BREAKING: Today's Frontier AI companies will never exceed the AI capability frontier again

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BREAKING: Today's Frontier AI companies will never exceed the AI capability frontier again<br>Doesn't matter if you care about AI speed, AI capability, or AI cost... centralized AI has lost the lead and cannot regain it... and the free market is starting to move<br>Jun 14, 2026

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Everyone I’ve talked to in AI has always assumed that the future of AI is bigger models held by a smaller number of players. I get it… they can see a very strong trend over the last 10 years, and they bring that view to every AI regulation, investor strategy, VC pitchdeck, and futurist prediction.<br>But they couldn’t be more wrong, and now the numbers are showing it. Networks of smaller AI models are outperforming every frontier AI system (Fable/Mythos included) on speed, accuracy, and cost.<br>Thanks for reading Andrew’s Substack! Subscribe for free to receive new posts and support my work.

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IBM, the US Government, Bell Telephone, Bell Labs , and everyone else was wrong in the 1960s about the mainframe computer… and everyone is wrong today about centralized AI. The future is a network of neural networks . It’s a PC+Internet of AI. The future is not open or closed source AI… it’s network-source AI.<br>Part 1: the economic game is over

If “The AI Race” is a race to maximize AI capability/speed and minimize cost… and if AI users fundamentally either look for the MAX capability possible… OR they follow the best deal (capability+speed) at the lowest price (cost), then the centralized AI race is over, and decentralized AI has definitively won. To see why, look at each one by one.<br>Capability

Networks of neural networks are now faster, cheaper, and more capable than any Frontier AI system. The game is over. I’ve personally tested this myself , and it’s also bearing out in multiple corners of the internet. Here’s one that dropped today:

image from website<br>Not only does it show how to exceed the accuracy of the best models, it beats the best models at half the price. I personally used this same technique 6 months ago. At the time, here were scores of frontier AI models on the multiple-choice section of humanity’s last exam.

And… a differentially private combination of them reached into the low 50s!

Here’s a Stanford student doing it and launching a startup.

Bottom line… if you want the most capable AI system in the world … from TODAY onwards… you can only get that from a routed/weighted ensemble of weaker AI models. No single frontier AI system will ever achieve the capability frontier ever again because of how the scaling laws / ensembles work (more on that below).<br>Speed

Open source models are simply faster, in part because the people who host them are only in the business of making money by delivering crazy fast/cheap results. Don’t believe me? OpenRouter has independent ratings (note: this is different than the corporate sales pitch by these companies… this is what actually happens in practice).

Cost

Open source models are offered at the cost of inference (with training being given way for free). Industry-wide, pound for pound, they’re cheaper for the same level of intelligence… but previously they there was a GAP where centralized AI was the only way to achieve the highest levels of intelligence:

But now this chart is being overwritten… because a different kind of decentralized AI is emerging… At the time of writing, the cheapest way to get Fable/Mythos level performance… is NO LONGER FABLE/MYTHOS… it’s basically any permutation of GPT and Opus (including Opus with itself!).

And here’s what they left out of this chart… if they added even more models… the capability would keep going up (I know this because I did these experiments myself 6 months ago). For example… you might be questioning this list above because it mostly features closed source models… but the latest Kimi model just dropped TODAY… which will undoubtedly combine with Opus or GPT-5.5 to be Fable-level while being even cheaper. Why do I know this? Because Kimi K2.7 is better than any of the models OpenRouter ensembled except Fable itself.

new kimi model benchmark<br>The playbook is to take any frontier AI model, find the next-best (cheaper) frontier AI model, ensemble it with the leading open source model, and now you’ve got a cheaper version of the frontier. And that keeps on recursing. Larger ensemble, better router, better accuracy, even lower cost.<br>So called “Frontier AI Companies” will never again achieve the accuracy/cost/speed frontier. The frontier is now owned by the network of leading models and companies.<br>Why Can’t Centralized AI Respond: The Hydra Effect

The problem for today’s centralized AI companies is the same one that mainframe computing companies had in the latter 20th century. Once the internet started linking together mainframe computers over telephone lines… the network of mainframe computers was always stronger...