AI Cloud vs Bare Metal vs Colocation
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AI requires fundamentally different infrastructure than general-purpose cloud infrastructure.
Simply put, AI data centers use a higher number of powerful $NVIDIA(NVDA)$ GPUs that eat a lot of electricity, requiring meaningful grid upgrades. Additionally, these GPUs generate more heat than a conventional data center, demanding improved cooling systems. This means that, unfortunately, using existing general-purpose data centers for AI workloads is just not economically viable.
This is why we are witnessing this extreme data center buildout boom!
In a colocation model, a company such as Cipher Digital builds the data center, secures energy, and equips it with cooling, networking, and other equipment. Then they secure a customer who signs a long-term lease agreement of 10+ years and brings their own GPUs to the facility. This model has the lowest value added and thus has the worst economics, generating the lowest price per MW.
Meanwhile, in a bare metal model, the owner of the data center is responsible for fully equipping the facility with all equipment, including GPUs. It then finds a customer who negotiates access to a pre-agreed number of GPUs for a set per-hour rental price. Bare metal customers use their own software to run AI workloads on these GPUs. As the data center operator provides the GPUs, the bare metal model has a higher value added than colocation, and thus has better economics, generating a higher price per MW.
However, the most profitable AI data center model is the AI cloud provider!
In this model, the data center operator provides advanced AI training and inference software. Purpose-built AI training clusters, model hosting, managed inference services, AI APIs, storage, networking, developer support, and more. An AI cloud doesn’t simply rent out space, like colocation, or rent out GPUs like in bare metal. An AI cloud is essentially an AI development, optimization, inference, and deployment partner for AI start-ups and large enterprises.
As revenues are software-driven, this model has the highest value added and thus generates the highest price per MW!
Each of the operating models has its own advantages and disadvantages.
In colocation, the data center operator is essentially a landlord, and such a model can be highly profitable if operated well. The key advantage is that it requires less capital to start, is easier to operate, and generates a more stable and predictable rental income from a small number of key tenants.
A bare metal is similar to colocation. But, if we use the analogy of a rental apartment, colocation is comparable to renting an apartment without any furniture, whilst bare metal is a fully furnished apartment. Meanwhile, an AI cloud could be comparable to a fully serviced apartment, with furniture, maids, a personal chef, nanny, tutor, and chauffeur.
An AI cloud might have the highest margins in theory, but it is also the most difficult model to operate. Companies must employ highly skilled software engineers to build the digital environment that AI start-ups need. This requires a lot of upfront capital and years of research and development. Furthermore, AI clouds must have big sales and customer management teams that manage a large number of small customers.
Most importantly, this area of the industry is highly competitive, filled with highly skilled start-ups, and it is led by Hyperscaler clouds with hundreds of billions of dollars at their disposal, such as $Alphabet(GOOG)$ $Amazon.com(AMZN)$ $Microsoft(MSFT)$.
$NEBIUS(NBIS)$ has chosen a mixed business model, where it provides Bare Metal services to Hyperscalers $Meta Platforms, Inc.(META)$ and Microsoft, while it provides AI Cloud services to others!
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