Big Tech’s AI revenue is accelerating, but free cash flow is moving sharply in the opposite direction. Across Google, Microsoft, Meta and Amazon, capex is rising much faster than operating cash flow as Big Tech races to build out AI infrastructure. Notably, the Big Tech company spending the most on capex in 2026 already turned free cash flow negative, and our estimates suggest it may not be alone by year-end.

The most pronounced difference between 2026’s tech rally compared to rallies in the past is which companies have been left out of it. The names most associated with the AI trade have hardly participated. Google leads Big Tech with returns of 18.7% YTD, followed by Amazon at 10.5% and Meta at 3.4%. Meanwhile, Microsoft has fallen 17.8%. What is most shocking is how much Big Tech has lagged in dollar terms. The combined market cap of these four firms rose just $426 billion this year to $11.93 trillion, just 3.7%. Compare this to Micron, a single supplier to the AI buildout, which alone added approximately $700 billion to its market cap in 2026.

This is Part 2 of our two-part series on AI inference economics. In Part 1 — Why Nvidia's Next AI Battle Is About Tokens per Watt, we laid out why tokens per watt has become the defining metric for inference profitability. Now, we turn from the why to the how and the who. Two architectural paths are competing to solve the KV cache bottleneck: Nvidia's proprietary CMX platform and the open, vendor-agnostic CXL standard. Although they tackle the same problem, each approach points to different sets of beneficiaries. 

As hyperscalers move from building AI infrastructure to monetizing it, tokens per watt helps to reflect if revenue is scaling and if profitability is improving. Offload engines can increase tokens per watt by improving utilization and by increasing the amount of inference revenue generated from the same power footprint.

Over the past 10 months, memory chip stocks have gone from being solid beneficiaries of the AI boom to capturing a massively outsized piece of the return pie. The inflection in Micron’s performance demonstrates this. From the beginning of 2025 to the end of August 2025, Micron added around $36 billion to its market capitalization, rising to $133 billion for a strong 37% gain. Since then, returns have exploded, with Micron soaring more than 900% from August 2025, and up over 1600% since the April 2025 low.

On February 28th, the U.S. went to war with Iran, and the market was handed the kind of shock it hasn't contended with for years. The conflict set off a chain reaction across the region: an ongoing supply disruption in essential commodities, a 30-year Treasury yield pushed to 5.2%, and a CPI print of 4.2%, more than double the Fed's target. By most measures, this was the most uncertain backdrop since COVID.

Neoclouds are one of the more hotly debated AI business models, with CoreWeave and Nebius being the two most widely recognized names. These companies have seen their sales, backlog, and share prices soar. Yet, supporting their growth is extremely expensive, and neoclouds do not have the same cash nor operating cash flow profiles of Big Tech. This is leading neoclouds to employ unique and circular financing structures, raising some red flags.

CPUs have gone from an afterthought to becoming the AI trade’s next great bottleneck – and with AMD, Nvidia, Arm and Intel circling a market that is doubling nearly overnight, the only question left is which company walks away with the lion’s share.