Brand: PNY | Category: GPUs
SKU: TCSL424GB-1-LR | Part #: TCSL424GB-1-LR | MPN: TCSL424GB-1-LR
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PNY NVIDIA L4 24GB GDDR6 PCIe 4.0 Low-Profile GPU Accelerator is a next-generation inference accelerator designed for enterprises deploying large-scale AI models, generative AI applications, and real-time inference in space-constrained datacenter environments. The low-profile form factor enables deployment in standard 1U servers without custom riser cards or chassis modifications.
Key Features:
Perfect for:
| Brand | PNY |
| Category | GPUs |
| SKU | TCSL424GB-1-LR |
| Part Number | TCSL424GB-1-LR |
| Condition | New |
| GPU Memory | 24GB GDDR6 |
| Form Factor | Low-Profile PCIe Card |
| Memory Bandwidth | 432 GB/s |
| Max Power Consumption | 70W |
| PCIe Generation | PCIe 4.0 x23 |
| Display Outputs | 1x DisplayPort 1.4a |
| Height | Low-Profile (67.05mm) |
| Length | 248.76mm |
| CUDA Capability | SM89 (Ada) |
| Operating Temperature | 0-65°C |
| Cooling | Passive |
| Driver Support | NVIDIA CUDA Toolkit 12.x |
The PNY NVIDIA L4 24GB GDDR6 PCIe 4.0 Low-Profile GPU Accelerator accelerates AI/ML training and inference, scientific HPC and virtualised GPU workloads in data-centre servers. Typical deployments include model training clusters, inference serving, computer-vision pipelines and rendering farms.
Key specifications for the PNY NVIDIA L4 24GB GDDR6 PCIe 4.0 Low-Profile GPU Accelerator: new condition; gpu memory 24GB GDDR6; form factor Low-Profile PCIe Card; memory bandwidth 432 GB/s; max power consumption 70W; pcie generation PCIe 4.0 x23; display outputs 1x DisplayPort 1.4a. Manufacturer part number TCSL424GB-1-LR. For the full datasheet with electrical, environmental, and compliance details, contact our pre-sales engineering team.
The PNY NVIDIA L4 24GB GDDR6 PCIe 4.0 Low-Profile GPU Accelerator needs a GPU-qualified server with adequate power and cooling for its TDP, plus NVIDIA CUDA driver support in your hypervisor or bare-metal OS. Our team confirms chassis qualification, slot or baseboard type and PSU headroom before quoting.