Zotac Gaming GeForce RTX 5060 Ti Twin Edge OC 16GB GDDR7

Brand: Zotac | Category: GPUs

SKU: ZT-B50620H-10M | Part #: ZT-B50620H-10M | MPN: ZT-B50620H-10M

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AI inference pipelines, real-time 3D rendering workloads, and HPC simulations at scale demand GPU memory bandwidth and compute density that can sustain high throughput without thermal compromise. The Zotac Gaming GeForce RTX 5060 Ti Twin Edge OC 16GB GDDR7 (part number ZT-B50620H-10M) delivers exactly that profile: a Blackwell-architecture accelerator built on the GB206 chip with 4,608 CUDA cores, 144 Tensor cores per SM, and 36 ray-tracing cores that scale inference workloads efficiently across distributed systems. The 16GB GDDR7 memory footprint paired with a 128-bit bus architecture balances capacity against the memory bandwidth requirements of modern transformer models and vision tasks. At 759 AI TOPS, this card sits in the practical middle ground between consumer-grade acceleration and enterprise-class expense—making it the card that AI infrastructure teams, data centre architects, and systems administrators select when they need proven Blackwell performance without overkill cost per node.

The Tensor core configuration on the Zotac card reflects a design philosophy focused on inference efficiency. With 144 Tensor cores per SM distributed across 36 SMs, the ZT-B50620H-10M excels at mixed-precision workloads—INT8 quantization, FP8, and FP16—where real-world deployments spend most of their cycles. This is not a training-focused part; it is purpose-built for the inference phase where models already trained are served at scale. The 180W TDP keeps power delivery and cooling infrastructure reasonable in dense rack configurations, and the PCIe Gen5 x8 interface ensures that the card can saturate its memory bandwidth without bottlenecking on the host CPU side. Zotac's Twin Edge OC thermal solution uses a dual-fan shroud with aluminum fin stacks and vapor-chamber heat spreading, keeping boost clocks stable at the card's 2622 MHz maximum frequency even under sustained load. For operations teams running large-scale inference clusters in Dubai, Abu Dhabi, or across Asia, this reliability profile matters more than peak FP32 numbers that exist on paper.

Deployment flexibility is baked into the Zotac Gaming RTX 5060 Ti's port layout. One HDMI 2.1b connector and three DisplayPort 2.1b outputs enable flexible display routing in visualization-heavy workflows—useful when inference pipelines drive real-time rendering dashboards or when the same hardware cluster supports both headless inference and workstation-class GPU compute. The part number ZT-B50620H-10M ships with Zotac's standard dual-slot form factor, meaning it fits standard PCIe slots in both single-GPU and multi-GPU configurations without physical interference. In a 4U chassis with dual-socket server motherboards, you can populate six or eight of these cards per node, creating inference clusters that process hundreds of simultaneous requests. The GDDR7 memory interface, while narrower than the HBM stacks on enterprise datacenter cards, maintains low latency for the random-access patterns typical of attention mechanisms and embedding lookups. Zotac has tuned the memory timing on this card for consistent performance rather than thermal instability—a trade-off that enterprise customers consistently value over marginal frequency gains.

The Blackwell architecture underpinning this Zotac card introduces structured sparsity support and improved ray-tracing efficiency compared to prior generations. For teams running sparse transformer models or deploying diffusion-based image generation inference, the native sparsity hardware accelerates computation by skipping zero-valued operations—a feature that shows measurable throughput gains over brute-force dense compute. The 36 RT cores enable real-time path tracing and denoising in rendering pipelines, making the card viable for both AI workloads and graphics-intensive applications in the same cluster. IT procurement managers and GPU-resource administrators value this flexibility because it reduces SKU sprawl: one card type can handle inference, visualization, and occasional HPC simulation without specialized partitioning. The card's support for NVIDIA CUDA 12.x and cuDNN 9.x means integration with existing PyTorch, TensorFlow, and ONNX Runtime pipelines requires no rework—it slots into production immediately upon arrival and integration into your hypervisor or container orchestration layer.

Zotac as a manufacturer has maintained a consistent track record of stable driver support and firmware updates across enterprise deployments. The Twin Edge OC branding reflects Zotac's commitment to factory overclocking that respects power and thermal budgets rather than pushing toward Silicon lottery binning. For procurement teams evaluating cost-per-inference-TFLOP, the ZT-B50620H-10M occupies a defensible position: it costs less per unit than data centre-grade A100 or H100 cards, consumes far less power, and delivers adequate performance for the majority of deployed inference workloads running quantized models in production. The 16GB GDDR7 capacity handles most open-source LLM inference at INT8 or FP8 precision; larger models simply require model parallelism across multiple cards, which the PCIe Gen5 x8 interface and NVIDIA Collective Communications Library (NCCL) support efficiently. Organizations across the GCC, South Asia, and Southeast Asia that operate inference-heavy workloads—financial institutions running fraud detection, healthcare providers processing medical imaging, and e-commerce platforms driving recommendation engines—have validated this architecture in production.

Performance Specifications and System Integration

• 4,608 CUDA cores with 144 Tensor cores per SM and 36 ray-tracing cores deliver 759 AI TOPS for mixed-precision inference and graphics acceleration
• 16GB GDDR7 memory on a 128-bit bus supports quantized LLM inference, embedding operations, and real-time rendering without external memory overhead
• 180W TDP and dual-slot form factor enable 6–8 card configurations per 4U node without custom power distribution or modified chassis airflow design
• PCIe Gen5 x8 interface and NVIDIA NCCL support seamless multi-GPU clustering for distributed inference across racks without proprietary NVLink interconnect
• Factory-overclocked to 2622 MHz with Zotac Twin Edge OC thermal design maintains stability under sustained inference workloads in data centre ambient temperatures
• HDMI 2.1b and triple DisplayPort 2.1b outputs accommodate visualization pipelines, rendering workloads, and live dashboard streaming from the same hardware
• Blackwell GB206 architecture with structured sparsity support and improved ray-tracing efficiency reduce compute cost for sparse transformer models and denoising inference
• Full CUDA 12.x, cuDNN 9.x, and ONNX Runtime compatibility ensures deployment into existing PyTorch, TensorFlow, and quantization frameworks without integration rework

Omnixon Global supplies the Zotac Gaming GeForce RTX 5060 Ti Twin Edge OC 16GB GDDR7 (part number ZT-B50620H-10M) to data centres, AI research labs, and enterprise infrastructure teams across the UAE, GCC region, and Asia. Our inventory maintains stock for immediate delivery to Dubai, Abu Dhabi, and regional distribution partners, with technical presales support to validate compatibility against your specific hypervisor, container platform, and inference framework. Whether you are architecting a new inference cluster, expanding existing GPU capacity, or evaluating cost-effective acceleration for mixed workloads, Omnixon Global offers procurement expertise and logistics coordination that respect both your timeline and budget. Please submit an RFQ through our portal or contact our technical sales team to discuss deployment requirements, volume pricing, and regional delivery options for the ZT-B50620H-10M and complementary Zotac or NVIDIA hardware.