TL;DR · 30-second read
The Short Version
NVIDIA, the company whose chips power most artificial intelligence work, is teaming up with eight Australian data centre operators to build a large amount of new computing capacity.
The plan could draw up to two gigawatts of electricity by 2027. That is roughly the output of a very large power station, spent on machines that learn from data.
The point is that Australians could build and run these systems at home instead of renting foreign computers. What has not been said: who pays, where the electricity comes from, and who has signed up to use it.
NVIDIA said on September 9, 2026 that it is working with a group of Australian cloud and data centre partners to expand land, power and shell capacity for its DSX artificial intelligence factories, targeting what the company describes as a buildout of up to 2 gigawatts by 2027. The named partners are Firmus, Sharon AI, IREN, Megaport, ResetData, CDC, NEXTDC and AirTrunk.
Under the arrangement described in NVIDIA’s announcement, the partners operate the facilities while NVIDIA supplies the DSX platform, accelerated computing, networking, software and ecosystem support. Sharon AI said it is deploying up to 68,000 NVIDIA graphics processors, and IREN pointed to its 800-megawatt Bundey campus in South Australia as the first place it will apply the DSX reference design. On the demand side, NVIDIA named Heidi and Atlassian as Australian companies building on its Nemotron open models.
Executive Summary
The announcement is best read as a capacity envelope rather than a purchase order. NVIDIA and its partners have described land, power and “shell” capacity, meaning buildings and electrical infrastructure prepared for computing equipment that has not yet been installed. Two gigawatts is the stated ceiling for 2027, not a contracted figure, and the release does not break the total down by site, partner or year.
What is substantiated is the alignment of a whole national ecosystem behind one vendor’s reference architecture. Every significant Australian and Australasian data centre developer of scale appears on the list, alongside newer entrants building graphics-processor clouds. That matters commercially: it standardises the power, cooling and networking specification that Australian AI capacity will be built to, and it makes NVIDIA the arbiter of what qualifies.
What is not substantiated is the economics. No capital cost, financing structure, contracted offtake, grid connection agreement or customer commitment accompanies the capacity figures. Those are the variables that determine whether two gigawatts is a plan or a press release, and they are the ones the participating companies have kept to themselves.
Ceilings, Not Contracts
The phrase doing the most work in this announcement is “up to.” Up to 2 gigawatts by 2027. Up to 68,000 graphics processors at Sharon AI. In infrastructure disclosure, an upper bound is a statement of ambition constrained by permits, power and money, none of which have been detailed here. It is not a criticism of the participants to say so; it is how early-stage capacity announcements are conventionally worded.
Some of the underlying numbers are also pre-existing rather than new. CDC said it operates more than 550 megawatts across Australia and New Zealand with a further 800 megawatts under construction, and IREN’s Bundey campus in South Australia is a 800-megawatt development it was already pursuing. Neither company said how much of that capacity is earmarked for NVIDIA DSX deployments. Readers cannot tell from the announcement how much of the headline 2 gigawatts is incremental to plans already in motion, or how much overlap exists between partners counting the same grid connections.
The more concrete commitment is architectural. NVIDIA is supplying DSX as a full-stack reference design spanning facilities, compute, networking and software, and partners are building to it. That has a real effect regardless of how the gigawatt arithmetic resolves: it sets the density, cooling and interconnect standard that Australian AI capacity will be procured against, and it shortens design cycles for operators who would otherwise engineer each hall from scratch.
Two Gigawatts Meets a Constrained Grid
A gigawatt-scale computing load is an industrial electricity customer of the first rank, comparable to a large smelter or a small city, and it must be connected to a transmission network that was not planned with it in mind. Australia’s grid is in the middle of a generation transition, and large new loads compete for connection studies, network capacity and firm supply. The announcement acknowledges this obliquely, noting that expanding capacity would support “additional power generation projects,” but it names no project, no megawatt of new generation and no timeline.
The cooling detail in the announcement is the most technically specific material in it, and it is where operator differentiation actually lives. CDC described direct liquid-to-chip cooling and what it called zero water advanced cooling on 100% renewable electricity. AirTrunk described direct-to-chip liquid cooling in AI-ready powered shells, meaning buildings with power and cooling delivered but computing equipment still to come. NEXTDC described liquid-cooled, high-density halls interconnected to major clouds. Liquid cooling matters because the current generation of accelerators dissipates more heat per rack than air can economically remove, and water-free designs matter in a country where drought risk is a live planning consideration.
