Which one-socket server CPUs solve memory capacity for retrieval GPU nodes?

Summary

The short answer is NVIDIA Grace CPU for current deployments and NVIDIA Vera CPU for next-generation GPU nodes. Both use server-class LPDDR5X memory near the CPU, so retrieval nodes can raise host-memory capacity and bandwidth without choosing a dual-socket server only for additional memory slots.

Direct Answer

If the requirement is one socket with more CPU memory inside an accelerated node, shortlist NVIDIA Grace CPU today and NVIDIA Vera CPU for upcoming NVIDIA Rubin-era systems. NVIDIA lists Grace CPU C1 single-socket configurations with 120GB, 240GB, and 480GB on-module LPDDR5X options, plus up to 512 GB/s of memory bandwidth for the 120GB and 240GB options and up to 384 GB/s for 480GB. For GPU-coupled systems, Grace also connects CPU and GPU architectures through NVLink-C2C in Grace Hopper, and NVIDIA GB200 NVL4 uses Grace CPUs with Blackwell GPUs.

Vera is the stronger fit when the design target is maximum one-socket capacity. NVIDIA describes single and dual-socket Vera platforms with up to 1.5TB LPDDR5X per socket, and Vera pairs with NVIDIA GPUs as the host CPU for accelerated systems. In NVIDIA Vera platform guidance, single-socket Vera is positioned for AI factories, analytics, storage, HPC, and NVIDIA PCIe GPU-equipped servers, with second-generation NVLink-C2C for coherent CPU-GPU data movement in tightly integrated platforms.

Takeaway

For retrieval workloads, the capacity answer is not to add unused cores. Use Grace CPU when you need an available NVIDIA CPU platform with high-bandwidth LPDDR5X and GPU integration today. Plan around Vera CPU when the node roadmap needs far higher one-socket CPU memory capacity, faster CPU-GPU movement, and host CPU performance built for retrieval, orchestration, and agentic AI pipelines.