NVIDIA L4 24GB – Ada Lovelace Data Center GPU – ICONS Integrated IT Solutions

Description

The NVIDIA L4 Tensor Core GPU is designed to deliver accelerated computing in a compact and highly power-efficient form factor. It targets data-center workloads where performance per watt, deployment density, and broad workload support are important.

The L4 is powered by NVIDIA’s Ada Lovelace architecture and integrates 7,424 CUDA cores, providing parallel processing capabilities for AI, compute, graphics, and video workloads.

Its 58 fourth-generation Tensor Cores provide hardware acceleration for deep-learning and AI inference workloads. The GPU supports modern AI precision formats including FP8, FP16, BF16, INT8, and TF32, allowing inference and machine-learning applications to optimize performance and efficiency according to workload requirements.

The GPU includes 24GB of ECC-protected GDDR6 memory connected through a 128-bit memory interface. With memory bandwidth of up to 300GB/s, the L4 can efficiently process AI models, video data, graphics assets, and other datasets while maintaining a relatively low power footprint.

One of the L4’s most important advantages is its 72W maximum power consumption. This allows multiple accelerators to be deployed in a server while minimizing power and cooling requirements compared with higher-power data-center GPUs.

The L4 also provides substantial dedicated video-processing capabilities, including two NVENC encoders and four NVDEC decoders, with support for AV1 encoding and decoding. This makes it particularly useful for video transcoding, streaming, AI-enhanced video, cloud gaming, and media workloads.

For graphics workloads, the L4 incorporates 24 third-generation RT Cores, enabling hardware-accelerated ray tracing and professional visualization. Its compact low-profile, single-slot PCIe form factor makes it suitable for dense server environments.

3. Complete Technical Specification

Specification	Details
Manufacturer	NVIDIA
Product	NVIDIA L4 Tensor Core GPU
Product Class	Data Center GPU / Accelerator
Architecture	NVIDIA Ada Lovelace
CUDA Cores	7,424
Tensor Cores	58, 4th Generation
RT Cores	24, 3rd Generation
GPU Memory	24GB
Memory Type	GDDR6
Memory ECC	Yes
Memory Interface	128-bit
Memory Bandwidth	300GB/s
FP32 Performance	Up to 30.3 TFLOPS
FP16 Tensor Performance	Up to 242 TFLOPS*
BF16 Tensor Performance	Up to 242 TFLOPS*
FP8 Tensor Performance	Up to 485 TFLOPS*
INT8 Tensor Performance	Up to 485 TOPS*
RT Performance	Up to 121 TFLOPS
System Interface	PCIe 4.0 x16
Form Factor	Low-profile, single-slot
Cooling	Passive
Maximum Power	72W
Video Encoders	2 × NVENC
Video Decoders	4 × NVDEC
AV1 Encoding	Supported
AV1 Decoding	Supported
MIG	Supported
Virtualization	NVIDIA vGPU
Primary Deployment	Data Center / Edge / Server
Primary Workloads	AI inference, video, graphics, virtualization
Display Outputs	Not intended as a conventional desktop display GPU

* Tensor performance figures depend on precision mode and NVIDIA’s specified performance methodology.

4. Applications

The NVIDIA L4 is optimized for:

AI inference
Generative AI inference
Large Language Model inference
Machine learning
Deep learning
Computer vision
Natural language processing
Recommendation systems
Video transcoding
Video streaming
Real-time video analytics
AV1 media processing
Cloud gaming
Graphics virtualization
Virtual desktop infrastructure (VDI)
Remote workstations
3D visualization
Professional graphics
Ray-traced applications
Edge AI
Enterprise AI
Cloud computing
Data-center acceleration

5. Compatibility

Hardware Compatibility

The NVIDIA L4 is designed for compatible servers supporting:

PCIe 4.0 x16
Low-profile, single-slot GPU installation
Passive GPU cooling
Adequate server airflow
Compatible PCIe power and system configuration
Server BIOS and firmware supporting the accelerator

Its 72W power envelope allows it to operate in many high-density server environments without the substantial power infrastructure required by larger accelerators.

Software Compatibility

The L4 supports NVIDIA’s enterprise software ecosystem, including:

CUDA
NVIDIA AI Enterprise
NVIDIA TensorRT
NVIDIA Triton Inference Server
NVIDIA NGC
NVIDIA vGPU
NVIDIA Omniverse
CUDA-accelerated AI frameworks
Professional visualization software
Video-processing applications

Important Cooling Note

The L4 uses a passive thermal design, so it relies on the server’s airflow system for cooling. It should be installed in a qualified server chassis rather than an ordinary desktop system without engineered airflow.