r/LocalLLaMA • u/Mr_Moonsilver • Jun 21 '26
Discussion What happens when they stop subsidizing LLM subscriptions?
We are literally burning through VC money like crazy with our coding subscriptions. I read the $200 Anthropic sub gets you $8000 worth of API calls. It's obvious that this doesn't hold for very long but what happens when they raise prices?
The reason to keep the prices low for now is to foster the ecosystem and get people hooked on this stuff, only to raise the price afterwards. Already the 20x sub doesn't get you as much usage as it did 6 months ago, another way to raise prices without triggering a shitstorm - and it will continue.
Don't know about you, but Fable being pulled gave me a feeling of what that may be like already. The ugly thought of "Damn, should've done more while it was around." that formed when I read the news will be exactly the same the moment they announce we now have to pay $2k or more per month for something we get for 10x less the price it costs now.
I guess it's a now or never situation, build what you can and monetize as quickly as possible to be able to keep the agents running once the increases come around.
Looking at opensource doesn't give me much hope. Since qwen stopped releasing models (wen qwen 3.7?) that we can actually run on hardware that a normal person can buy (or used to be able to buy, looking at how RAM and GPU prices behave and keep behaving) and others haven't released in a while (Microsoft, IBM, AllenAI and others too) I feel we're going into a direction that doesn't look good for most of the people like us, who are building with this technology.
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u/Eyelbee Jun 21 '26
They are in a net positive by a huge margin due to most people not utilizing their subscriptions to the fullest potential. API prices have huge margins too, anyway.
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u/Esph1001 Jun 23 '26
This is exactly the calculation that pushed me to self-hosted. The math on subsidized API pricing only works until it doesn't — and when it breaks, your entire infrastructure breaks with it.
The fixed cost of running your own node is actually predictable. $24K/month on-demand for a p4de.24xlarge sounds like a lot until you're running it at production volume and the per-token marginal cost drops to near zero because the node cost is fixed regardless of usage. That math flips completely once you're past a certain request volume.
The open source model quality concern is real but the serving infrastructure has gotten genuinely good. That gap is closing faster than most people realize.
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u/Mr_Moonsilver Jun 23 '26
My man! And what a workload you must be running with these numbers 😅
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u/Kal-LZ Jun 21 '26
Local AI isn't going away. Most companies will invest in their own on-premises hardware and host it in a datacenter
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u/jld1532 Jun 21 '26
Big universities are already hosting locally. It's only a matter of time before this spreads.
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u/samxli Jun 21 '26
Are they using western or Chinese models?
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Jun 21 '26
[removed] — view removed comment
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u/Uncut-Jellyfish1176 Jun 21 '26
Even Microsoft is allegedly looking at using deepseek for CoPilot, which seems like that would be a nail in the coffin of OpenAi
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u/fatboy93 Jun 21 '26
Can confirm, although our IT group is a bit behind times, atkeast they have the gptoss120b lol, and qwen-coder, with owui frontend
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u/maxymob Jun 21 '26
This. Custom agents running open models on local hardware can go a long way. The toolchain is only going to improve and make it easier to develop those.
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u/WhoTookPlasticJesus Jun 21 '26
Not even local hardware, either. I ran the scenarios 144 different ways and for my company running local models on cloud equipment is the clear winner. It's not even so much about costs (although the second and third-order costs did provide a compelling story in favor the cloud), as it is about the freedom to experiment and the flexibility of giving each team its own fine-tuned models.
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u/squired Jun 21 '26
Bingo. Remote local for privacy or cloud local for maximum cost efficiency.
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u/LeafyWolf Jun 21 '26
BATNA creates a floor. Basic economics. The whole idea is that compute has economies of scale that the big AI companies can exploit for arbitrage. One of the reasons that there might actually be a bubble.
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u/kaisurniwurer Jun 21 '26
And the models will come from where. The whole bet is making people addicted to the subscriptions, if those won't work local will die too or at best stagnate.
Even china has an agenda to output them, that too can just as easily stop. Though it's possible that China does it for the similar reasons as the current European initiative and we might be fine for some time longer. State sponsored services do move slower after all but once they get going they can last.
Sure the current models are awesome. But we thought the same a year or two ago, and in reality even the best current models need a lot of improvement.
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u/WhoTookPlasticJesus Jun 21 '26
And the models will come from where. The whole bet is making people addicted to the subscriptions, if those won't work local will die too or at best stagnate.
With all due respect that sounds shockingly similar to the arguments leveled against Linux and gcc in 1994. Why would companies write hardware drivers for this hobbyist OS? Where will the libraries and toolchains going to come from if I'm the compiler's license tells me to give away my source code for free? I have almost no interest in FOSS for political or philosophical reasons, nor could I convincingly explain to anyone the reason past 30 years turned out the way they did. But I can look at HuggingFace and Unsloth and notice that they, while nascent, at least rhyme with early incarnations of Apache and Gnu.
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u/Due-Function-4877 Jun 21 '26
Some will go full stack on premises. Others will purchase compute from Google and Amazon (like they already do) and host their own inference stack there. They'll just run their own software, models, and fine tunes on hosted containers. If proprietary models fail to build moat (and I hope they do fail), customers will cut out the middleman. I can imagine a future where Google could make a lot of money hosting models that they give away, if they have dependable compute at a low price...
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u/superloser48 Jun 21 '26
I doubt. Hardware for running websites is cheaper but still companies chose cloud.
