The NVIDIA A10 24 GB is based on the Ampere architecture and combines computing power, large memory, and professional features for complex workloads in artificial intelligence (AI), parallel computing, GPU virtualization, and professional visualization. It is designed for environments where reliability, energy efficiency, and sustainable performance are essential.
Key Technical Specifications
Architecture and Computation
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GPU Architecture: NVIDIA Ampere Tensor Core – suitable for massive computations, AI, and unified workloads.
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CUDA Cores: up to 9216 computing cores for high parallel performance.
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Tensor Cores & RT Cores: specialized cores to accelerate AI and professional ray tracing.
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FP32 (single precision): ~31.2 TFLOPS of raw power.
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Tensor (TF32 / FP16 / INT8 / INT4): enhanced performance for AI frameworks.
Memory
Interface & Design
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System Bus: PCI Express 4.0 x16 for fast communication with the CPU.
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Form Factor: single-slot, full height/full length (FHFL) – suitable for compact servers and workstations.
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Cooling: passive solution (no onboard fan) requiring adequate chassis ventilation.
Power
Encoder / Decoder
For What Uses?
The NVIDIA A10 24 GB is designed for professional and data center environments:
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Artificial Intelligence & Deep Learning: training and inference of large models.
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Graphical Virtualization (vGPU): support for virtual desktops, cloud applications, and VDI.
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Scientific Computing & HPC: simulation, massive data analysis, distributed computing workflows.
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Pro Workstation: 3D visualization, accelerated rendering, CAD/CAM applications.
What it Brings to a System
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Large Memory Capacity (24 GB): handles very large datasets without swapping.
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High Parallel Performance: acceleration of AI training, simulations, and complex renderings.
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Energy Efficiency: contained TDP for powerful and reliable servers and workstations.
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Datacenter-Friendly Integration: form factor and cooling adapted for racks and professional infrastructures.
