NVIDIA’s Inference Context Memory Storage Platform, announced at CES 2026, marks a major shift in how AI inference is architected. Instead of forcing massive KV caches into limited GPU HBM, NVIDIA formalizes a hierarchical memory model that spans GPU HBM, CPU memory, cluster-level shared context, and persistent NVMe SSD storage.
This enables longer-context and multi-agent inference by keeping the most active KV data in HBM while offloading less frequently used context to NVMe—expanding capacity without sacrificing performance. This shift also has implications for AI infrastructure procurement and the secondary GPU/DRAM market, as demand moves toward higher bandwidth memory and context-centric architectures.
This enables longer-context and multi-agent inference by keeping the most active KV data in HBM while offloading less frequently used context to NVMe—expanding capacity without sacrificing performance. This shift also has implications for AI infrastructure procurement and the secondary GPU/DRAM market, as demand moves toward higher bandwidth memory and context-centric architectures.