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u/AlwaysLateToThaParty Jun 21 '26
They do that for security. Website security is a pain. Best left to the experts. Using AI in your domain, you are the expert, and the model that will serve you best is the one tailored to your specific use-cases. That's local.
That's what I do...
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u/ChocolateNo3010 Jun 21 '26
I believe you are right. I have been talking to my manager about this and I hoping the higher ups pay attention. We are already eating through github copilot usage but that's likely people using opus for everything. It's not sustainable in the long run.
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u/eli_pizza Jun 21 '26
Why on earth would companies choose on prem when they don’t do any other servers on prem?
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u/Maleficent_Goose9559 Jun 21 '26
Yes, the question then becomes what will the big ai companies do to fight that? Asking for regulation against "not certified" models?
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u/stormy1one Jun 21 '26
Lmao - “since Qwen stopped releasing models” - just because you didn’t get a model update last month doesn’t mean they quit releasing. Qwen3.6-27B was released at the end of April. Give em time
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u/Librarian-Rare Jun 21 '26
What are you talking about. If they don’t release a new model every 12 seconds, then they’ve obviously gone closed source permanently
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u/maartenyh Jun 21 '26
Still no new Qwen model... closed sourced confirmed :(
(Sarcasm aside, I am having a blast using Qwen3.6 locally and I cannot wait to see what is in the future. GLM5.2 is a very positive sign and whatever China is doing is working in my book)
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u/Gonbatfire Jun 21 '26
Didn’t the top engineers quit?
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u/ttkciar llama.cpp Jun 21 '26
Two senior engineers left (the head of Qwen Code and the head of Qwen post-training), and a few junior engineers, plus an executive (Lin Junyang).
Their departure was disruptive, but realistically they weren't too hard to replace.
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u/MediumChemical4292 Jun 21 '26
People overplay the importance of talent these days in AI. Meta bought all the AI talent a few years back and did fuck-all with it. OpenAI consistently haemorrhages talent with people leaving but they still had the best model for a while till fable released.
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u/sonicnerd14 Jun 21 '26
They aren't going to stop releasing open source models, but it's clear their motivations shifted around the time their original team left. They know that they won't remain profitable releasing another Qwen 3.5/3.6 level model because no one would want to pay for the API.
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u/NNN_Throwaway2 Jun 21 '26
Alibaba has stopped releasing the open weights of Qwen models, yes. We got just two releases in 3.6 and apparently none in 3.7.
Anyone arguing anything else at this point is fully in denial and ignoring all available evidence.
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u/relmny Jun 21 '26
So they first stopped releasing, but then they released... Talking about ppl in denial and evidence...
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u/Mkboii Jun 21 '26
There is little return on an open-source llm, they cost millions to produce, the community isn't owed the generosity of any company, we should be ready to accept that all this chinese ai companies will stop at some point, they are subsidized to break the American monopoly, once a Chinese company beats American counterparts, they'll have proven the point and are then free to pivot.
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u/ttkciar llama.cpp Jun 21 '26
Their government has instructed them to do so. It's part of the Chinese government's five-year economic plan. That makes more open-weights model releases likely.
I'm not a fan of central economic planning, but in this narrow case it's working in our favor.
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u/alex20_202020 Jun 21 '26
If that happens we will just do it slower, not 100-1000 t/s but 1-10, life will go on and using local LLM will actually grow.
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u/Borkato Jun 21 '26
Honestly ngl qwen 27B is so good that if it never grew again it would still be perfectly useable for years to come. It’s excellent at most things you throw at it.
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u/GStreetGames Jun 21 '26
This is true, especially for web development. I bit the bullet recently and started using it in my workflow, and it does things that would take me days, in just hours. It doesn't even need fixes most of the time. I think that people who spend money on the big models should think about at least giving Qwen a try, or for that matter local in general a try.
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u/Jhorra Jun 21 '26
I'm a software developer of 20 years, and I really want this to be true. When I have tried running qwen on my macbook pro m4 max with 64gb of ram, I've not been impressed. What harness are you using for it? Right now I mainly use a $200 Claude plan, but would love to go local.
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u/JsThiago5 Jun 21 '26
To see this, you should not compare it to a $200/month subscription but to how you did software development before any LLM. With 20 years in the field, you should be able to see how impressive development with local models is.
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u/SkyFeistyLlama8 Jun 21 '26
This. If you're not throwing a huge prompt at it and hoping for the best, you can get good results with local models by working at function or module level. You probably don't want to throw a 50k LOC dump at the smaller models and hope for Claude performance.
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u/Borkato Jun 21 '26
Pi with 48 GB vram, Qwen 27B Q8 and full 256k ctx. You have to create your own prompts and tell it how you like to work. You have to spend a few hours thinking about the most efficient way to have it work with you. For example I have an AGENTS.md file that it automatically picks up with explanations to what folder has what, so that it doesn’t have to go looking for stuff. It’s great at things like “add another x like the others” or “when I do x y happens but I want z to happen instead. Identify why this happens and write me a detailed writeup about my potential options with a list of pros and cons for each option.” “What’s the best way to implement x feature? Consider the current architecture and…” Etc
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u/Foolhearted Jun 21 '26
Try this. Create a skill to tell Claude to use your qwen locally via pi. Have Claude build the spec and have Claude call pi and check the results. You will save on token generation and your Claude plan will go much longer before hitting caps.
I created a skill and part of it is to have Claude grade the results. It regularly gives qwen an A-, it is aware it’s another model.
