost of ownership—factoring in performance gains, operational simplicity, and energy efficiency—often outweighs the initial 920-9B110-00FH-0D0 price. It represents a strategic investment in infrastructure that directly accelerates time-to-solution and enhances research competitiveness.

By deploying the NVIDIA Mellanox 920-9B110-00FH-0D0, network architects and data center operators gain a proven, high-efficiency solution to build and scale the low-latency interconnects that are fundamental to unlocking the full potential of RDMA, HPC, and AI clusters today and into the future.