I keep meaning to try Claude Code, but I can't seem to run out of limits on Codex on regular pro plan.

Meanwhile all my friends on Claude Code are fighting the token limits every few hours.

I even switched to using extra high for easy medium level script tasks as a test and besides taking longer there was not much reduction in the token allowance.

I generally write a detailed spec before plan then possibly iterate a bit before implementation. Not sure what I am doing "wrong".

The timing of these price cut discussions says to me OpenAI has no imminent release that will be edging out Mythos/Fable.

If so the question becomes when can they do so, or is this possibly a turning point where Anthropic keeps the crown to themselves for the foreseeable future.

I am curious how many on HN have manually configured their copilot install with a custom OAI token for 5.4/5.5. In my experience, the performance difference over the built in subscription models is immense. This setup tends to solve the problem so quickly and reliably that any desire to have it run while I'm asleep seems absolutely ridiculous. The performance is constant throughout the day and week.

I think what might be happening is that we are chasing the cost optimization rabbit a little bit too hard. Capability is weird dimension to quantify. A weaker model is not weaker in a linear way. It's usually this incredibly tall brick wall of a discrete go/no-go. If the model can't do the task, it doesn't matter how cheap the tokens are. Something approaching the inverse is also largely true.

Focus on the capability (is this giving my customer what they want) instead of the cost, and you will likely find that the cost never reaches a threshold where you even begin to worry about it. Starting from a position of cost optimization tends to spiral into a dark place.

[1] https://www.theverge.com/report/947575/microsoft-claude-fabl...

Reality is Fable is x2 price increase against previous.

GPT5.5 is x2 price increase against previous. And after the last week reset, codex is hungry for your sub allowance.

Everybody can see that the massive raises are not matching the revenue, at all.

It's a surprising headline. Yes it does make sense to cut the price to gain market share, but it also make sense to keep it at a sustainable level, which seems to not have been reached yet.

I'm doing model training and architecture dev all day. often running loops to monitor training status or executing spec and E2E tests.

I really hope token costs come down.

It would be awesome if OpenAI could double the usage allowance for the Pro subscription.

I am not complaining, I like my investor subsidised tokens, I don't see what these companies see as their end goal when it's becoming more and more possible to run a competent LLM locally(even with today's RAM prices).

I am surprised that there is no Claude or ChatGPT machine that I could buy, I feel like they should be opening up that model, but I guess subscriptions look better on balance sheets.

I completely don’t understand Anthropic’s pricing where you have to pay a monthly fee to access their crappy models and pay per use for access to their top model. If you’re going to go pay per use it should be actually pay per use.

Right now OpenAI is looking like the one setup to fail here. They have lost momentum big time and are looking incredibly vunerable.

Think about where any of them will be in 20 years

On device AI?

Maybe the better comparison is Uber? I.e. a commoditised product (taxis on an app), burning money to directly subsidise and gain market share. I always thought it was utterly insane and a waste of money... But you'd be hard pressed to have not made money on Uber.

This is my understanding anyway. A LLM-generated summary suggests that anyone who invested pre-IPO got at least 8-10% annually compounded. Even Series G investors made 2.3x since then. It's not an Eldorado and has to make up for all the losers in the VC portfolio but it's money made, not a smouldering crater of losses.

And after going public, return from IPO is 9.4% compounded. Price is 40% below all time high in October 25 but hey that's a harsh criterion for a long term investment.

The reason why I think it's a good point of comparison is that there's no moat, plenty of competition, heavily subsidised for years by literally burning cash, now seemingly profitable and a reasonably sane PE ratio of 17.

Of course one difference is that a major cost item for LLM companies is building genuinely new, cutting edge engineering/science products whereas for Uber, I never understood why they need the 1000s of technical staff to deliver a taxi app.

I don't know about the ins and outs of the business models of either LLM providers or Uber but keen to hear from people who have insights.

That way you will loose money even faster and we can finally get ridd of this nonsense even sooner.

Claude actually works - unless OpenAI can do that it would make no difference if it was free.

It works unbelievably well actually - it’s truly amazing.

More than happy to watch them lose the global consumer market while they compete with Palantir for DoD contracts.