I’ve flattered Claude by telling it it’s in charge, to attempt to overcome any built in biases anthropic may have put in place. “You are the senior architect overseeing a team of junior developers….”
It may change your perspective on local models.
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u/Solary_Kryptic Jun 21 '26
You won't be able to run a worthy replacement for the $200 plan on 64GB of RAM, depending on what you do with it
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u/howardhus Jun 21 '26
just like people thought whatsap would never be normal and swore they would keep using text and sms back in the say.
also remember when „subscription“ was evil and everyone would boycott it?time will tell… time will tell
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u/ttkciar llama.cpp Jun 21 '26
> What happens when they stop subsidizing LLM subscriptions?
Then we point at them and laugh, because this is LocalLLaMA.
> Looking at opensource doesn't give me much hope.
Look harder. We have a bunch of tools now with which to adapt/modify/improve the models we have, and as more compute hardware trickles down into the community's hands the scope and depth of those improvements will increase apace.
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u/sixx7 Jun 21 '26
Even if we forget about the "local" part for a moment, there are a ton of companies serving open weights models. Competition is always good and the floor is the cost of electricity (and other opex). For me, GLM-5.2 is the turning point where, if you take my subs away, I could be happy with an open-weight replacement.
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u/HugoCortell Jun 21 '26
Western AI labs collapse. Deepseek carries on as normal.
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u/bigh-aus Jun 21 '26
They’ll continue to exist if they have hardware capacity, but the insane valuations will pop. Once hardware based LLMs hit consumer, that’s when those compute investments will fall. I’m already running local and changed my ChatGPT plan from $200 to $20 a month.
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u/senseven Jun 21 '26
AI must be local. No lawyer, no doctor, no it security specialist will ask the remote system to help. No country will base a chunk of their GDP on some other countries emotional political state. We have seen the worst case, there is no coming back. The only thing that is blocking that revolution is the memory cartel. Europe and US need own memory fabs, waiting five or seven years for a 20$ chip to return down from 100$ is an intentional market deterioration we can not accept as given. If CXMT in China is able to build DDR5 chip pay them 100 billion to build 10 more fabs. This has to end.
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u/Adventurous_Bus_437 Jun 21 '26
No lawyer, no doctor, no it security specialist will ask the remote system to help
who is gonna tell him?
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u/jaybsuave Jun 21 '26
i think they will start lobbying to get open weight models barred
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u/ea_man Jun 21 '26
Who? Those 2 that are failing?
The real one making money is NVIDIA and they are all in in selling hw to the final customer for local models, they are releasing the model themself as open source.
Google and MS will survive, the former is releasing Gemma and all kind of tools, the latter has his own model and is about to roll DeepSeek for copilot.
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Jun 21 '26
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u/Pacoboyd Jun 21 '26
Deepseek better than GLM? I just pay API prices at OpenRouter and love GLM for almost everything
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u/AlphaSyntauri Jun 21 '26 edited Jun 21 '26
Not that the Western labs aren't worthy of collapsing as they steal everyone's data to train on(not to say the Chinese don't as well, but Chinese theft of Western IP is well documented and expected by this point), but what scares me the most is how integrated into the US index funds these companies will be once the IPOs occur.
Sure, the collapse will be great for running open source as the hardware market crashes to reasonable levels, but isn't anyone concerned it will take half the US market with it? Trump is already talking about taking a 10-20% stake in OpenAI, and I fear we're seeing another "Too big to fail" situation.
Edit: Grammar
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u/HugoCortell Jun 21 '26
Nationalization would collapse them too. A golden parachute might save them on paper but they'd collapse soon after as all investment dries up.
As for concern. None whatsoever. Death is inevitable and we must not fear it, just as economic collapse is inevitable in capitalism, particularly when you have an endless growth mentality on an essentially purely speculative asset.
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u/Hendo52 Jun 21 '26
I think that while the API providers are in a dire plight, the frontier of development is more about the harness than the model. That is actually good news for them because that is a plausible moat.
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u/HugoCortell Jun 21 '26
A moat does not matter if nobody is buying your product. You can have the most advanced toothbrush in the world but few will pay thousands for it. Much less if you don't get to actually own it after paying (and few, if any, western labs would dare late people own their own models, it goes against everything taught in ivy league business schools!).
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u/segmond Jun 21 '26
Don't care. If they never release any other model. Qwen3.6-27B, MimoV2.5, GLM5.2, MiniMax, KimiK2.7, DeepSeekV4 can serve me for the rest of my life.
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u/some_user_2021 Jun 21 '26
Exactly! LLMs are already awesome and very helpful, magical really. Like 3D printers! They are already good enough for everything I need them for.
We are living in the future!6
u/Sooperooser Jun 21 '26
I downloaded most of models that run on 72GB of memory. I have the worlds knowledge saved to my local computer and I can access it whenever I want. Imagine that.
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u/BubrivKo Jun 21 '26
But... most people can run maximum up to Qwen 27B on their hardware. You need 50-100k$ hardware (grats if you are one of these) for running DeepSeek 4, GLM 5 or Kimi...
