The profit comes from the enterprise customers who have to pay for usage at API rates. Not the subsidized subscriptions, which both OpenAI have designed to be unavailable for large enterprises by withholding IAM and auditing features they need except on the usage based entperise plans.

As an individual I'm still paying for a ChatGPT Plus plan since $20/mo gives me a lot of value and I use many multiples of $20 at API rates per month. But in terms of capabilities, I am entirely satisfied when using my Opencode Go plan with open models like Deepseek Flash/Pro, Kimi and MiMo.

At this point keeping my ChatGPT subscription isn't because of a significant capability gap compared to open models. It's 90% about the value of the subscription priced well below API rates (10% the fun of trying latest models).

If OpenAI/Anthropic dropped their cheap subscriptions or drastically undermined the value proposition I'd be happy using open models exclusively and currently barely notice a difference switching back and forth for the vast majority of tasks.

I'm expecting the subs to increasingly provide less value as the US labs IPO and follow the SV pattern of moving from marketshare capture mode to profit extraction mode. Thankfully I'm already comfortable using OpenCode with open models and avoid lock-in to any specific harness so would be a very soft landing.

Openrouter stats seem to indicate that there is a lot of demand for ‘good enough at a good price.’ After all, not everyone is decompiling PS5 games. In fact, most people are just speedrunning notetaking apps in JavaScript frameworks.

Have you considered you are reading comments from different people?

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Borrowing money is not the only way to go into debt. They reportedly made binding and non-cancelable commitments. Once those commitments come due then they will be indebted to their counterparties until they pay up or the courts sort it out.

This is comparable to how, if I sign a 12 month non-cancelable lease and then don’t pay the rent, I will be in debt to my landlord.

Yes.

LLMs? No. LLM companies? Yes. It's just math, data centers, and mass copyright infringement. The only scarcity is Nvidia, who just passed Apple in market cap, somewhat proving your point but not in the way you meant it.

Maybe not, but it is probably less likely that Apple will face stiff competition from freely available alternatives, given that AOSP has been a thing for the iPhone’s entire lifespan and nonproprietary Android phones have failed to capture significant market share.

I don't think we have seen an Apple of AI yet. I wouldn't describe the frontier that way, would you?

Goverment bailing they out will be using people tax to rescue the companies that absorbed most of the 801k money so they can get people out of work... it's the ultimate slap to the face... I would strongly resist this, I would vote if they implode to give to whoever owned shares via 801k their money, to people and let them (openai, anthropic, et al) eat shit... I would love to buy one of those gpus to run an open model at discount price...

My reason is their revenue chart is flattening.

https://techstartups.com/2026/10/15/anthropics-q3-revenue-hi...

I am technically not saying that. I am taking off from the parent comment and speculating.

Their data from September is leaked via IPO preview, and October is not yet complete, so how can someone even project that?

// I am a techie, not a finance guy, so apart from public chatter, no inside knowledge.

And I do feel their IPO is being rushed before anyone has enough information to make up their mind. The VCs or private equity have given them a lot of money and want to cash out. When the revenue does slow down, any investor should pause to take a look at whether they can right the ship, or has the landscape itself changed.

I don't have the numbers in front of me but could have sworn I had seen quarterly revenue growth rates dropping drastically over the last year or so. Still a strong growth rate, but much lower than prior growth rates.

Edit: Data because silent down votes are useless, Anthropic Q2 2026 grew 147% while Q3 grew 45%

It may solve the problem of anthropic and open ai going out of business with all major consequences that would have for the rest of the US.

“Ban open weight models” Lol how. How do you even prove a model that I’m hosting is open weights?

Banning open weight models in the US would provide the rest of the world with a huge business advantage since these models are much more cost-effective than US models.

Presumably, legally operating companies aren't the dominant threat though. So banning open weight models doesn't solve anything.

> If you are a legally operating company in the US just saying it's banned is enough, the threat of enforcement is enough pressure.

Is there precedent for the US actually "banning" software? I know for example the Kaspersky ban and tiktok ban, but both of those were either banning the sales or banning the service. IIRC neither made the actual software illegal.

What is an example of a specific software being illegal to possess? What is an example of a specific software being illegal to use if it is not used to break other laws (copyright, etc.) or talks to banned service providers?

Closest thing I can think of is restricting the export of cryptography in the 90's, but that was not even close to what you are suggesting.

Thanks for the suggestion, but that’s not a fit for me.

I’m writing my own harness to learn. And I’m writing it in zig.

But, I’ll absolutely add maki.sh to my reading list. So, that’s a win.

> "What kind of hardware... "

At home, I mostly use openrouter.

A few bucks will realistically last you forever. I also bought a DGX Spark at launch. I've learned a ton. but it's not usually my daily driver. I do run overnight tasks on it, like "read this book and write up notes on each chapter..."

In retrospect, given the dirt cheap prices of apis and or renting hardware, buying hardware for inference was likely a mistake (but not enough of a mistake to sell it now).

Take a look at the docs for https://github.com/niko1221/strata for some ideas, particularly https://github.com/Niko1221/Strata/blob/main/docs/MODELS.md#... .

Schaefer says they write their own harness, not necessarily training or running a local model.