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NVIDIA Rubin Ultra (V300)

Product Overview​

NVIDIA Rubin Ultra (codename V300) is the flagship-enhanced variant of the Rubin architecture, announced at GTC 2026 (2026-03-17) alongside Rubin R200 and positioned as the top product for hyperscale training/inference. The original design uses a 4-die MCM package with 576GB HBM4e per card, expandable via NVL144 racks to 144 GPUs — NVIDIA's flagship answer for sovereign AI and yotta-scale clusters.

⚠️ Architecture revision notice: According to SemiAnalysis, the original 4-die Rubin Ultra design has been cancelled due to packaging manufacturing difficulty; the new version is scaled down to roughly half the size, with performance halved accordingly. The specs below are based on originally published information; final production specs are subject to NVIDIA's official announcements.

📌 2026-09 spec-cut report (SemiAnalysis / STAR Market Daily): Rubin Ultra's HBM configuration may be downgraded from HBM4E 12-Hi (384GB tier) to HBM4 8-Hi (192GB), with Samsung co-developing the 8-high product. The driver: after HBM/DRAM price hikes, memory already accounts for roughly 40% of total system TCO; the downgrade cuts HBM cost by more than 50%, and the saved budget shifts to the Scale-up network — under an NVL576 NPO scheme, the Scale-up network's share of rack spending rises from 4% to 12%. TrendForce also shows NVIDIA evaluating HBM4E 8-Hi / HBM4E 12-Hi / HBM4 8-Hi options in parallel from 2026 Q3. Final configuration subject to official announcements.

Core Specifications (original design, pending final official confirmation)​

SpecValue
GPU ArchitectureRubin architecture (MCM multi-chip module)
PackageOriginal 4-die design (⚠️ under revision)
ProcessPresumed TSMC 3nm (same as Rubin R200)
FP4 Inference ComputePresumed ~100 PFLOPS (original, dense)
FP8 Training ComputePresumed ~70 PFLOPS (original)
Memory Capacity576 GB HBM4e (original design)
Memory TypeHBM4e
Memory BandwidthPresumed >44 TB/s (HBM4e)
InterconnectNVLink 7 (presumed, >3.6 TB/s unidirectional)
TDPPresumed 3000W+ (liquid cooling mandatory)
AnnouncedMarch 17, 2026 (GTC 2026)
Mass ProductionPresumed 2027 H2 - 2028 (original timeline)
PricingPresumed $15-21 million per NVL144 rack

Comparison with Rubin R200​

ItemRubin R200Rubin Ultra (original)
GPUs/rack72 (NVL72)144 (NVL144)
Memory/GPU288 GB HBM4576 GB HBM4e
HBM/rack20,736 GB82,944 GB
Mass production timing2026 H22027 H2 - 2028
PositioningVolume workhorseFlagship-enhanced

NVL144 rack: Rubin Ultra forms racks of 144 GPUs with 82,944 GB of total HBM — 4x the memory capacity of NVL72 (Rubin R200).

Platform Configuration (original NVL144)​

  • 144 Rubin Ultra GPUs
  • 72 Vera CPUs (presumed)
  • Total memory: 82.9 TB HBM4e
  • Total compute: Presumed ~14 EFLOPS FP4 (original)
  • TDP: Presumed ~360kW (full liquid cooling mandatory)
  • Mass production: Presumed from 2027 H2

Mass Production and Delivery (original timeline)​

  • GTC 2026: Announced alongside Rubin R200
  • Mass production: Presumed 2027 H2 - 2028 (later than Rubin R200's 2026 H2)
  • ⚠️ Revision risk: SemiAnalysis reports the original 4-die design has been cancelled; the new version's specs and schedule may change

Use Cases​

Rubin Ultra targets hyperscale data centers and sovereign AI clusters, suited for:

  • Ten-trillion-parameter LLM training
  • yotta-scale AI factories
  • Ultra-long-context inference (576GB memory per card)
  • National-scale AI infrastructure

References​

  • NVIDIA GTC 2026 keynote (Rubin Ultra announcement)
  • SemiAnalysis: Rubin Ultra's original 4-die design cancelled; new version scaled down by about half
  • SemiAnalysis / STAR Market Daily (2026-09): Rubin Ultra memory may be cut from the 384GB tier to 192GB HBM4, with budget shifted to Scale-up optical interconnect
  • Industry supply chain analysis (Foxconn): V300 576GB HBM4e / 144-GPU rack, $21,000/rack