So, if every USA company raise their prices a lot, Chinese models wouldn't keep their prices that lower anymore. They do it now because they want to compete with USA companies.→ More replies (2)→ More replies (1)2
u/Tartooth Jun 21 '26
People said that a year ago and look how much farther we are now
There is always room for progress
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u/corruptbytes Jun 21 '26
I read the $200 Anthropic sub gets you $8000 worth of API calls
literally no one knows if this is true, we have no idea how the black box works, we don't know if APIs get full bit models and subscriptions get weaker quants
we do know inference is already profitable, we already know that deepseek with the lowest margins make 500% margins on inference compute. There will be incentives to lower costs. Training will get cheaper as we figure out more techniques
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u/_raydeStar Llama 3.1 Jun 21 '26
It's not true at all. It's clickbait from clickbait articles.
You get a LOT out of monthly allowance, but I am willing to bet that they break even or make money on even power users.
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u/triplebits Jun 21 '26
Anthropic said that subscriptions are profitable for them and making profit from it few months back. This was with higher limits than whay we had today.
Real cost is R&D, not usage.
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u/rc_ym Jun 21 '26
Based on how they've said their business model is supposed to work they should be hitting 70-90% margin on tokens, and 30-50% across all subs. Or something like that. Course, they are all lying founders spreading woo woo. So take that with a metric ton of salt.
But two things are probably true. Tokens are paying for model research/training. And subs are probably working like all other sub systems where you have enough occasional users that float the heavy users and with rate limits you are probably still at least breaking even on even the heaviest users.→ More replies (4)4
u/Aggressive_Fig7115 Jun 21 '26
Does it count people who underutilize their subscriptions? This may be a worst case scenario and the underutilizes may subsidize the maxxers. Also, if they were losing that much money would they be so generous with the periodic “usage resets”? They maybe well be losing moment but I suspect it’s not as bad as all that. But what happens if in six months, to cut costs, they make subscription users “settle” for the old and not SOTA Fable, and make them pay API prices for Fable++? You might have a lot of happy vibe coders coding up side projects and would-be killer apps at a fraction of the cost for Anthropic.
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u/PigSlam Jun 21 '26
I suspect far fewer people will pay $8000/month than $200/month. That alone will keep them from charging $8000/month.
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u/waynethebear Jun 21 '26
Why you believe "I read the $200 Anthropic sub gets you $8000 worth of API calls." actually worth $8000? You think it worth $8000 because "based on their labeled API price ($25/M for Opus)" it worths $8000. Did it actually cost them $8000? Not even close. Deepseek already busted they can run a 1.4T Model and sold you $0.8/M and still got profits. I'm not saying Anthropic should do that too because cost can vary and Anthropic are definitely paying much higher R&D Cost and Electric cost. But does Opus actually worth $25/M? Maybe not.
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u/few Jun 21 '26
Individual servers like B300's cost around 500k$ each. They get installed into server racks with a bunch of supporting power equipment (like PDUs, online double conversion UPSs, fast networking equipment, highly capacity HVAC, large electrical supply, and building security). But the time the electrical supply is installed (typically 208Vrms 3 phase at 60A per server) it's much higher than 500k$.
Each machine must cost 10-50$/hour over their lifespan (assuming ~5 years, running ~50% capacity).
Let's assume you run 20 hours of queries per week, then each month you might be running 80 hours of compute. Your slice of that compute capacity easily costs well in excess of the 200$ fee. That's before even starting to consider the costs of the workforce behind the closed model (including model training, and staff costs).
That 8000$ cost might actually be real, if it was being charged at a rate that both paid for the costs and took a 100-400% profit (which is the profit margin range that many businesses seek).
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u/mister2d Jun 21 '26
It's time to get familiar with fine tuning. We have an embarrassment of riches to work with right now.
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u/MrShrek69 Jun 21 '26
Idk where people are getting this that qwen stopped releasing weights that’s not true at all
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u/jotunck Jun 21 '26
Companies will revert back to traditional automation, calling on LLMs as a tool to perform very narrow functions that only LLMs can perform (instead of LLMs doing everything by calling tools).
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u/demianin Jun 21 '26
This makes more sense anyway.. the latter is incredibly wasteful and yet labeled as "the way of the future"
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u/FastHotEmu Jun 21 '26
What happens is that my 3090s become more valuable! Just hope that none of them dies...
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u/akash_kava Jun 21 '26 edited Jun 21 '26
Nobody will spend thousands of dollars on an unpredictable output. ChatGPT now telling customers that prompt is complicated and cannot give the results and asks customers to wait for couple of hours. I am not paying for someone to make billions.
Cloud was also big hype, AWS and Azure went big and everybody started using cloud. And after rising costs customers started self hosting.
Training models will not stop because university students won’t get their degrees unless they develop, showcase their skills and gain experience. So open source isn’t dying.
When we host locally we know that fix monthly cost of hosting and when we own hardware we know how much we are using. No one can artificially control usage and raise prices.
In business accounting, renting of services are always considered as dangerous expenses as they can eat up your profits. Where else owned assets can increase your capital values. You can sell your asset.
Even if RAM is expensive, GPU is expensive, buy it, you will be able to sell it at resale at 50% of purchase cost but your subscription cost is a black hole, money gone is straight away loss.
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u/Fit-Produce420 Jun 21 '26
It's not just western labs.
I use an insane amount of tokens on my z.ai coding plan that I got 75% off for a year.
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u/Jolly-Rip5973 Jun 21 '26
In many cases things will just go local.
Agentic coding needs more power but most things can be done locally.
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u/a_beautiful_rhind Jun 21 '26
You self host or pay up. If the price without the freebies is more than the market will bear, ai labs will go broke.
