Five reasons your next inference deployment should be one server.Run every model your teams need in parallel, one per GPU, on AMD Instinct™ MI350P.
When a job outgrows a server, the standard answer is to buy another. Here is what changes when every model runs on one.
144 GB of HBM3E per MI350P holds a full 70B model at FP8, or gpt-oss-120b, on one card. Up to 30 GPUs on one AMD EPYC™ host means up to 30 models running in parallel.
Every GPU stays in one server on a LIQID PCIe Gen 5 fabric, peer-to-peer. There is no inter-node fabric to design, buy, power, tune or troubleshoot.
One host, one OS image, one license footprint and one thing to patch, instead of four of each. Configurations are fixed and tested, from 4 to 30 GPUs.
MI350P is a standard dual-slot PCIe card at 600 W, passively air-cooled. A full 30-GPU system draws about 22 kW. No liquid cooling and no rack redesign.
Add GPUs and the next job’s models to the same host: 10 GPUs for a team, 20 for a department, 30 for the enterprise.