NVIDIA RTX PRO 6000 96GB GDDR7 AI Accelerator Card 900-5G144-2200-000
- RTX PRO 6000
- PCIe 5.0 x16
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16 GB GDDR6 AI accelerator with multi-precision Tensor cores in a 70-watt PCIe form factor
The NVIDIA Tesla T4 is a 16 GB GDDR6 AI accelerator card built for scale-out computing environments. It targets data-centre workloads such as deep learning training, inference, machine learning, data analytics and graphics. The full-height PCIe form factor fits standard server slots. Buyers who need more than 16 GB of memory or multiple cards per node should look elsewhere.
The card operates within a 70-watt power envelope, enabling energy-efficient deployment in dense racks. Its small PCIe form factor is optimised for scale-out servers where thermal headroom is limited. No external power connectors are required. Installations that cannot accommodate a full-height card or that demand lower power draw will need a different solution.
Accelerated containerised software stacks from NGC are combined with the hardware to deliver performance at scale. The bundled software simplifies deployment of diverse cloud workloads. Users who prefer to manage their own software stack or who rely on unsupported frameworks will not benefit from this integration.
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| Size & build | |
|---|---|
| Shipping weight | 0.45 kg |
| Package size | 25 × 25 × 25 mm |
Insert the full-height PCIe card into a compatible x16 slot, secure the bracket screw, and ensure the chassis airflow meets the 70-watt thermal design; the step often missed is verifying that the server BIOS allocates enough PCIe resources for the 16 GB frame buffer.
Plan to clean the passive heatsink fins annually and replace the card if the 16 GB GDDR6 memory or Tensor cores show persistent ECC errors; no fan or liquid-loop service is required because the 70-watt design uses passive cooling only.
The 70-watt power envelope is the first ceiling; once the Tensor cores drive the GPU to that sustained draw, the card throttles clocks to stay within the thermal budget before the 16 GB GDDR6 capacity becomes a bottleneck.
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