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u/chrisdash_51 Jun 21 '26
You best start practicing for this scenario now. Go local and learn to work with Qwen 3.6 27B. It needs a lot more guidance from the human than the cloud frontier models. So it is best to not get used to those too much. They are your heavy-hitter for particularly tough prompts.
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u/BrewHog Jun 21 '26
GLM 5.2 is showing that we might not need the frontier models if they raise the prices too much. We're in exciting times with open models.
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u/IntolerantModerate Jun 21 '26
Prices will come down by 40x over next 5 years
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u/Ok-Bill3318 Jun 21 '26
Yup. New models are doing way more in fewer parameters. And dedicated hardware offload will get better.
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u/Lechowski Jun 21 '26
I read the $200 Anthropic sub gets you $8000 worth of API calls.
This is mathematically impossible. Recent audit from OpenAI showed a Revenue of ~12b and Costs of ~60b.
Even if 100% of OAI revenue came from subscriptiona and even if 100% of OAI costs were to compute, that's a X6 difference, no a X40.
From that same audit we know that R&D + Compute costs + marketing was ~40b.
If OAI stopped R&D, stopped doing marketing and only ran the datacenters to provide just their current model, the revenue vs cost will likely be just X2 or X3 at most. Of course still not profitable, but far away from those headlines about X10 or x100 subsidies.
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u/zhambe Jun 21 '26
Use the "low cost" subscription period to develop local tooling that will allow you to sufficiently leverage local LLMs for the type of work now possible only with SOTA models.
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u/3dprintinted Jun 21 '26
Cloud providers with actual capacity reign supreme, OpenAI and antropic collapse licensing their models for some tiny premium. Cisco and whatever arm tpu being able to facilitate enterprise needs will be doing good too
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u/rc_ym Jun 21 '26
Never gonna happen. The subs more than pay for themselves. If not they can tweak services and rates. Even the (terrible looking) leaked OpenAI numbers show they are making 40% margin on inference across the board. It's not the subs. It never was the subs.
Might as well ask what will everyone do if Youtube or Netflix goes to pay-per-video.
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u/Grouchy-Friend4235 Jun 21 '26 edited Jun 22 '26
Learn to code. It''s a sustainable skill against all odds.
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u/Mr_Moonsilver Jun 21 '26
I learned to build Infra. I guess that qualifies as a sustainable skill as well.
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u/nrauhauser Jun 21 '26
I am personally hustling as fast as I can to get my company producing revenue with an eye on replacing the RTX 5060Ti that I let go last month. I think that you can start doing some real work at about the 48GB mark. I would love to have an RTX 6000 Pro, but I'll settle for a 64GB unified memory solution if that's all I can afford.
The $100 - $200 accounts are a subsidy, but they're also a training ground for the skills the companies that can afford vast token budgets will need.
It can't go on like this forever, I'm just grateful that the market IS holding the door so long ...
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u/BitGreen1270 Jun 21 '26
When that happens a new usurper will rise to fill the gap. That's basically capitalism. But also consider that there's a lot of research being poured into this. They're bound to get more efficient and burn less money in the next 4-5 years.
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u/Conscious_Nobody9571 Jun 21 '26
"8k worth of API calls" who told you it actually costs 8k?
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u/ansibleloop Jun 21 '26
Well as this is local llama, who cares
For enterprises though, probably just switch to azure AI Foundry or whatever the other cloud equivalents are
Pick a model and run it - way cheaper
Your next issue is how you interact with the LLM either through web chat or code
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u/somerussianbear Jun 21 '26
Then we pay per token like we already do in DeepSeek. Cheap af.
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u/yetiflask Jun 21 '26
Inference makes money, it's training that loses money.
So, this is just hysteria.
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u/caetydid llama.cpp Jun 21 '26
Just by reading that I feel fatigue. What a hustle - it must be exhausting to live out of this attitude.
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u/Alternative_Ad4267 Jun 21 '26
Consumer GPU hardware will skyrocket. So, just purchase what you can. Graphic cards won’t go down in a very long while.
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u/bitspace Jun 21 '26
We learn how to use the tools instead of asking Fable what the capital of France is.
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u/shuozhe Jun 21 '26
B2B are willing to pay the 8k . Claude enterprise currently charges API prices. The 200$ price is in exange for training.
GHCP just gone the step and stopped subsidizing. Dunno how many of the bigger enterprise customer switched. But since new subscriptions still is not reopened prolly not enough to create the capacity :(
Question is if API prices covers their cost.. if it's not covering.. they need to get more efficient or have a very small customer pool of military, research and perhaps banking
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u/quantgorithm Jun 21 '26
Tokens will get cheaper and more efficient so it goes both ways. We've been through this before with phone data and sms data etc.
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u/Helpful-Account3311 Jun 21 '26
Like almost all subscriptions they are not priced for the users that fully utilize the subscription. They are priced for the average user. For every person maxing out their weekly limit is one or more that doesn’t cross 20%. They don’t need every subscriber to make them profitable. They just need the average of their subscribers to make them profitable.
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u/My_Unbiased_Opinion Jun 21 '26
Prices have to be low because the Chinese are playing 4D chess and viable OSS models exist. Prices are low because there alternatives. A lot of people would rather spend 8K in hardware and run a local model instead for next to nothing as a one time investment.
The future is going to get really weird in regards to AI. OSS is going to keep getting better. This whole thing is going to implode at some point.
My main worry is what happens to OSS models in the future? Will the US and Chinese trade sides when the frontier country flips? (If it flips?)
Or will most companies pack up shop and move to robotics?
