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.

In April, Google announced it would begin selling its TPUs to select third-party data center operators, which is something the market has anticipated for nearly a decade. The TPU-versus-Nvidia-GPU debate has long fueled both bulls and bears; yet it may finally carry real stakes. Google’s announcement is far from a coincidence—it is driven by several converging factors that make now the right moment to move.

AI networking stock Lumentum is among the key I/O Fund winners in 2026. We allocated heavily to LITE in January—a month before Nvidia backed the company. While most investors couldn’t stomach taking a stake in this stock that soared 339% in 2025, I/O Fund built a 9% position that has since paid off in spades. Overall, in just five brief months, our Lumentum position delivered a return of 135.4%, or 6.8X higher than Nvidia’s 19.9% return since the end of January. For investors new to this name, Lumentum recently received significant validation from the world’s most valuable company—Nvidia—with the dominant force in AI infrastructure investing $2 billion in LITE. However, the importance of this goes far beyond the investment itself. The real story is Lumentum’s central position in Nvidia’s multi-year networking roadmap, and the broader AI market, which is affording Lumentum the opportunity to grow its business several times over.