High-End Workstation with Multiple RTX 6000 Ada

Each NVIDIA RTX 6000 Ada Generation card has 48GB of ECC graphics memory. A workstation with two cards therefore has 96GB of installed VRAM, although applications do not automatically treat that as one unified memory pool.

They can support large local model deployments when the inference software can shard weights across GPUs and the model is appropriately quantized. A 70B model is much more practical in a multi-card configuration than in a single 48GB card, but context length and runtime overhead still affect the final fit.

The RTX 6000 Ada combines the Ada Lovelace architecture with 48GB of ECC memory and workstation-oriented drivers. That memory capacity is useful for fine-tuning, visualization, and larger inference workloads that exceed the usual capacity of consumer cards.

No, scaling depends on the model framework, PCIe layout, workload parallelism, and communication overhead between cards. Two cards provide twice the installed 48GB memory capacity, but an application must be designed to use both GPUs efficiently.