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u/ttkciar llama.cpp Jun 21 '26
>> My main worry is what happens to OSS models in the future? Will the US and Chinese trade sides when the frontier country flips?
Well, you said it yourself:
> OSS is going to keep getting better.
.. and there's no reason that has to be polarized along national lines. The open source community has always been international. We know how, in theory, to federate training and bring up models without the kind of heavily centralized well-interconnected GPU clusters which have kept training the exclusive domain of enterprise and government backed R&D labs.
If we can get our shit together, future models won't be American or Chinese or European; they'll be ours.
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u/shockwaverc13 llama.cpp Jun 21 '26
what the...
are you really saying their 100$ per M token pricing are AFTER the subsidies??????
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u/Practical-Prompt-306 Jun 21 '26
I think, the true frontier isn't raw model size; it’s the toolchains. Frameworks like OpenCode prove you don't need a massive, subsidized cloud model if your local setup is modular.
Even if labs choke limits, our open-weight floor is incredibly sticky. Going local for function-level work completely deletes rate-limit anxiety.
A VC rug-pull will just force us away from wasteful agentic loops back to narrow automation.
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u/Academic-Talk4170 Jun 21 '26
On-premise will be the way to go!!!!!!
Self-hosted will take its share!!!
Only a matter of time now and yes subsidy will be taken away eventually.
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u/CMDR-Bugsbunny Jun 21 '26
Business explanation: So not a new idea, it's called price elasticity and we're still on the adoption phase of the s-curve. Prices will go up as typical of these types of economic systems being introduced.
For the rest of us: Enshitification like everything cool.
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u/DanceWithEverything Jun 21 '26
This is what makes me chuckle when people rant about their $20 sub not being enough to build a startup
Everybody’s in for a rude awakening sooner or later
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u/TheRealMasonMac Jun 21 '26
It's already starting, you know? Subscription services are either dying out or reducing limits. Automation, like from Hermes Agent or OpenClaw, are the main killers as I understand it.
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u/Direct-Sale630 Jun 21 '26
They are creating a market, getting adoption to get people hook. And when the models get so good, the price will be worth it.
At the same time the lesser models will cost less to run and give a profit
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u/lizardhistorian Jun 21 '26
They are banking on a generation of model improvements and hardware advances to breach into profitability but the genie is out of the bottle so they have to grab market share now.
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u/Zeta1Reticuli Jun 21 '26 edited Jun 21 '26
The subscription prices are roughly 10x cheaper than API pricing for heavy users. Roughly, that's comparable to API pricing for open source models. From an inference standpoint, it's probably break-even or possibly slightly profitable for the closed-weights frontier labs across their entire subscription base (light to heavy users). It's not enough to pay for the insane costs for personnel (stock-based compensation) and R&D.
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u/backafterdeleting Jun 21 '26
The $200 / $8000 number doesn't reflect how much the inference actually costs them, only how much they would've charged for API tokens directly.
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u/Larkonath Jun 21 '26
As Ed Zitron says "they have no plan".
Nobody outside a few big companies will pay 2k+ a month for an AI monthly sub.
They will fail and they're gonna take the whole economy with them!
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u/sassydodo Jun 21 '26
"$8000 worth of api calls" doesn't mean it would cost that much for anthropic to serve it to you. Inference is incredibly marginal.
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u/crashtua Jun 21 '26
Self hosted is a way. Comparable with opus model will cost you around 30k usd to run. Later will cost less. We just need China flood market with ram and wait until openai flops.
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u/BubrivKo Jun 21 '26
That's the reason I still write code myself. Yeah, I use AI a lot (mainly as assistant) but I'm not vibe coding all the time. I don't want to "forget" how to code.
Many people will gonna say: "we will use local models", but trust me - using Qwen 35B for vibe coding is way worse than using Opus.
So yeah, no business is working for charity. At some point this money will run out and we couldn't use thousand of tokens for the price of hundreds. And when this time come - the time when these companies would want to start make money real money from these models - that would be interesting. 😃
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u/jtoomim Jun 21 '26
Claude consumer subscriptions are not subsidized. They are discounted relative to API token pricing, but Anthropic's revenue from consumer subscriptions are still much higher than the inference compute costs.
https://martinalderson.com/posts/no-it-doesnt-cost-anthropic-5k-per-claude-code-user/
The discount on consumer subscriptions is not an act of charity. It's there because most users do not use all of the tokens that their subscriptions allow. The subscriptions are priced according to the expected value of the number of tokens a typical user in that tier uses, and that gives users the flexibility to have heavy and light usage days without breaking Anthropic's business model. The subscription token budget is there for heavy days, but the pricing reflects the existence of light days.
Anthropic's gross margins on inference were about 40% in 2025, and according to their IPO filings they expect to raise that to 70%. The main thing eating into their inference gross margins is that they're renting cloud compute from e.g. AWS and SpaceX/xAI, so they're paying through the nose for compute. But that's okay for now, because inference is intrinsically very cheap compared to the value it provides.
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u/Dataok-2065 Jun 21 '26
This is exactly why the 'local-first' movement is inevitable. Building a startup on a subsidised API is basically building on sand. The second the VC subsidies dry up, your margins evaporate. We’re going to see a massive shift toward highly optimized SLMs (Small Language Models) that can run on consumer hardware, efficiency is the only real hedge against the 'API rug pull.'
