{
 "id": "2.02",
 "slug": "dram-ddr5-rdimm-mrdimm-lpddr5x-for-grace",
 "url": "/parts/memory-and-storage/dram-ddr5-rdimm-mrdimm-lpddr5x-for-grace",
 "name": "DRAM",
 "qualifiers": "DDR5 RDIMM/MRDIMM, LPDDR5X for Grace",
 "layer": {
  "id": 2,
  "name": "Memory & storage"
 },
 "parent_id": null,
 "children": [],
 "summary": "Off-package system memory — DDR5 modules for host CPUs and LPDDR5X soldered near Nvidia's Grace CPU — that holds the working data a server's processors operate on.",
 "description_md": "DRAM sits a step further from compute than HBM: it serves the host CPU rather than the accelerator, reached over the memory channels described by the buffer chips in the next part, and it is what memory modules (2.03) package into a pluggable form. AI servers lean on host DRAM for data staging, batching, and checkpoint handling ahead of GPU reads, and newer module standards like MRDIMM exist specifically to push more bandwidth through the same socket as core counts rise. A structural pressure worth watching is that HBM and standard DRAM are produced on the same manufacturing lines by the same small set of makers, so wafer capacity a supplier commits to HBM is capacity it is not committing to commodity DRAM — a trade-off that can tighten DRAM supply and pricing even though DRAM itself has not become any more technically exotic. For an investor, this layer is less about a single chokepoint than about how the same three suppliers allocate capacity across HBM, DRAM, and LPDDR product lines as AI demand pulls at all three simultaneously.",
 "ai_delta": "AI servers' data-staging and checkpointing needs raise host DRAM content per node, and HBM production competing for the same fab capacity tightens standard DRAM supply alongside it.",
 "bottleneck_status": null,
 "scale_tiers": [
  "edge",
  "enterprise",
  "hyperscale_building",
  "ai_campus",
  "gw_class"
 ],
 "density_modes": [
  "any"
 ],
 "scale_notes": "Quantity tracks node count and the memory-per-socket ratio a platform is designed around, not the facility's physical scale.",
 "flow": [
  "compute",
  "data"
 ],
 "companies": [
  {
   "company_id": "micron",
   "name": "Micron",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "public",
   "ticker": "MU",
   "product_note": null,
   "note": null,
   "source_url": null
  },
  {
   "company_id": "nanya",
   "name": "Nanya",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "public",
   "ticker": "2408.TW",
   "product_note": null,
   "note": null,
   "source_url": null
  },
  {
   "company_id": "samsung-electronics",
   "name": "Samsung Electronics",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "public",
   "ticker": "005930.KS",
   "product_note": null,
   "note": null,
   "source_url": null
  },
  {
   "company_id": "sk-hynix",
   "name": "SK Hynix",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "public",
   "ticker": "000660.KS",
   "product_note": null,
   "note": null,
   "source_url": null
  },
  {
   "company_id": "winbond",
   "name": "Winbond",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "public",
   "ticker": "2344.TW",
   "product_note": null,
   "note": null,
   "source_url": null
  },
  {
   "company_id": "cxmt",
   "name": "CXMT",
   "role": "manufacturer",
   "confidence": "inferred",
   "ownership_type": "private",
   "ticker": null,
   "product_note": null,
   "note": "China",
   "source_url": null
  }
 ]
}