RTX PRO Workstations for AI
Lenovo ThinkStation P3 Ultra (RTX PRO 4500) leads this page with an AIPC Score of 47.6, giving a local model about 32GB of usable AI memory at $2,029.99 for the 32GB / 512GB configuration. 4 systems on this page, 1 with a verified price.
Updated
| # | System | Type | AI Memory | GPU/NPU | AI Score | Price | Verified | View |
|---|---|---|---|---|---|---|---|---|
| 1 | Workstation | 96GB | RTX PRO 6000 Blackwell | 73 | No verified price | — | View details → | |
| 2 | Workstation | 48GB | RTX PRO 5000 Blackwell | 56.8 | No verified price | — | View details → | |
| 3 | Lenovo ThinkStation P3 Ultra (RTX PRO 4500) | Workstation | 32GB | RTX PRO 4500 Blackwell | 47.6 | $2,029.99 | View Deal on Amazon → | |
| 4 | HP Z2 Tower G1i (RTX PRO 4500) | Workstation | 32GB | RTX PRO 4500 Blackwell | 46.6 | No verified price | — | View details → |
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply to the purchase of this product.
Why these exist
An RTX PRO 6000 puts 96GB of ECC memory behind one graphics processor at 1,792 GB/s. That combination, large memory and high bandwidth together, exists nowhere else in this catalogue, and it is the only way to hold a 70B model entirely in VRAM at full speed.
Usable AI memory decides what a machine can load at all, and memory bandwidth decides how fast it answers once loaded. Those two numbers matter more than the processor name on the box. A machine with a large unified pool and modest bandwidth will run a very large model slowly; a machine with a fast narrow pool will run a small model quickly and refuse a large one outright.
What you pay for
ECC memory, certified drivers, support and sustained cooling. None of those make a benchmark faster, and all of them matter when a job runs overnight and must not fail.
When to buy something else
If your models fit 32GB, a consumer card does the same work for much less money. If your priority is model size rather than speed, a unified-memory machine gives more room per dollar. These are for the case where both matter at once.

