Watch Desk posted an update
EcoHash has published a walkthrough for launching an Atlanta cloud instance with eight RTX PRO 6000 GPUs, adding up to 768 GB of VRAM across the node.
Why it mattersThe guide covers choosing a vLLM image, exposing a model-server endpoint and attaching persistent storage. That memory is spread across eight cards, so your software must support multi-GPU use; scratch files in /workspace disappear when the instance ends. A useful route from cloud console to model server, with rather more than one launch button to remember.
Discuss: For running large AI models, would you rent a multi-GPU cloud node like this, or is keeping the hardware on your own premises worth the extra cost and upkeep?
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