You can tell these guys know nothing about LLMs or how they’re provided. I love how they show OpenRouter’s graph of token usage as if it speaks for usage across the board. DeepSeek looks like the king because people who use Anthropic and OpenAI use them on either a direct basis or AWS Bedrock …

And the bar chart for token costs, really? As if that’s information? Their sources are the API docs ffs. If they had at least modeled something to estimate token costs that would be interesting, but showing the public prices and calling it research is dumb.

This seems healthy to me. A market where returns are less dependent on seven mega-cap names is probably more stable, not less. If earnings growth broadens out and capital starts flowing back toward quality and free cash flow outside the obvious AI winners, that should reduce concentration risk and make the whole market less fragile.

Historically stocks that had a good run then tended to underperform:

> […] Since 1926, the median ten-year return on individual U.S. stocks relative to the broad equity market is –7.9%, underperforming by 0.82% per year. For stocks that have been among the top 20% performers over the previous five years, the median ten-year market-adjusted return falls to –17.8%, underperforming by 1.94% per year. Since the end of World War II, the median ten-year market-adjusted return of recent winners has been negative for 93% of the time. The case for diversifying concentrated positions in individual stocks, particularly in recent market winners, is even stronger than most investors realize.

* https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4541122

On slide 6, they list the Mag7 stocks (not defined in a foreword), but on slide 8 they list the free cash flow (FCF) of a somewhat different set of companies. Why not stick to the Mag7 FCF only? It muddies the waters.

It is less that the Mag 7 is starting to underperform and more that a market correction is likely and coming very soon.

I guess "nothing lasts forever".

This feels like telecom "massive demand, bad returns".

If a good enough model can be swapped in every few months, the value moves away from the model and toward cheap inference. That is great for users, but not always great for returns on huge capex.

I like that the invisible hand of market is slapping the Mag-7 for capex which is the only way to discipline them. Investors are waking up to say: hey, you are spending all your profits on data-centers, where is the return for me ? But, it surprises me that there are vast pools of capital which we collectively call the "market" that makes these calculations, or maybe a simpler causal explanation is the missing stock repurchase bid. At some point, one of the hyperscalers (msft ?) will break from the pack and announce reductions to capex and increase stock repurchases to stem the decline.

6 months ago when Mag7 was overperforming everyone was worried about it being too high a fraction of the S&P500.

See also:

https://finance.yahoo.com/markets/article/magnificent-7-stoc...

> The once high-flying "Magnificent Seven" are looking more like the Dreadful Seven.

> The why: Wall Street is growing increasingly impatient with Big Tech's astronomical capital expenditures on artificial intelligence, projected to balloon 70% to exceed $700 billion this year.

they are building new narritaves with made up BS name like mag 7 this, that. it used to be faang BS but they updated so lower IQ folks gets into new narratives. Marketing dep. and fin. engineering working together. Another older one was ZIRP that, ZIRP this and you see lower and avg. IQ folks talk about it along with lots of bots. ZIRP bots stopped so MAG whatever bots can take over.

Waiting for next game, bets are open, any new names? O A S I S? upcoming IPOs and new names needed so they can exit scam

What has been the best way to determine return on the AI specific capex for hyperscalers?

I would naively expect Microsoft’s to be the highest since they are probably mainly just selling access to their capex through cloud since they aren’t seriously pursuing frontier AI, I’d imagine Google to be in the middle (selling TPUs, general cloud GPUs, Gemini, revenue lift on ads from better AI) but also spending heavily on infra to compete with OAI/ Anthropic, and then Meta to be on the low end since they are likely getting serious revenue lift from AI but not monetizing their models by API.

Planned Capex for 2026:

Amazon $200B

MS $190B

Alphabet $175B-$185B

Meta $115B-135B

OMG - ridiculous to evaluate it based on the last 3 mo.

I am invested in some of the companies that are downstream of the capital expenditures of Big Tech (e.g., COHR), so I have nothing to complain about.

I am really struggling to see what's the investment thesis behind Google valuation increasing 2x in response to AI, though. Assuming no magical AGI singularity, by the end of the day, they're still selling the same services, but the services have gotten more expensive for them to provide. Everyone was already using Google Search, but now, provisioning AI summaries on top of requires more compute. Everyone was already using Google Docs and Meet, but now, AI features cost Google more. Etc, etc.

The only place where they stand to make money is selling AI compute to enterprises. But with the current supply-chain challenges, the margins there are probably getting thinner.

Apollo should be smart enough to know that you can't draw any conclusions from 1 month of market data (especially when there was a big, relevant IPO).

Nothing wrong, necessarily, but Tesla doesn’t belong to that seven they never have.

Markets are obviously, rationally, not happy about the overspending.

But what gives me pause is that a some of the mag 7 (think Meta) could change their mind on AI build-out tomorrow, and 1-year from now have the same amazing free cash flow they always did.

This is probably a hot take and I am by no means a financial expert and this is probably quite wrong. I personally think that attempting to value these companies using the same methodology as the history of all American companies is fundamentally wrong. Sure, some mom and pop small local regional business that overperformed is probably more likely to underperform. But when it comes to big tech companies, these companies are operating a data and capital flywheel that doesn't easily just slow down. I mean, you look at the history of these computer tech companies, especially software companies. They really haven't slowed down. Like, look at Microsoft. It's just been growing from the very beginning, pretty much.

While I agree with other comments indicating that the headline is drawing on a small period of data, other data in the deck is pretty compelling.

Page 25 "The number of data centers in the US" gives an interesting insight as to the magnitude of the data center boom. 60% more data centers are being planned or are under construction. This might actually be underselling it in dollar amount, as I believe the average data center size under construction is larger than the average data center already constructed.

Page 27 "Cyclically adjusted P/E ratio near all-time highs" is certainly concerning and points to a near term correction.

The dumps on memory/hardware stocks when these companies scale back purchasing is going to make Trump's shitcoins look sovereign bonds

-signed a bitter somebody that had to buy a new SD card for my camera last week.

Hyperscaler free cash flow chart is interesting, but why does it omit Apple?

This is like a straightforward Red Queens Race story, isn't it?