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NVIDIA

NVIDIA Tesla M10 32GB GDDR5 PCIe 3.0 x16 workstation graphics card

SKU CH-WEJP-NMXPG MPN M10

Four-GPU accelerator with 32 GB GDDR5 memory and passive PCIe 3.0 x16 cooling for dense virtualised graphics and compute workloads

  • Four GPUs deliver massive parallel compute power
  • 32 GB GDDR5 memory handles large datasets and models
  • PCIe 3.0 x16 interface provides high-throughput host connectivity
  • Passive cooling suits dense, noise-sensitive server racks
  • Operates in 5 – 95 % humidity for harsh environments

Multi-GPU Accelerator

The NVIDIA Tesla M10 integrates four GPUs on a single PCIe 3.0 x16 card. It delivers 32 GB of GDDR5 memory for parallel compute and virtualised graphics workloads in dense server environments.

Virtual Desktop & Compute Targets

This card suits IT teams building VDI infrastructure or running CUDA-accelerated simulations where a passively cooled, multi-GPU module fits the chassis airflow. Buyers who need active cooling, single-GPU graphics, or driver support for consumer APIs should look at something else.

Passive Cooling Constraint

The M10 uses fanless heatsinks and requires server-grade airflow to stay within its 5–95 % operating humidity range. Confirm that your rack provides sufficient directed air before purchase.

Punti di forza

  • Four GPUs deliver massive parallel compute power
  • 32 GB GDDR5 memory handles large datasets and models
  • PCIe 3.0 x16 interface provides high-throughput host connectivity
  • Passive cooling suits dense, noise-sensitive server racks
  • Operates in 5 – 95 % humidity for harsh environments

Caratteristiche tecniche

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Domande su questo articolo

How do I verify the four GPUs are active after installing the card?

Check the NVIDIA control panel or nvidia-smi output; all four GPUs should appear with 32 GB total GDDR5 memory and CUDA cores detected.

What is included with the Dell H56H0 part and what must I source separately?

The card ships as a fanless PCIe 3.0 x16 accelerator; you must provide a server chassis with adequate airflow and a compatible power supply.

Which capacity should I choose for virtual desktop infrastructure workloads?

The 32 GB GDDR5 model with four GPUs is the only version listed and suits high-density VDI deployments.

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