We’re at a small startup and we mix models. But mainly just between the major providers. I wouldn’t say it’s as much to avoid spending money as it is to get the maximum benefit out of different capability spectrums.
Well, you can say that all day long but realistically would your “small startup” even exist if your firm was charged Enterprise rates or the actual compute costs and denied access to capital to subsidize your users? It’s a fair question.
The other, more complex one would be “what benefit” are you talking about? Clearly there are some differences in performance regarding speed and token cost, but industry news indicates not a single one has solved the inherent hallucination problem which makes the reliability akin to an untreated schizophrenic research or coding assistant.
Nowadays I don't understand why you wouldn't use a (more-or-less) nearby hosted Chinese model. You have the security, you have roughly the same performance, and you have an order of magnitude more bang for your buck. Bonus point : the models aren't censored and won't refuse to answer in the middle of your coding session.
It's about whether or not their censorship affects you. Their models are censored for the Chinese audience. Meanwhile Anthropic OpenAI etc models are censored for the American audience.
So by default you'd be better with one of the Chinese models if you're American.
As long as you’re not asking it for help discussing a trip to tiananmen square. “Censor” is probably the wrong word. Chinese models are “censored” but much less restricted. For all intents and purposes, Chinese models are less “censored” / “restricted” / “limited”.
The only path forward is to get LSD into the water supply at Davos and put on a really scary play about Rokko’s Basilisk for all the money people, or else Sam Altman won’t be able to afford to repair his infinity pool
They need a new acronym: AGI -> ASI -> Artificial Mega Intelligence AMI? Maybe go back to AGI but make it mean Artificial Godlike Intelligence?
It's too bad Altman already blew his wad with the whole Dyson sphere thing. It's hard to top that. Maybe he can promise them a paperclip universe? That's gotta be worth a few more trillion.
If you sell "AI" maybe, if you sell products that happen to use LLMs to provide services previously not possible, the money still exists in my experience.
When I first heard of tokenmaxxing, I thought it had to be a joke. But no, it turned out to be a widespread phenomenon. I still cannot believe that was a thing.
What I keep saying in internal meetings is: "I am so glad these people are this bad at deploying these tools." It really leaves the door open for folks like us.
It’s a forcing function. If you are running a company you need to be in control. Some engineers dngaf or will sandbag everything.
We did a 90 day push and identified where we found value and where we didn’t. Our tools teams really upped their game, more than expected, and it would have been unlikely to have been funded if they tried to justify the budget as an individual initiative.
There’s a spectrum of people - some folks are building rando apps for fun with LLMs, and many don’t really know what’s possible becuase they don’t or can’t invest in the subscription to really use the tools at home.
Exactly. People misunderstand the point of the tokenmaxxing time period, it was to force people to use AI so as to not have them stuck in their way, as some people are, and then to evaluate how it can help the company.
There's very little that wasn't possible before LLMs, because, well, you still had humans. There are many things that the models promise to make a lot cheaper, if you're willing to accept trade-offs, but these trade-offs can be quite severe.
Many of the most successful applications of LLMs are fields that were already terrible. For example, LLMs are a natural fit for customer support. And somehow, it's also a natural fit for software engineering, which I suppose is an indictment of our field... who cares if a model comes up with a bad architecture or a product that only kinda-works, that's how we always rolled.
> There's very little that wasn't possible before LLMs, because, well, you still had humans.
Agree, but only partially. I considered being more clear, but I am trying to learn to stop writing walls of text :)
When I said "provide services previously not possible," it was just due to the fact that finding an allocating the talent to do analysis on Topic X, would have previously made many products too expensive. Even if you just consider LLMs + harnesses to be an improved search tool, there is a lot you can make with a better search tool.
Enron was doing really well with creative accounting too. Non-GAAP numbers are out of control in 2026. The unwinds are going to be stunning eventually. Also, my small portfolio is worth a billion! In Yen, but it’s still an accurate claim.
Never spent more than 40 euros per month on the base plans for Claude and OpenAI. And I’m doing 10x the amount of work I did before. As long as my computer isn’t running at night as well, I’m not upgrading.
Same experience. There was a period where Claude was burning through it's limits very quickly (~2 months ago?), but other than that, the $20/month plan is enough to do loads of work+personal coding. I am curious what workflows people are using that requires the expensive plans, and what they're building/maintaining.
We’re at a small startup and we mix models. But mainly just between the major providers. I wouldn’t say it’s as much to avoid spending money as it is to get the maximum benefit out of different capability spectrums.
Well, you can say that all day long but realistically would your “small startup” even exist if your firm was charged Enterprise rates or the actual compute costs and denied access to capital to subsidize your users? It’s a fair question.
The other, more complex one would be “what benefit” are you talking about? Clearly there are some differences in performance regarding speed and token cost, but industry news indicates not a single one has solved the inherent hallucination problem which makes the reliability akin to an untreated schizophrenic research or coding assistant.
