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$200.00
The HP NVIDIA Tesla P4 is a compact, high-efficiency GPU designed for inference acceleration and data center workloads. With 8GB of GDDR5 memory, it delivers fast, reliable AI, deep learning, and high-performance computing (HPC) performance.
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Verified Warranty (3-12 month)
Overview
The HP NVIDIA Tesla P4 is purpose-built for accelerating inference workloads in data centers, cloud infrastructures, and AI applications. Its 8GB GDDR5 memory ensures efficient processing of deep learning models, image recognition, and real-time data analytics.
Built on NVIDIA’s Pascal architecture, the Tesla P4 combines high throughput with energy efficiency, making it ideal for dense server deployments. Its low-profile PCIe form factor allows for easy integration into rack-mounted servers while maintaining optimized thermal performance.
The Tesla P4 supports a wide range of AI frameworks, delivering reliable and consistent performance for large-scale deployments. Its passive cooling design and enterprise-grade components ensure stability and durability in demanding environments.
Details
| specifications | |
|---|---|
| Category | Data Center GPU / Accelerator AI & Deep Learning Hardware High-Performance Computing (HPC) |
| Specifications | GPU: NVIDIA Tesla P4 Memory: 8GB GDDR5 Interface: PCIe 3.0 x16 Architecture: Pascal Features: Inference acceleration, low power, enterprise-grade |
| Dimensions | Low-profile PCIe card Approx. 168 mm × 68 mm × 38 mm |
| Material | Industrial-grade PCB Aluminum heat sink for efficient cooling |
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Sarah M. (store manager) –
The Tesla P4 handles our inference workloads efficiently. It’s compact, energy-efficient, and integrates seamlessly into our servers. Excellent for AI projects.
Daniel T. (store manager) –
Installation was easy, and the card delivers consistent performance under heavy data center workloads. Ideal for deep learning applications.
Kevin L. (store manager) –
A solid GPU for inference acceleration. The 8GB memory and low-power design make it perfect for large-scale AI deployments in our servers.