
HP Q2N68A NVIDIA Tesla V100 16GB PCIe GPU
Accelerate Your Workloads with the HP NVIDIA Tesla V100 GPUUnlock unparalleled performance for deep learning, scientific computing, and data analytics with the HP NVIDIA Tesla V100. This high-performance GPU offers exceptional processing power and memory capacity to accelerate your most demanding...
*Price sourced from Amazon.com. Last updated:Jun 04, 2026.Price and availability are subject to change.
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Overview
Accelerate Your Workloads with the HP NVIDIA Tesla V100 GPU
Unlock unparalleled performance for deep learning, scientific computing, and data analytics with the HP NVIDIA Tesla V100. This high-performance GPU offers exceptional processing power and memory capacity to accelerate your most demanding workloads.
- API supported: openacc opencl directcompute
- Chipset manufacturer: NVIDIA
- Chipset line: Tesla
- Chipset model: V100
- Standard Memory: 16 GB
- Memory technology: HBM2
- Form Factor: plug-in card
- Card length: full-length
- Card height: full-height
- Cooler Type: passive cooler
- Platform supported: PC
- Standard memory: 16 GB
- Memory technology: HBM2
Key Features
Standard memory: 16 GB
Memory technology: HBM2
Specifications
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Pros & Cons
👍 Pros
- Equipped with 16 GB of standard memory, providing substantial capacity for demanding computational tasks.
- Utilizes HBM2 memory technology, which offers high bandwidth and efficiency for data processing.
- Designed for PCIe interface, ensuring compatibility with a wide range of modern server and workstation motherboards.
- The NVIDIA Tesla V100 GPU is engineered for high-performance computing and artificial intelligence workloads.
👎 Cons
- Specific clock speeds, CUDA core counts, or other detailed performance metrics are not provided in the available features.
- The cooling solution for this GPU is not described, which could be a factor in sustained high-load operations.
- No information regarding power consumption or recommended power supply requirements is given.
- Details on the physical dimensions or form factor are absent, which can be critical for system integration planning.

