Will LLMs be Commoditized?

TL; DR: Don't sleep on $GOOGL’s "free tier" playbook

December 26, 2025

Will LLMs be Commoditized?

By @LazyTrader 22.12.2025

TL; DR: Don't sleep on $GOOGL’s "free tier" playbook sucking out all the economic oxygen amid the current LLM wars.

Will LLMs commoditize? To answer this core debate, it may be helpful to consider the LLM wars for Consumer AI and Enterprise AI separately:

LLM Wars: Consumer Side

High-end AI will not automatically mean paid subscriptions if "good enough" free options exist—remember AOL charging for internet access before the free web crushed it?

What’s potentially different this time, is that frontier LLMs are brutally difficult to build; Meta has poured billions in and still lags the leaders. I suspect frontier models with differentiated capabilities, that are solving real consumer pain points, will be valuable.

That said, expect a perpetual free tier from Google and open-source models, draining economics from pure-play AI firms. Google's mastered this: Gmail, Android, Maps—all "free" to hook users, then monetize via ecosystem lock-in.

Prediction: Consumer AI = General Purpose (GP) AI assistant + on-demand specialist AI apps for niche tasks. The GP with the most users wins big via flywheel: More users lead to more developers connecting specialist AI apps to its ecosystem, which leads to better task execution and stickier users.

Google's edge here? Their track record of killer free products to grab market share. Free GP AI locks in the masses, pulls in app developers, and Google takes a platform cut—like Uber (matching riders/drivers) or Amazon (with sellers/buyers).

Risk 1: LLMs hot swapping? Competition between leading models like GPT and Gemini could encourage consumers to switch between the "best-for-task" options, especially with interoperable APIs allowing specialist AI apps to integrate across multiple AI platforms. This might reduce user loyalty to any single GP agent.

Mitigation: Consumer habits can be remarkably sticky—consider how Google Search remains dominant even when Microsoft Bing produces similar results. Similarly, while some consumers occasionally jump between Uber and Lyft apps, and some drivers work for both, Uber has pulled ahead to a market cap over 20 times that of Lyft. Over time, the winner slowly but surely widens the gap through network effects.

Risk 2: As data center infrastructure scales up—such as with Nvidia's Blackwell GPUs—tokens could become commoditized, potentially diminishing Google's cost advantage from its in-house TPUs.

Mitigation: Over the long term, token costs will likely converge toward the marginal cost of power. However, competitors like OpenAI must pay hyperscalers, who in turn pay Nvidia, introducing layers of middlemen. Google, with its full AI vertical integration, retains a margin advantage even in a commoditized token environment.

LLM Wars: Enterprise Side

Here, it is all about deep sector verticals with proprietary data for moats. Generic LLMs flop without clean data—hallucinations kill deals in high stakes sectors such as healthcare, finance, etc.

Real defensibility: Distribution + data flywheels. For instance, Microsoft can bundle AI into its empire for forced adoption; huge user base = faster feedback loops = superior model improvement cycles.

For startups: Need unique datasets in niches, going deeper than Big Tech ever would. Without capability differentiation or high switching costs, open-source alternatives cap profits.

But perhaps most importantly, enterprises demand more than features—think data and system security, where Microsoft and Google have credibility.

So, on the Enterprise AI side, LLMs hot swapping feels even less likely, given the likelihood of deep sector specialization via proprietary data, and lower reputation risk tolerance for enterprises mean wholesale changes are typically very slow.

OpenAI's Compute Bets and What It Means for the Sector

OpenAI just dropped $1.4 trillion in commitments for data center compute—yes, trillion with a T. They are banking on revenue growth to fund it, which directionally points to hundreds of billions in annual revenues. Even if they hit half that, it is game-changing. And if it is true for them, it has to be directionally spot-on for Google too. No more hand-wringing about Search dying in the AI era—GOOGL's trading at under 30x forward PE, which screams option value for the post-AI world. Compare that to OpenAI's $700B-800B private valuation on just ~$15B-$20B ARR?

Google's advantages? Elite AI research, in-house TPUs/chips, data centers, frontier models (Gemini), apps/products, billions of users/distribution, and a fortress balance sheet with FCF to self-fund. They are the lowest-cost token producer right now—can undercut everyone, price below cost, and dominate. Sure, classic Search (those 10 blue links) is under siege, but Google is simultaneously well positioned to own the AI shift. Oh, and you get Waymo (autonomous driving gold) and YouTube (ad/printing machine) basically for free at this valuation.

Valuation Risk vs. Execution Risk

$GOOGL’s embedded option value in AI makes it a compelling long. OpenAI's massive compute bets signal explosive revenue potential in AI, but Google's vertical integration makes it the real powerhouse at a bargain valuation (vs. Mag 7 peers or OpenAI's private valuations).

Open-source momentum is the wildcard that amplifies LLM commoditization risk for everyone, with open-source fine-tuning tools making custom models cheaper/easier to implement. While Google’s role in the AI era is not guaranteed, execution risk is perhaps somewhat reduced by their track record of shipping really sticky consumer products!

The LLM wars have only just begun. New players could emerge; new AI device form factors or orchestration tools could redefine the entire game. AI could cannibalize Google Search’s ad revenue faster than Gemini could replace it, and regulatory scrutiny might slow Big Tech's dominance further.

Yet, amid these uncertainties, Google is still the incumbent to beat.

History warns: Don’t bet against the house that built the internet as we know it.

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