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Cisco UCSX-GPU-L4 | NVIDIA L4 24GB Graphics Card, 70W, PCIe Gen4 x16

SKU:UCSX-GPU-L4

Stock Status: Enquire

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Description

The Cisco UCSX-GPU-L4 features the NVIDIA L4 Tensor Core GPU with 24GB GDDR6 memory, built on the Ada Lovelace architecture for efficient AI inference, video processing, and virtualization workloads. This single-slot, half-height half-length GPU delivers 485 TOPS INT8 performance at just 70W power consumption, making it ideal for space-constrained UCS X-Series compute nodes. Designed for enterprise data centers and edge deployments requiring accelerated AI, VDI, and graphics in a compact, energy-efficient form factor.

Features

NVIDIA Ada Lovelace architecture with 4th generation Tensor Cores for AI acceleration
- FP8 precision support for up to 4X higher AI inference performance with structured sparsity
- 24GB GDDR6 memory with ECC for reliable data integrity in enterprise workloads
- 3rd generation RT Cores with 2X ray-triangle intersection throughput
- Hardware-accelerated AV1 encode/decode for efficient video streaming
- NVIDIA DLSS 3 support for AI-powered graphics and rendering acceleration
- Single-slot, half-height half-length form factor for maximum server density
- 70W TDP with passive cooling for quiet, reliable operation
- PCIe Gen4 x16 interface for high-bandwidth GPU-to-host communication
- Multi-instance GPU (MIG) capable for workload isolation and resource partitioning
- NVIDIA Virtual GPU (vGPU) software support for VDI and virtualized workloads
- TensorRT optimization for low-latency AI inference deployment
- CV-CUDA support for accelerated computer vision pipelines
- Designed for UCS X-Series modular compute architecture integration

Warranty

All products sold by XS Network Tech include a 12-month warranty on both new and used items. Our in-house technical team thoroughly tests used hardware prior to sale to ensure enterprise-grade reliability.

All technical data should be verified on the manufacturer data sheets.

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Technical Specifications

FAQs

Technical Specifications

GPU: NVIDIA L4 Tensor Core with Ada Lovelace architecture
- Memory: 24GB GDDR6 with 300GB/s bandwidth
- CUDA Cores: 7,424
- Tensor Cores: 240 (4th generation with FP8, TF32, FP16, BFLOAT16 support)
- Performance: 485 TOPS (INT8), 485 TFLOPS (FP8), 242 TFLOPS (FP16/BFLOAT16), 120 TFLOPS (TF32), 30.3 TFLOPS (FP32)
- RT Cores: 3rd generation for ray tracing acceleration
- Power Consumption: 70W TDP
- Form Factor: Single-slot, half-height half-length (HHHL)
- Interface: PCIe Gen4 x16
- Cooling: Passive cooling design
- Video Encode/Decode: NVENC, NVDEC with AV1 support
- Compatibility: Cisco UCS X-Series modular systems (X210c, X215c compute nodes with GPU fabric module)

FAQs

Q: What UCS systems is the UCSX-GPU-L4 compatible with?
A: The UCSX-GPU-L4 is designed for Cisco UCS X-Series modular systems, specifically the X210c and X215c compute nodes when equipped with the appropriate GPU fabric module. It requires PCIe Gen4 x16 connectivity and is optimized for the UCS X-Series chassis architecture.

Q: What are the primary use cases for the NVIDIA L4 GPU?
A: The L4 is optimized for AI inference at scale, video transcoding and streaming, virtual desktop infrastructure (VDI), graphics rendering, and generative AI applications. Its 70W power envelope and single-slot form factor make it ideal for high-density deployments where space and power efficiency are critical.

Q: How does the L4 compare to previous generation GPUs like the T4?
A: The L4 delivers approximately 2.5X higher generative AI performance compared to the T4, with support for FP8 precision and 4th generation Tensor Cores. It maintains the same 70W power envelope and single-slot form factor while offering significantly improved AI inference, video processing, and graphics capabilities through the Ada Lovelace architecture.

Q: Does the L4 require external power connectors?
A: No, the UCSX-GPU-L4 draws its 70W power entirely through the PCIe slot without requiring auxiliary power connectors, simplifying installation in UCS compute nodes and enabling dense GPU configurations.

Q: What AI frameworks and software are supported?
A: The L4 supports all major AI frameworks including TensorFlow, PyTorch, and ONNX Runtime through NVIDIA CUDA, cuDNN, and TensorRT libraries. It is optimized for inference workloads with FP8, TF32, FP16, and INT8 precision modes, and includes support for NVIDIA AI Enterprise software suite for enterprise deployments.

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