Industry Analysis · XiaoHu Explains

a16z Report: Neoclouds Are Raking In Capital—Will Horizontal SaaS Disappear?

Across 16 charts, a16z examines Neocloud infrastructure, horizontal SaaS, enterprise Token usage, and the talent race among frontier AI labs—and asks how massive AI spending turns into durable returns.

One-minute overview

Neoclouds are growing at exceptional speed, but depreciation, financing costs, utilization, and customer concentration determine whether that growth becomes durable cash flow.
AI is not erasing SaaS evenly: products with proprietary context, trust, or AI-created demand have a stronger position than generic tools built mainly around seats and interfaces.
Cheaper Tokens do not guarantee a smaller bill. Routing can lower cost per task while lower prices unlock more workloads and expand total usage.
High compensation can attract scarce AI talent, but salary and hiring-flow charts cannot prove culture, research quality, or a lasting organizational moat.

a16z Puts Four Battlegrounds on the Same Ledger

a16z's latest weekly chart report uses 16 charts to examine four battlegrounds: Neocloud compute providers, horizontal SaaS, enterprise Token usage, and the competition for talent among AI labs. They may look unrelated, but all record the same transition: AI capital is moving from "believing in the future" to "checking the books."

That does not mean the four sectors can be measured with the same ruler. Neoclouds must be judged by whether heavy assets earn their cost back; SaaS by whether workflow value is being redistributed; Tokens by both unit price and volume; and talent data can show only compensation and movement. The shared question is merely a map: the spending has happened, and now we must ask how it becomes revenue, efficiency, and durable advantage.

The most important investment, and the one that needs to be explained clearly first, is the computing infrastructure.

What exactly is Neocloud? Don’t rush to see growth yet

01 · Let’s look at the most important sum of money first

Suppose a AI company wants to train a model. It requires not just a batch of GPU, but also enough power, a data center that can put down the machines and continuously dissipate heat, a high-speed network connecting thousands of cards, and an operation and maintenance team to make the entire system run stably. Of course, it can build it from scratch, or it can directly rent a set of computing power that is already ready for construction from a company like JIEDU PROTECTAEND.

**Neocloud is the latter business. ** It is not a trendy nickname for "small AI", but a new group of cloud vendors that organize their capabilities around AI and high-performance computing. They package GPU, power supply, computer room, network and operation and maintenance into usable computing power, and then sell it to model companies and enterprises. CoreWeave, Nebius, Applied Digital, IREN are the companies focused on in this set of data. This name is not a strict regulatory or accounting classification, but a common label given by the market to a group of similar companies.

Drop the unfamiliar words to the ground first

Traditional cloud sells "general computing", Neocloud first solves "GPU production capacity"

AWS, Azure and Google Cloud provide complete services such as database, storage, network and general computing; Neocloud has a narrower starting point and first solves the most urgent needs of GPU, power and high-density computer rooms. Narrow means that it can expand faster around an explosive demand; it also means that revenue is more easily tied to a few large customers, a few chip suppliers and a hardware cycle.

Neocloud is not the first time that old infrastructure has been turned into a starting point for new industries. There have been at least three similar asset revaluations in history: railroad companies converted land rights along the routes into communication lines; natural gas companies turned idle pipelines into fiber optic channels; and cable TV companies upgraded coaxial cables into broadband networks.

The underlying assets existed first, then new communication needs broke out, and those who could complete the transformation and operation turned it into another business.

Four asset revaluations share the same structure

The underlying asset exists first; demand surges later. The scarce capability is not owning a particular asset, but converting and operating it as new productive capacity.

railwayLand rights along the routeContinuous right-of-way already exists

Laying communication linesReuse routes that would be difficult to reacquire

communication networkSprint

natural gasunderground pipesThere is a cross-region physical channel

Fiber ChannelConvert idle capacity into communications infrastructure

communication networkWilTel / WorldCom

cable TVcoaxial cableAlready connected to a large number of families

Upgrade two-way broadbandReuse the last mile network

broadband networkComcast / Charter

Mining farms and data centersPower, land, and facilitiesCapable of carrying high-density computing

Supplement GPU, Networking and SchedulingTransform existing conditions into deliverable computing power

AI INFRASTRUCTURENeocloud

This diagram explains only why Neoclouds can start faster. GPU replacement cycles, financing costs, and customer concentration differ from legacy communications assets, so the analogy does not prove long-term success.

This historical analogy explains why they took off so quickly, but it does not prove that they will become the next generation of large clouds. Railway rights-of-way and underground pipelines can be used for decades, but GPU will quickly depreciate after the emergence of new generations of chips; communication networks face a wide range of customers, and Neocloud's early revenue may also be highly dependent on a few large customers. The analogy should stop here, and we must look at the data next.

Look at Neocloud, don’t just focus on one curve

01 · Speed ledgerThe growth curve is really steepYoung Neoclouds are growing revenue even faster than the major clouds did in their early years.

02 · Scale ledgerThe absolute size is still smallHigh growth starts from a small base, but there is still a huge gap between AWS, Azure and Google Cloud.

03 · Valuation ledgerThe market has paid in advanceAfter the high revenue multiple is expected to be written in, the growth is slightly less than expected, and the valuation may shrink first.

04 · Cost ledgerRevenue does not equal free cash flowChips, electricity, facilities, depreciation, and interest determine how much cash remains from each dollar of revenue.

All four ledgers must work together: running fast does not mean the business is already large, and high revenue does not mean cash is already staying behind.

Every core judgment is visible without clicking. The next six charts provide the underlying evidence and definitions.

Start with speed. Figure one compares the early revenue trajectories of CoreWeave, Nebius, and Applied Digital with the quarterly revenue paths of Azure, AWS, and Google Cloud after their respective launches. To make the comparison fairer, the horizontal axis is not calendar time but "quarters since each cloud business launched." In about 25 quarters, CoreWeave reached roughly $2.6 billion in quarterly revenue; early AWS did not reach a similar level until around quarter 40.

This is indeed a rare growth curve, but it also depends on how the graph is drawn. The solid line is realized data, the dashed line contains estimates; inverse values are also available for early large clouds. Therefore, it can answer "who ran steeper in the early days" and cannot be used as an audit of the same caliber, nor can the dotted line be regarded as the future that has already happened.

Data graphs · Click on any graph to see a larger version

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