Megaport raises A$827M to build a distributed AI cloud and chase the inference market

Four new contracts and a big GPU bet turn the Australian networking company into an AI-infrastructure play.


Megaport raises A$827M to build a distributed AI cloud and chase the inference market

Megaport spent a decade as a company you used to connect to other people’s clouds. On Wednesday it announced a plan to become one. The Australian networking firm secured four new AI infrastructure contracts worth a combined A$458.9M (about $329M) and launched a fully underwritten entitlement offer to raise A$827.3M (about $594M), according to its filing. The money funds a pivot from plumbing to compute.

The contracts come first. All four are with US-based technology providers running AI applications, are expected to start in the first half of 2027, and require nearly A$369.5M in capital expenditure, mostly for high-performance Nvidia GPUs alongside network and storage. That is a meaningful commitment for a company of Megaport’s size, and it explains why the raise is so large relative to the business.

What the capital is really buying is the strategy behind the contracts. Megaport says it will build a globally distributed AI inference cloud, anchored by an on-demand GPU pool backed by about A$350M in investment and offered to enterprise customers on both contracted and consumption-based pricing.

The pool is to be deployed across the company’s existing footprint of more than 1,100 connected data centres in 31 countries, with rollout over the next six to nine months.

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The bet is geographic. Most GPU capacity today sits in a handful of enormous data centres optimised for training the largest models. Megaport is targeting the other half of the AI workload: inference, the act of running a trained model to answer a query, which benefits from being close to the user.

Its pitch is that a distributed network of smaller GPU pools, spread across the data centres it already connects, fits inference better than centralised mega-campuses, and slots into the gap between hyperscaler clouds and single-location GPU specialists.

It is a credible reading of where AI infrastructure is heading. As models move from research demos into products embedded in real applications, the economics shift from training to serving, and serving rewards proximity and distribution.

Megaport already owns the network that links the locations where that compute would live, which is a genuine structural advantage if the thesis holds.

The numbers around the raise were briefly muddled across early coverage, which is worth untangling. The four contracts are worth A$458.9M in total contract value; the capital raise is A$827.3M; the GPU pool commitment is about A$350M.

Several headlines collapsed these into a single figure. They are distinct: contract wins, the money to fund them, and the specific compute investment inside that money.

Megaport also tightened its 2026 revenue guidance to A$307M–A$315M and projected combined group pro forma annual recurring revenue of A$662.9M once the compute division is folded in. The shares were halted while the raise was arranged, a standard mechanism for a deal of this scale on the ASX.

The risk is the obvious one for any company spending heavily on Nvidia GPUs on the strength of contracts that begin in 2027: that AI infrastructure demand, and pricing, may look different by the time the hardware is installed and earning.

Megaport is committing capital now against revenue that lands later, in a market moving fast enough that 18 months is a long time. The contracts give it a floor. The inference-cloud ambition is the part that has to compound, and that is the part the A$827M is really betting on.

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