NETGEAR
SKU: MSM4320-100NES
Overview
NETGEAR CSM4316-100NES M4350-16C 16-Port 100G Switch The NETGEAR M4350-16C (model CSM4316-100NES) is a 1U rack-mount switch purpose-built for AI compu…
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Overview
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The NETGEAR M4350-16C (model CSM4316-100NES) is a 1U rack-mount switch purpose-built for AI compute clusters and high-performance data center environments where 100G QSFP28 interconnect is non-negotiable. Sixteen ports of 100G density in a single rack unit means you can wire up large GPU clusters, distributed training infrastructure, or dense HPC workloads without sprawling across multiple switch chassis.
This is a fixed-configuration switch with no modular slots—what you see is what you deploy. The 16 QSFP28 ports run at 100 Gbps each, delivering 3.2 Tbps of aggregate switching capacity. The design assumes you're moving petabytes of data between compute nodes, storage arrays, and external networks. Out-of-band 1G Ethernet management port keeps the control plane separate from your 100G data traffic, which is standard practice in AI ops where you don't want administrative traffic competing for precious fabric bandwidth. USB-C connectivity on the chassis supports out-of-band console access—useful when the management network is saturated or unreachable.
The CSM4316-100NES integrates into Kubernetes cluster networks, HPC job schedulers (SLURM, PBS), and distributed training frameworks (PyTorch Distributed, TensorFlow) via standard Ethernet. QSFP28 optics are commodity—you'll use either passive DAC (direct-attach copper, up to 3m) for intra-rack cabling or active or passive fiber modules (SM/MM) for inter-rack or campus distances. Interoperability with Mellanox, Broadcom, or Cisco fabric endpoints is standard; confirm your specific optic SKUs with your integrator. NETGEAR Insight cloud management (if enabled) provides dashboard visibility, but many AI operators prefer local controller-based management (Ansible, Terraform, or custom Python) to avoid external dependencies during training runs.
Q: What QSFP28 optics do I need to populate the CSM4316-100NES?
A: The switch itself does not include optics. You'll source them separately based on distance and budget—passive DAC for same-rack connections (0–3m), active DAC for medium distances, or fiber modules (100GBASE-SR, 100GBASE-LR, etc.) for longer runs. Verify compatibility with your specific optic part numbers before deployment.
Q: Can I mix different port speeds on the CSM4316-100NES?
A: No. All 16 ports are hard-wired for 100G QSFP28. There is no downshift to 40G or 10G on this model. If you need mixed speeds, consider a different NETGEAR switch family with modular or multi-rate ports.
Q: Does the CSM4316-100NES support redundant power supplies?
A: Power architecture specifications are not detailed in the available evidence. Confirm redundancy requirements with the manufacturer or integrator before final procurement.
Q: What is the warranty on the CSM4316-100NES?
A: This unit is factory-new with full US manufacturer warranty path. Exact warranty duration should be confirmed at point of purchase or with the supplier.
Q: Is the CSM4316-100NES NDAA Section 889 compliant?
A: NDAA compliance is not documented in the available product evidence. If NDAA compliance is a requirement, verify directly with NETGEAR or your procurement team before purchase.

The CSM4316-100NES is built for environments where 100G fabric density is the baseline, not an upgrade. If you're standing up a serious AI training cluster with hundreds of GPUs, the 16 QSFP28 ports and 3.2 Tbps switching capacity mean you can drive sustained east-west traffic without the bottleneck that kills iteration speed on distributed model training. The out-of-band 1G management port is not optional—it's your lifeline when the data plane is running hot.
Technical Highlights:
Deployment Considerations:
Deploy the CSM4316-100NES when you're building a dedicated high-speed fabric for GPU-intensive workloads (large language model training, computer vision at scale, multi-node fine-tuning). It assumes you've committed to 100G across the board and you're optimizing for throughput and latency, not for maximum port flexibility.
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