How to read this page. Each section starts Simple, then goes to a Deep dive: stop wherever you have what you need. The small numbers are sources: click one to open the original document. Where the maker has not published a figure -- a price, a die size, a factory address -- this page says so rather than estimate it.
1.At a glance
SimpleStart here
The GB300 pairs NVIDIA’s Grace CPU with two Blackwell Ultra GPUs on one module; sold rack-scale as GB300 NVL72 — 72 GPUs and 36 CPUs in one liquid-cooled cabinet. Announced 18 March 2025 at GTC, the same day as B300 1.
Deep diveThe technical detail
Microsoft Azure switched on the first production-scale GB300 NVL72 cluster on 9 October 2025, built with OpenAI, at more than 4,600 Blackwell Ultra GPUs 2. CoreWeave announced its own first deployment, built with Dell, on 3 July 2025 3.
2.Launch and history
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GB300 NVL72 is the rack-scale twin of B300: the same Blackwell Ultra memory refresh, but sold as a complete 72-GPU cabinet with NVIDIA’s own Grace CPUs built in, rather than a board that a customer installs into their own server.
Deep diveThe technical detail
Announced 18 March 2025 alongside B300 1; DGX GB300 availability was described as expected “later this year” (2025) in the same-day SuperPOD release 4. Real deployments followed quickly: CoreWeave with Dell in July 2025 3, and Microsoft Azure’s NDv6 GB300 cluster with OpenAI in October 2025 2.
3.What’s inside it
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Structurally identical to GB200 NVL72 — 72 GPUs, 36 CPUs, connected by NVLink — but with 50% more memory per GPU and faster networking 5.
Deep diveThe technical detail
GB300 NVL72 keeps the same 72-GPU/36-CPU topology as GB200 NVL72 5. What changes: total rack GPU memory rises to roughly 20TB (up from about 13.5TB on GB200, a 1.5x increase), driven by each Blackwell Ultra GPU’s jump to 288GB of HBM3e; CPU memory is 17TB of LPDDR5X at 14 TB/s, for 37TB of combined fast memory per rack 52. Grace CPU core count is unchanged from GB200. Networking moves up a generation to ConnectX-8 SuperNICs (800 Gb/s per GPU) and BlueField-3 DPUs, versus GB200’s ConnectX-7 16.
4.Full spec table
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72 Blackwell Ultra GPUs, 36 Grace CPUs, about 20TB of GPU memory and 37TB of combined fast memory per rack, connected by fifth-generation NVLink at up to 130 TB/s 5.
Deep diveThe technical detail
| Spec | GB300 NVL72 (per rack) |
|---|
| GPUs | 72x Blackwell Ultra |
|---|
| CPUs | 36x Grace (Arm Neoverse V2) |
|---|
| GPU memory | ~20TB HBM3e, up to 576 TB/s aggregate bandwidth |
|---|
| CPU memory | 17TB LPDDR5X, 14 TB/s |
|---|
| Total fast memory | 37TB |
|---|
| FP4 Tensor (dense) | 1,080 PFLOPS |
|---|
| FP8/FP6 Tensor | 720 PFLOPS |
|---|
| NVLink (5th gen) | 130 TB/s aggregate per rack |
|---|
| Networking | 72x ConnectX-8 (800 Gb/s each), 18x BlueField-3, 9x NVLink switches |
|---|
Figures per NVIDIA’s own GB300 NVL72 and DGX GB300 pages 56; corroborated by CoreWeave’s own deployment post, which independently cites “21TB of GPU memory per rack, 1.5x more than GB200 NVL72” 3. NVIDIA’s own pages have shown more than one FP4-sparse figure for this rack in different places; this table uses the dense figure from the DGX GB300 spec sheet as the more consistently reproducible number.
5.Where it’s made
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The Blackwell Ultra GPUs inside GB300 are made by TSMC on the same custom 4NP process used for B300. NVIDIA does not state a fab or process for the Grace CPU in its GB300 materials.
Deep diveThe technical detail
NVIDIA’s Blackwell architecture material names TSMC and the custom 4NP node for the GPU die shared by B300 and GB300. Neither NVIDIA nor TSMC discloses which fab site produces the wafers, and GB300’s own release material does not restate Grace’s foundry for this generation, so this page does not state one.
6.Which systems use it
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Sold as the GB300 NVL72 rack and DGX GB300 system. Microsoft Azure and CoreWeave have both announced production deployments; Wistron is named as a manufacturing partner 235.
Deep diveThe technical detail
Microsoft Azure’s NDv6 GB300 VM series powers the first production-scale GB300 NVL72 cluster, built for OpenAI at over 4,600 GPUs 2. CoreWeave’s deployment was built with Dell Technologies for rack integration, with Switch and Vertiv as infrastructure partners and Moonvalley as an early customer 3. NVIDIA names Wistron’s Texas facility as a manufacturing partner for Grace Blackwell Ultra systems, and Equinix as the first provider of a managed “Instant AI Factory” service built on this generation across 45 markets 54. Broader OEM partners named for the platform include Cisco, Dell, HPE, Lenovo and Supermicro; cloud partners include AWS, Google Cloud, Azure and Oracle Cloud 1.
7.Official pricing
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No official GB300 NVL72 price has been published anywhere this page could verify. CoreWeave lists it as “Contact sales” rather than a published rate 7.
Deep diveThe technical detail
CoreWeave’s official pricing page lists GB300 NVL72 as “Contact sales,” with no per-hour or per-rack figure disclosed 7. No published GB300 pricing was found on AWS, Google Cloud or Azure’s own pricing pages; Azure’s NDv6 GB300 announcement discusses capability, not cost 2. As of this check, no official or primary-source GB300 price exists anywhere publicly — this page states that plainly rather than estimating one.
9.What came before, what came next
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Came before: GB200 NVL72, announced March 2024. Came after: Vera Rubin NVL72, officially announced 5 January 2026 at CES 9.
Deep diveThe technical detail
GB300 NVL72 succeeds GB200 NVL72, keeping the same 72-GPU rack topology while upgrading memory and networking. NVIDIA’s own newsroom names Vera Rubin NVL72 — pairing NVIDIA’s next-gen Vera CPU with its Rubin GPU — as the platform that succeeds Grace Blackwell, expected in the second half of 2026 9.
10.Hidden in plain sight
SimpleStart here
GB300 NVL72 is marketed on the same headline count as GB200 NVL72 — still “72 GPUs, 36 CPUs.” The generational leap is almost entirely a memory and networking refresh, not a new rack design.
Deep diveThe technical detail
Because the rack topology, NVLink domain size and CPU core count carry over unchanged from GB200 NVL72, and only the GPU memory (up 50%, from 192GB to 288GB per GPU) and networking generation actually changed, customers already running GB200 NVL72 infrastructure could adopt GB300 largely as a drop-in upgrade rather than a new rack architecture — which is exactly why CoreWeave and Microsoft Azure were each able to stand up “first” GB300 NVL72 deployments within months of their GB200 rollouts 32.