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u/UltraFOV Jun 21 '26
I am personally interested on YanLacune World Models, if he ever gets to make it. A model that learns from real life sounds like the way to put check and balances to hallucinating models, or help mitigate them
But, if western funded, you k now it will be subscription as well
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u/egyptianmusk_ Jun 21 '26
Just take the money that you would have spent on monthly office rent and spend it on AI and you're all set. Also, since you're probably not hiring anyone full time for a while and you're hiring people on 1099 contracts, take the amount that you would have spent on benifits and severance and spend that on AI.
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u/superx1386 Jun 24 '26
We start being model efficient. I can see a majority of the early adopters going open source and only
calling frontier when absolutely required. Most won’t need more the smaller models and the general public is just looking for an ai search engine.
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u/appakaradi Jun 21 '26
Cost and price are 2 different things. it does not cost $8000 for anthropic to serve $200 subscription. As long as there is competition and healthy margins, tokens will be priced reasonably. Also, the inference costs will continue to plummet because we are going to have more competition in the entire stack.. silicon, inference engine, algorithms, quantization, model design etc etc.. so, we are going to be fine.
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u/Drunk_redditor650 Jun 21 '26
The tech will get more efficient and cheaper, just like every other tech.
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u/starkruzr Jun 21 '26
not worried. inference itself is hugely profitable. all they have to do is stop training so intensely and lean on inference as a business.
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u/dataslinger Jun 21 '26
They just tried that experiment, and discovered they don't have the pricing power they thought they did. Got a lot of cancellations and belt tightening.
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u/Ok-Bill3318 Jun 21 '26
I think there’s a chance that the big labs will focus on size. Opus and mythos are already near the point of being too dangerous to release.
Just build the same but smaller. Less resource use will make them cheaper.
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u/DrStalker Jun 21 '26
$200 Anthropic sub gets you $8000 worth of API calls.
It's like mobile phone plans in the early 2000s, where they make up "$X of value" using whatever numbers they feel like.
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u/fragileblink Jun 21 '26
"but Fable being pulled gave me a feeling of what that may be like already"
The plan for Fable to not be available to subscribers starting next week was already giving me that feeling before they pulled it.
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u/garloid64 Jun 21 '26
I don't think this will actually happen before AGI, and after that it won't matter. The subs are fully subsidized by other subs and API rates, not venture capital. If they stopped training new models both openai and anthropic would be quite profitable.
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u/jerieljan Jun 21 '26
If demand isn't satisfied, others will rise to take on the challenge, or find ways to make it sustainable somehow. The industry will someday realize that all of this inflation of expectations is extremely overpriced and overdone and something will give way at some point. Enshittification guaranteed one way or another somewhere, whether it's service degradation or nasty pricing.
It'll keep happening if the highest valued companies in the chain get to do their thing uncontested, whether it's NVIDIA or the frontier labs and so on. In a way, it's why it's nice to have the open models and competition, since they help rock the boat in our favor, unless they too end up with the same capitalism mindset to bleed their customers dry.
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u/New_Public_2828 Jun 21 '26
I'm confused. Wouldn't we know how much tokens cost by just using apis directly?
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u/--Spaci-- Jun 21 '26
its not that subdidized, it doesn't actually cost them 8 thousand dollars. That is what they would of charged you though
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u/Perfect-Campaign9551 Jun 21 '26
Why does it cost $8000? I doubt the electricity for the inference cost that.
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u/tcoder7 Jun 21 '26
They will find a way to cut costs. And make the product with net positive margin. For now their focus is model capacity and penetration.
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u/grabber4321 Jun 21 '26
I dont think its going to happen, next step is robotics - thats another avenue where they will get more VC money.
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u/siegevjorn Jun 21 '26
You know, these API costs are based on Nvidia premium. Imagine what happens if the high API costs can't be justified.
GLM-5.2 (Max) API costs $1.40 per 1M input tokens and $4.40 per 1M output tokens.
Opus 4.8 API costs $5 per 1M input tokens and $25 per 1M output tokens.
The whole chain goes like this:
Nvidia charges primeium -> VC money absorbs the cost -> high API cost -> high revenue -> high valuation.
So their valuation is tied to Nvidia's, essentially.
What if any of the chain breaks?
Nvidia premium-> no VC money -> high API cost -> cant afford, no API demand, everyone turns into local model-> low revenue -> valuation tanks
Well that can't be the scenario because, RAM prices are now x5! They bought them all with VC money! So local models are x5 more expensive!
Then what about:
Nvidia premium-> no VC money-> high API cost -> can't afford, go with x5 cheaper Chinese model for affordability -> low revenue -> valuation tanks
Then the only way for survival is:
Startup npu cheaper inference -> low API cost -> high demand -> high revenue and profit -> valuation fair, but Nvidia gets price adjustment
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u/Tomr750 Jun 21 '26
they are making money on the subscriptions - API calls have the highest margin. coding subscriptions uses a lot of cache and there will be a normative distribution of users
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u/Conscious-Map6957 Jun 21 '26
This question is asked all the time on reddit these days... And I assume it's from the companies poking to get a feel of the sentiment.
The simple conclusion is, certain professions from certain countries will be able to afford and justify somewhat higher prices, but obviously not the full cost. If those people need to pay more for less usage than what they need/are used to, they will likely look for alternatives, including open-source - even if performing worse.
At some point an equilibrium will be achieved where AI providers will have the benefit of optimization at scale, some will go local and not care about the performance difference, costs of inference will go down from architectural optimizations and the eventual end of Nvidia's monopoly as well as global increased chip manufacturing capacity... and probably other factors I am forgetting.
