3 ms·
This is 3x the price of GPT-5.1, released just 6 months ago. Is no one else alarmed by the trend? What happens when the cheaper models are deprecated/removed ov
by mudkipdev 7mo ago
This is 3x the price of GPT-5.1, released just 6 months ago. Is no one else alarmed by the trend? What happens when the cheaper models are deprecated/removed over time?
- dandaka 7mo agoSOTA models get distilled to open source weights in ~6 months. So paying premium for bleeding edge performance sounds like a fair compensation for enormous capex.
- operatingthetan 7mo agoWe know they cost much more than this for OpenAI. Assume prices will continue to climb until they are making money.
- beering 7mo agosource? There have also been a bunch of people here saying the opposite
- horiap 7mo agoHow do we know that? There is a large gap between API pricing for SOTA models and similarly sized OSS models hosted by 3rd party providers. Sure, they’re distilled and should be cheaper to run but at the same time, these hosting providers do turn a margin on these given it’s their core business, unless they do it out of the kindness of their heart. So it’s hard for me to imagine these providers are losing money on API pricing.
- energy123 7mo agoLook a cost per intelligence or cost per task instead of cost per token.
- ulimn 7mo agoIsn't the outcome / solution for a given task non-deterministic? So can we reliably measure that?
- dns_snek 7mo agoRepetition and statistics, if you have $1000++ you didn't need anyway.
- genericresponse 7mo agoStatistically. Do many trials and measure how often it succeeds/fails.
- kridsdale1 7mo agoAka a benchmark.
- foota 7mo agoYes, sort of. Generally you can measure the pass rate on a benchmark given a fixed compute budget. A sufficiently smart model can hit a high pass rate with fewer tokens/compute. Check out the cost efficiency on https://artificialanalysis.ai/ https://artificialanalysis.ai/ (say this posted here the other day, pretty neat charts!)
- throwuxiytayq 7mo agoIt's much easier to measure a language model's intelligence than a human's because you can take as many samples as you want without affecting its knowledge. And we do measure human intelligence.
- torginus 7mo agoThis is the only correct take. The only metric that matters is cost per desired outcome.
- yokoprime 7mo agoHow do I reliably measure 1 unit of intelligence?
- wellthisisgreat 7mo agoIn pelicans, obviously
- msdz 7mo agoSuch an increase tracks the company's valuation trend, which they constantly, somehow have to justify (let alone break even on costs).
- dannyw 7mo agoIt's far more meaningful to look at the actual cost to successfully something. The token efficiency of GPT-5.5 is real; as well as it just being far better for work.
- Night_Thastus 7mo agoThis is entirely expected. The low prices of using LLMs early on was totally and completely unsustainable. The companies providing such services were (and still are) burning money by the truckload. The hope is to get a big userbase who eventually become dependent on it for their workflow, then crank up the price until it finally becomes profitable. The price for all models by all companies will continue to go up, and quickly.
- oezi 7mo agoI recently looked at this a bit but came away with the impression that at least on API pricing the models should be very profitable considering primarily the electricity cost. Subscriptions and free plans are the thing that can easily burn money.
- Night_Thastus 7mo agoThe physical buildouts and massive R+D spending is the big part.
- subhobroto 7mo ago> The price for all models by all companies will continue to go up, and quickly. This might entirely be true but I'm hoping that's because the frontier models are just actually more expensive to run as well. Said another way, I would hope, the price of GPT-5.5 falls significantly in a year when GPT-5.8 is out. Someone else on this post commented: > For API usage, GPT-5.5 is 2x the price of GPT-5.4, ~4x the price of GPT-5.1, and ~10x the price of Kimi-2.6. Having used Kimi-2.6, it can go on for hours spewing nonsense. I personally am happy to pay 10x the price of something that doesn't help me, for something else that does, in even half the time.
- viktorcode 7mo ago> This is entirely expected. The low prices of using LLMs early on was totally and completely unsustainable. Do you think this is true for DeepSeek as well?
- 7mo ago
- kuatroka 7mo agoNot really a big problem. Switch to KIMI, Qwen, GLM. You’ll get 95% quality of GPT or Anthropic for a 10th of a price. I feel like the real dependency is more mental, more of a habit but if you actually dip your toes outside OpenAI, Anthropic, Gemini from time to time, you realise that the actual difference in code is not huge if prompted in a good way. Maybe you’ll have to tell it to do something twice and it won’t be a one shot, but it’s really not an issue at all.
- nubg 7mo agoGod I hope this is true. Where can i find up to date resources on open source models for coding?
- vibe42 7mo agohttps://old.reddit.com/r/LocalLLaMA/ https://old.reddit.com/r/LocalLLaMA/ Bit of a hype madhouse whenever a new model is released, but it's pretty easy to filter out simple hype from people showing reproducible experiments, specific configs for llama.cpp, github links etc.
- Mashimo 7mo agoI use glm and I like it, not they also increased the price to 18 usd /month. I think Kimi and qwen are similar?
- Schlagbohrer 7mo agoAs others have mentioned you're ignoring the long tail of open-weights models which can be self hosted. As long as that quasi-open-source competition keeps up the pace, it will put a cap on how expensive the frontier models can get before people have to switch to self-hosting. That's a big if, though. I wish Meta were still releasing top of the line, expensively produced open-weights models. Or if Anthropic, Google, or X would release an open mini version.
- Wowfunhappy 7mo agoWell, Google does release mini open versions of their models. https://deepmind.google/models/gemma/gemma-4/ https://deepmind.google/models/gemma/gemma-4/
- deaux 7mo agoAnd they're incredibly good for their size.
- boppo1 7mo agoWhich, unfortunately is still slow unusable garbage compared to fronteir models.
- deaux 7mo agoNot at all, it's more than enough for a large range of tasks. As for slow, that's just a function of how much compute you throw at it, which you actually control unlike with closed weights models.
- kridsdale1 7mo agoDepends on your hardware.
- typs 7mo agoGPT-4 cost 6x on input and 2x output tokens when it was released as compared go GPT-5.5
- thrawa8387336 7mo agoApparently the cost/price is 20x in the major providers. Not clear how it is a business
- scotty79 7mo agoWhen technology settles rent seeking beancounters will squeeze out of this the last drop of value they can. In theory it just needs to be cheaper than human doing the same job. In practice it will have to be cheaper than a human using open source model on his own hardware, that can do the job.
- jeffybefffy519 7mo agoSurely its just the same model, just allowed to do more work...??
- michaelcampbell 7mo ago> What happens when the cheaper models are deprecated/removed over time? Fewer people will use it.