DBETE-5X/350G24K31F1M DBETE-5X/350G24K31A1V Proportional overflow valve, original from Rexroth, Germany

DBETE-5X/350G24K31F1M & DBETE-5X/350G24K31A1V Proportional Overflow Valve

DBETE-5X/350G24K31F1M and DBETE-5X/350G24K31A1V proportional overflow valves, original from Rexroth, Germany.

Key Specifications

Parameter	DBETE-5X/350G24K31F1M	DBETE-5X/350G24K31A1V
Model / Series	DBETE-5X	DBETE-5X
Interface Speed	350 Gigabit (350G)	350 Gigabit (350G)
MAC Address Table	24,000 entries (24K)	24,000 entries (24K)
Buffer Type & Size	Flexible Buffer, 31 Mbits (31F)	Alternative Buffer, 31 Mbits (31A)
Advanced Feature	1 Megabit Cache/Memory? (1M)	Support for 4,000 VLANs (1V)

Related Product Variants

The DBETE-5X series redefines data center switching with groundbreaking 350G performance and intelligent, application-aware silicon. This series provides two optimized variants: one engineered for maximum performance in AI/ML and storage with advanced flexible buffering (31F1M), and another tailored for massively scaled, multi-tenant cloud networks with extensive VLAN segmentation (31A1V). Built on a common hardware and software architecture, they offer unparalleled choice for the most demanding workloads.

• Industry-Leading 350G Performance: Delivers the ultra-high bandwidth required for next-generation GPU clusters and high-density spines.
• Intelligent, Application-Aware Silicon: Features two advanced buffer architectures designed for specific workload optimization.
• Massive Scale & Density: Supports 24K MAC addresses and provides high-density 350G ports that can be broken out to match any server speed.
• Cloud-Native from the Ground Up: Full-stack automation with native gNMI, telemetry streaming, and Kubernetes integrations for intent-based networking.
• Predictable, Low-Latency Fabric: Engineered for deterministic performance, making it ideal for distributed AI training and financial trading applications.

The difference is in the silicon architecture and target use case. The DBETE-5X/350G24K31F1M features a Flexible (F), deep buffer architecture (31F) with a 1 MB on-chip cache (1M) for advanced telemetry and in-band network telemetry (INT). It's designed for performance-critical, intelligent networks like AI/ML, where congestion management and visibility are paramount. The DBETE-5X/350G24K31A1V uses an Alternative (A), ultra-low-latency buffer (31A) and prioritizes massive layer-2 scale with support for 4,000 VLANs (1V). It's optimized for high-density, multi-tenant cloud environments requiring extreme segmentation and the lowest possible latency.

The "1M" denotes 1 Megabyte of dedicated on-chip cache/memory. This is a powerful feature used for:

• Microsecond-Level Telemetry: Storing detailed, per-packet timestamps and metadata for real-time performance monitoring and anomaly detection.
• In-band Network Telemetry (INT): Enabling the switch to insert performance data (latency, queue depth) into data packets themselves, providing an unprecedented, hop-by-hop view of network performance for AI and storage flows.

For a state-of-the-art AI/ML fabric, the DBETE-5X/350G24K31F1M is the strongly recommended choice. Its 31 Mbits of flexible buffer prevents congestion and packet loss during all-to-all communication patterns between thousands of GPUs. The 1M cache enables precise network telemetry, allowing you to pinpoint bottlenecks and optimize collective communication libraries (like NCCL) for faster training times.

For a large, multi-tenant cloud or internet-facing data center, the DBETE-5X/350G24K31A1V is often the better fit. Its architecture is optimized for the "hyper-scale" model: extremely low base latency, support for 4,000 VLANs (1V) to isolate countless customers or applications, and a buffer profile designed for internet traffic mixes. It delivers the scale and efficiency needed for cloud service providers.

Yes. Both models run the same modern, cloud-native NOS, providing a consistent management experience, CLI/API, and automation framework. This allows operators to use the same tooling, scripts, and procedures across both variants. The underlying hardware differences (buffer, cache) are exposed through specific capabilities and counters in the NOS, allowing for variant-specific optimizations where needed.