91–100 of 214 posts
Crazy value for money now with the banked resets. At my $COMPANY, we have claude enterprise at API pricing. I've blown through $10k already this month, opting for Opus 4.8 w/ Sonnet 5 agents where possible. On my codex pro plan, I am 5.6 sol'ing my way everyday with the odd ultra mode. Point being my real API usage here must be very unsustainable!
I really wish there was a canonical platform endpoint to programmatically check Codex usage amount and the quota reset times so I could just vibecode an app to alert "hey, your usage just went to 100% so that means OpenAI did a reset" and "hey, your 5-hour usage is at 10%, wrap up what you're doing". The only way to do it now is through shenanigans with the Codex App Server which is not ideal.
Just ask Codex to use its local auth token as a bearer token and send a GET request to it. The response includes "available_count" and "credits[].expires_at". Or script it yourself obviously.
https://chatgpt.com/backend-api/wham/rate-limit-reset-credit...
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They just merged the ChatGPT app and the Codex app into one super app. It is a clever growth hack.
I would expect them to grow faster than 1 million users a day in that case, since chatGPT has almost a billion users. Maybe everyone's just using the web app or mobile?
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> Point being my real API usage here must be very unsustainable! I think it’s funny that everyone anchors to the API pricing as the real cost. Most likely is that their API costs are printing profits. They can sell the subscription plans at a slight loss because it gets more people like you hooked on GPT models at home and suggesting them at work, where the real money is made. I think their subscription plans go most…
Idk, Kimi K3 is not that much cheaper than Opus and it’s probably a smaller model. We’ll know for certain when commodity providers price it, but I expect it to be the same price.
Remember they ~doubled the price going from GLM 5 to GLM 5.2, despite same [1] cost of inference.
[1] GLM 5.2 is actually slightly more efficient, thanks to baked in indexer cache.
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Can anyone explain how you “win” the market of super intelligence? Particularly with open weights models now rivaling the frontier, it seems like a race to the bottom even if the prices don’t yet reflect that.
You hit the nail on the head. It's a race to the bottom.
Now K3 is almost 6x the cost of the original K2 checkpoint, and while the parameter count finally jumped, it's still an extremely sparse MoE and definitely does not cost 6x what the original K2 checkpoint did to host at scale.
Race to the bottom only takes real effect when there's a cap to the capabilities, otherwise everyone races to the bottom of a rising target (how economically valuable the tokens are)
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Idk, Kimi K3 is not that much cheaper than Opus and it’s probably a smaller model. We’ll know for certain when commodity providers price it, but I expect it to be the same price.
Commodity providers aren't a good indicator. They have margins too. Remember they ~doubled the price going from GLM 5 to GLM 5.2, despite same [1] cost of inference. [1] GLM 5.2 is actually slightly more efficient, thanks to baked in indexer cache.
On openrouter GLM 5.2 is ~3x cheaper than 5.0.
I really wish there was a canonical platform endpoint to programmatically check Codex usage amount and the quota reset times so I could just vibecode an app to alert "hey, your usage just went to 100% so that means OpenAI did a reset" and "hey, your 5-hour usage is at 10%, wrap up what you're doing". The only way to do it now is through shenanigans with the Codex App Server which is not ideal.
I keep this bookmarked and check it frequently https://chatgpt.com/codex/cloud/settings/analytics
Earlier quoted context omitted.
They just merged the ChatGPT app and the Codex app into one super app. It is a clever growth hack.
I would expect them to grow faster than 1 million users a day in that case, since chatGPT has almost a billion users. Maybe everyone's just using the web app or mobile?