Megaport raises A$827M to build distributed AI cloud for inference

Megaport spent the better part of a decade as a company that simply connected customers to other people’s clouds. On Wednesday, it announced plans to become a cloud provider itself. The Australian networking firm has secured four new AI infrastructure contracts valued at a combined A$458.9M (roughly $329M) and launched a fully underwritten entitlement offer to raise A$827.3M (about $594M), as disclosed in its regulatory filing. The capital will fund a strategic pivot from network plumbing to high-performance compute.

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

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

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

The bet is fundamentally geographic. Most GPU capacity today is concentrated in a handful of massive data centres optimized for training the largest AI models. Megaport is targeting the other half of the AI workload: inference, the process of running a trained model to answer a query, which benefits significantly from being close to the end user.

Its pitch is that a distributed network of smaller GPU pools, spread across the data centres it already connects, fits inference better than centralized mega-campuses. This approach 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. Serving rewards proximity and distribution.

Megaport already owns the network linking the locations where that compute would live, giving it 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.