The video highlights the Nvidia RTX Pro 5000 workstation GPU, particularly its 72GB GDDR7 variant, as a cost-effective and powerful option for local AI workloads, offering large VRAM capacity and stable high-bandwidth memory in a single card. It contrasts this GPU with other setups like the DGX Spark and multiple RTX 3090s, emphasizing the RTX Pro 5000’s balance of performance, compatibility, and ease of use for AI enthusiasts and professionals.
The video discusses the project llamas.ai, which focuses on recommending suggested builds for local AI rigs. The creator has completed the data model and found open-source benchmarking code from Visilla to run tests on various GPUs and builds. The goal is to gather real data on GPU performance in a way that makes sense for local AI enthusiasts. The creator invites viewers to contact them via Twitter to be among the first to try out the benchmark.
The main focus of the video is the Nvidia RTX Pro 5000, a workstation GPU that was quietly released recently. This card comes in two variants: a 48GB model and a newly introduced 72GB model, both using GDDR7 memory. The 72GB version is notable because it offers a large amount of VRAM at a relatively affordable price point compared to the more expensive RTX Pro 6000. The GPU is based on the same architecture as the RTX 5080, with around 14,000 CUDA cores, and is aimed primarily at AI workflows and professional use cases.
The video explains that the RTX Pro 5000 uses a 384-bit memory bus with 16 GDDR7 chips, each with 3GB capacity, rather than a 512-bit bus as initially speculated. The 72GB model essentially has more memory chips to increase capacity without changing the bus width or GPU die. This design allows for a stable and high-bandwidth memory setup, which is crucial for AI workloads. The card also supports multiple 4K displays and the latest AV1 video codecs, making it versatile for both AI and professional visualization tasks.
The creator compares the RTX Pro 5000 to other options like the DGX Spark and multiple RTX 3090 cards. While the DGX Spark is powerful, it is expensive and not very user-friendly for enthusiasts due to driver and software compatibility issues. On the other hand, a rig built with RTX 3090s can be bulky and less efficient. The RTX Pro 5000 strikes a balance by offering a large amount of VRAM in a single GPU at a reasonable price, making it a compelling choice for local AI researchers and hobbyists.
Finally, the video touches on the challenges of working with newer hardware like the DGX Spark, where many AI frameworks and tools need to be recompiled due to platform differences. This makes the RTX Pro 5000 more attractive for those who want a more straightforward setup. The creator encourages viewers to consider these GPUs for local AI projects and invites feedback and questions, emphasizing that this card could be a better investment for many enthusiasts than other high-end or multi-GPU setups.