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Product Overview |
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The Lenovo NVIDIA Tesla T4 16GB GPU accelerates AI and graphics workloads through its efficient architecture and high-speed memory. It fits into PCI-E 3.0 x16 slots, making it a practical choice for data centers and enterprise systems focused on machine learning and real-time processing tasks. |
General Information |
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| Brand | Lenovo |
| Part Number | 699-2G183-0200-211 |
| Series | NVIDIA Tesla T4 |
Miscellaneous |
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| Eco Friendly | Yes |
| Compliance Standards | RoHS, CE |
Physical Characteristics |
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| Weight | 3.00 |
| Condition | Refurbished |
Product Description |
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The Lenovo NVIDIA Tesla T4 is a GPU accelerator card built for handling intensive AI workloads, machine learning inference, and high-performance graphics processing. It delivers a balance of powerful computational capabilities while maintaining efficient power consumption. Often found in data centers, research labs, and enterprise servers, this card is designed to accelerate applications that require rapid data processing and real-time analytics. Professionals involved in AI development, scientific simulations, and video processing benefit from its architecture and speed. Key Features
This GPU accelerator is typically deployed within high-density servers and AI-focused workstations where space and power efficiency matter. It plays a crucial role in speeding up model training and inference tasks without requiring extensive hardware changes. Users see improvements in processing times and the ability to tackle complex workloads more effectively. |
Use Cases |
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The Lenovo NVIDIA Tesla T4 GPU is primarily deployed in enterprise data centers and cloud environments where AI inference, machine learning, and accelerated computing tasks demand high efficiency and scalability. IT professionals managing virtualization platforms and real-time data processing workloads benefit notably from its optimized design and compatibility. How It's Used:
By integrating seamlessly into PCI-E 3.0 x16 slots, the Tesla T4 enables organizations to scale their AI and graphics workloads efficiently without significant infrastructure changes. Its design supports operational agility in diverse computing environments, balancing power and performance for demanding enterprise tasks. |