Yeah, that can't be cheap....
Archive: https://archive.today/GSzO6
From the post:
>In the era of foundation models, multimodal AI, LLMs, and ever-larger datasets, access to raw compute is still one of the biggest bottlenecks for researchers, founders, developers, and engineers. While the cloud offers scalability, building a personal AI Workstation delivers complete control over your environment, latency reduction, custom configurations and setups, and the privacy of running all workloads locally.
This post covers our version of a four-GPU workstation powered by the new NVIDIA RTX 6000 Pro Blackwell Max-Q GPUs. This build pushes the limits of desktop AI computing with 384GB of VRAM (96GB each GPU), all in a shell that can fit under your desk.
Yeah, that can't be cheap....
Archive: https://archive.today/GSzO6
From the post:
>>In the era of foundation models, multimodal AI, LLMs, and ever-larger datasets, access to raw compute is still one of the biggest bottlenecks for researchers, founders, developers, and engineers. While the cloud offers scalability, building a personal AI Workstation delivers complete control over your environment, latency reduction, custom configurations and setups, and the privacy of running all workloads locally.
This post covers our version of a four-GPU workstation powered by the new NVIDIA RTX 6000 Pro Blackwell Max-Q GPUs. This build pushes the limits of desktop AI computing with 384GB of VRAM (96GB each GPU), all in a shell that can fit under your desk.
(post is archived)