Nowadays I don't understand why you wouldn't use a (more-or-less) nearby hosted Chinese model. You have the security, you have roughly the same performance, and you have an order of magnitude more bang for your buck. Bonus point : the models aren't censored and won't refuse to answer in the middle of your coding session.
How does it connect to let's say, vscode. I would love to move away from Claude, but it's really easy to set up. Just add a vscode extension
Is censorship not an issue with Chinese models?
It's about whether or not their censorship affects you. Their models are censored for the Chinese audience. Meanwhile Anthropic OpenAI etc models are censored for the American audience.
So by default you'd be better with one of the Chinese models if you're American.
As long as you’re not asking it for help discussing a trip to tiananmen square. “Censor” is probably the wrong word. Chinese models are “censored” but much less restricted. For all intents and purposes, Chinese models are less “censored” / “restricted” / “limited”.
Far less than OAI or Anthropic’s censorship. If you really care about it, you can use a completely uncensored edition of Qwen.
Not for coding or office work which is the majority of use cases.
I'd say no more than in Usanian models?
https://archive.is/osBJs
The only path forward is to get LSD into the water supply at Davos and put on a really scary play about Rokko’s Basilisk for all the money people, or else Sam Altman won’t be able to afford to repair his infinity pool
They need a new acronym: AGI -> ASI -> Artificial Mega Intelligence AMI? Maybe go back to AGI but make it mean Artificial Godlike Intelligence?
It's too bad Altman already blew his wad with the whole Dyson sphere thing. It's hard to top that. Maybe he can promise them a paperclip universe? That's gotta be worth a few more trillion.
Call it "Roko's Modern Life"
If you sell "AI" maybe, if you sell products that happen to use LLMs to provide services previously not possible, the money still exists in my experience.
When I first heard of tokenmaxxing, I thought it had to be a joke. But no, it turned out to be a widespread phenomenon. I still cannot believe that was a thing.
What I keep saying in internal meetings is: "I am so glad these people are this bad at deploying these tools." It really leaves the door open for folks like us.
It’s a forcing function. If you are running a company you need to be in control. Some engineers dngaf or will sandbag everything.
We did a 90 day push and identified where we found value and where we didn’t. Our tools teams really upped their game, more than expected, and it would have been unlikely to have been funded if they tried to justify the budget as an individual initiative.
There’s a spectrum of people - some folks are building rando apps for fun with LLMs, and many don’t really know what’s possible becuase they don’t or can’t invest in the subscription to really use the tools at home.
Exactly. People misunderstand the point of the tokenmaxxing time period, it was to force people to use AI so as to not have them stuck in their way, as some people are, and then to evaluate how it can help the company.
There's very little that wasn't possible before LLMs, because, well, you still had humans. There are many things that the models promise to make a lot cheaper, if you're willing to accept trade-offs, but these trade-offs can be quite severe.
Many of the most successful applications of LLMs are fields that were already terrible. For example, LLMs are a natural fit for customer support. And somehow, it's also a natural fit for software engineering, which I suppose is an indictment of our field... who cares if a model comes up with a bad architecture or a product that only kinda-works, that's how we always rolled.
> There's very little that wasn't possible before LLMs, because, well, you still had humans.
Agree, but only partially. I considered being more clear, but I am trying to learn to stop writing walls of text :)
When I said "provide services previously not possible," it was just due to the fact that finding an allocating the talent to do analysis on Topic X, would have previously made many products too expensive. Even if you just consider LLMs + harnesses to be an improved search tool, there is a lot you can make with a better search tool.
Yet OpenAI and Anthropic combined are somehow making $100B in revenue...
Yea, that tracks. I just looked it up and AWS made ~130bn.
Given how big AI is, and how those two are pretty much the only players (in comparison aws is 1/3 market share), that seems about right.
It's a far cry from "nobody's going to be writing any code, and ai will do all the things in 6 months".
Enron was doing really well with creative accounting too. Non-GAAP numbers are out of control in 2026. The unwinds are going to be stunning eventually. Also, my small portfolio is worth a billion! In Yen, but it’s still an accurate claim.
Source?
Never spent more than 40 euros per month on the base plans for Claude and OpenAI. And I’m doing 10x the amount of work I did before. As long as my computer isn’t running at night as well, I’m not upgrading.
Same experience. There was a period where Claude was burning through it's limits very quickly (~2 months ago?), but other than that, the $20/month plan is enough to do loads of work+personal coding. I am curious what workflows people are using that requires the expensive plans, and what they're building/maintaining.
use rtk or other similar tool
"Trust me bro" - Wall Street Journal
how long until the too-big-to-fail bubble bursts so I can buy a hard drive again?
> so I can buy a hard drive again
Well, that is unless the burst also brings a general collapse. Some are seeing similarities with 2008.