Location strategy is the quiet variable. South Australia, where IREN’s Bundey campus sits, has a high share of wind and solar generation and periods of surplus, which is attractive for a load that can tolerate some siting distance from population centres. Training workloads travel well; inference does not, which is why Megaport’s approach, extending access through its Latitude.sh subsidiary across a software-defined global network, is a different bet on the same demand. Where compute lands in Australia will be decided by transmission and land availability more than by customer preference.
The Fungibility Pitch and Who Carries the Risk
NVIDIA’s Raj Mirpuri framed DSX as making AI factories “more productive, fungible and durable, and a new investable asset class.” That language is aimed squarely at the people who finance data centres. Fungible means the capacity can be re-let to a different customer running a different workload; durable means software upgrades extend the useful life of hardware that would otherwise depreciate on a punishing schedule. Both properties, if they hold, raise the residual value that lenders will underwrite against.
The claim is reasonable in principle and unproven in this context. Whether an accelerator installed in 2026 remains rentable at an economic price in 2032 depends on what competitors ship in between, and no software layer fully insulates an owner from a step change in performance per watt. Investors evaluating IREN, NEXTDC or Megaport on the back of this announcement should note that the depreciation question is precisely what the announcement asserts rather than demonstrates.
Risk allocation is also unstated. The partners operate the facilities; NVIDIA delivers the platform. That division suggests the balance-sheet exposure of building shells and buying accelerators sits with the operators, but the announcement does not describe any purchase commitment, capacity reservation, revenue guarantee or equity participation flowing the other way. In a sector where vendor financing arrangements have become common enough to draw scrutiny, the absence of detail is itself the thing worth watching.
Sovereignty Runs on Open Models
The second half of the announcement is about demand, and it is the part most relevant to buyers. Capacity without applications is a stranded asset, so NVIDIA paired the buildout with named users of its Nemotron open models: Heidi, whose chief technology officer Yu Liu described post-training Nemotron 3 Ultra for clinical reasoning, and Atlassian, which is applying the models to semantic search in its Rovo product. ResetData made the sovereignty case most directly, pitching Australian data residency, meaning customer data that stays under domestic jurisdiction, to government, enterprise and research buyers.
Open models are strategically central to NVIDIA rather than incidental. In an 8-K filed with the Securities and Exchange Commission on September 3, a current report companies use to disclose material events, NVIDIA said it had entered a definitive agreement two days earlier to acquire Hugging Face, the main distribution platform for open-source models and datasets, for roughly $11.9 billion plus an equity retention program of up to about $1.0 billion, with closing expected in the first half of 2027. NVIDIA committed to keeping the platform open, including continuing to support other silicon vendors.
That same filing contains a risk disclosure that bears directly on the sovereign AI thesis. NVIDIA warned that governments may impose new requirements on the development, release, distribution and use of AI models, including open-source ones, and that restrictions on models derived from any region could materially affect its business. Sovereign capacity is often sold as insulation from exactly that kind of policy risk. It is worth being clear that domestic data centres address where data and computation sit, not which models remain legally available to run on them.
Background
Australia has built a substantial data centre industry relative to its population, anchored by operators such as NEXTDC, which is listed on the Australian Securities Exchange, hyperscale developer AirTrunk, and CDC, which serves government and critical infrastructure customers across Australia and New Zealand. Megaport, also Australian-founded, built a global software-defined network that lets customers provision connections between clouds and data centres on demand, and now extends compute through its Latitude.sh subsidiary. IREN began as a bitcoin mining business and has been redirecting its power and land portfolio toward AI data centres, a transition several miners have attempted as accelerated computing outbid hashing for electricity.
The sovereign AI idea, that countries should host the computing capacity their economies and institutions depend on rather than rent it from foreign providers, has been a policy theme for several years. It has produced far more strategy documents than energised megawatts. This announcement is notable because it puts named operators, named sites and a dated ceiling behind the concept in one market, and because it arrives while Australia’s electricity system is simultaneously absorbing a generation transition and a new class of very large industrial loads. Source: NVIDIA Expands AI Infrastructure Capacity in Partnership With Australia’s Data Center Ecosystem — NVIDIA’s September 9, 2026 newsroom release naming Firmus, Sharon AI, IREN, Megaport, ResetData, CDC, NEXTDC and AirTrunk in a buildout of up to 2 gigawatts by 2027. Primary sources: NVIDIA Corporation, Form 8-K filed September 3, 2026, disclosing the definitive agreement to acquire Hugging Face and NVIDIA’s risk disclosure on government restrictions affecting open-source models.Sources