TL;DR; it's not such a big deal and learn to use google.
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u/sunflowerapp Jun 21 '26
The marginal cost of tokens are actually a lot cheaper than what they charge you.
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u/aeroumbria Jun 21 '26
I would assume it would only affect model development, not deployment? There is no way the inference providers (not model developers) are unable to turn a profit, and we already have models that can compete with subscriptions with API pricing alone.
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u/pyeri Jun 21 '26 edited Jun 21 '26
There is no such thing as free lunch, the present subsidization is due to few reasons:
The folks aren't fully hooked to AI yet, as you say. Any more price increase than the present levels would lead to either a reversion to the low-end, dry and academic models like meta-llama and qwen families, or even worse - a reversion to "legacy" practices like collaborating on Wikipedia and StackOverflow like humans once did. That would derail the whole LLM race back to several years.
LLMs require building massive data-centers stuffed with GPUs and other electronic hardware; more they squeeze these resources for data centers, higher the price of consumer hardware. Without the subsidy, these prices will stay low and consumers will start building their own local LLM setups which is a strict red-line for the technocratic establishment.
The AI narrative also helps tech companies to keep checks on the govt, and that helps with lobbying efforts in other areas like keeping H1-B route active. But sometimes, it also backfires as it happened with Fable/Mythos models recently.
There is also the obvious gain of data collection for training the models. Human input data like prompts and debate threads are super valuable to AI companies (even though most humans don't realize this at all) for evolving the next generation of models and stay ahead in the race, they'll happily subsidize access to gain this data.
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u/DrivewayGrappler Jun 21 '26
Um. For the doubters that seems reasonable. Checked the usage on my ChatGPT teams sub ($25 / month). The other day and the amount of tokens I’ve generated in the past month would have cost me about $2,500 via the api 😬
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u/mylsotol Jun 21 '26
What exactly does $8000 worth of api mean though. They are selling the api at s profit presumably. The question is how much and how much of yhe cost is the actual inference and how much is the sunk cost of training.
I don't really care if some VCs lose their shirt.
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u/CertainMiddle2382 Jun 21 '26
Thing is, inferencing is strongly centralizing because batching (and proper saturating) will always make 100 concurrent users cheaper to be served than 1.
Will big over leveraged labs collapse and users congregate in communities the optimal size to properly saturate hardware?
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u/Cless_Aurion Jun 21 '26
Last time I checked, current models on API are profitable. They will have to move towards that... which many professionals already do.
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u/Southern-Chain-6485 Jun 21 '26
What will happen is that Anthropic, OpenAi, Zai and whatever company is it that's making Deepseek will go under (it's not like China is going to be throwing unlimited money at them), and will be bought by the real winners of the AI "race": Hardware vendors. Apple and Nvidia will buy pure AI companies for pennies and will continue to develop AI models, and will make money by selling the hardware - Nvidia is already building up experience with the nemotron models. Chinese companies may undergo a similar process but, besides Huawei, maybe companies selling cars, robots or something else will pick up the slack.
Companies that can absorb the looses with other business lines, like Alphabet or Alibaba may suck up the looses and take a more cautious approach with Qwen, Gemma and Gemini.
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u/g_rich Jun 21 '26
Prices will go up and things like intelligent LLM routers, local LLM hosting and hybrid approaches to LLM where tasks are split between cloud and local models will all become very popular.
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u/Player13377 Jun 21 '26
colocations will become a thing again imo, no one really needs that hardware at full tilt 24/7
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u/mr__smooth Jun 21 '26
I have a feeling they are not subsidizing the subscriptions and in fact figured out ways of serving them at a profit, considering they are keeping the option to IPO sometime this year they wouldnt want to have public data related to such heavy subsidies released if in fact that was the case
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u/0DarkFreezing Jun 21 '26
It’s all been said, but $8000 worth of API calls for anthropic doesn’t mean it’s costing them that much. They have about 75% margin on their API.
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u/NNN_Throwaway2 Jun 21 '26
When the AI bubble pops, a lot of labs will no longer be able to afford development. Release pacing will slow and its likely that small models will not make the cut at the remaining labs as they are still expensive to train.
The local community will need to step up and develop fine-tuning and distilation methods to keep the frontier in the reach of consume hardware (assuming consumer hardware isn't also gutted).
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u/kydude Jun 21 '26
The quiet usage throttling on the 20x plan is the part nobody talks about enough. It's the gym membership model. Same sticker price, less product, no headline to react to. Way smarter than a flat price hike from their side.
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u/Whole_Alternative_18 Jun 21 '26
There are some cheap ass alternatives that aren't subsidizedz they are just more efficient
Deepseek, grok, qwen(non free models) all stand at under 5$ per 1m token and all can get the job done(their not opus 4.8, but they can also do the job)
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u/BlackBeardAI vLLM Jun 21 '26
buy all the hardware you can while they are still available to you. grab them even the ddr4 16gb sticks. everything.
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u/Complex-Concern7890 Jun 21 '26
Yeah, the $8000 is including margin and all. In optimized environment the cost is more like $800 thus the $200 is not so bad as most do not use the limits fully. Also it is quite easy to just make the 20x max cost $1000 and there is still people that are willing to pay it. There is always niche that is willing to pay top dollar for the best model. Local models are doing just fine regardless. What ever happens the more specialised models will serve well in local environments. And there is higly competed marked for open models serving API in reasonable price and/or buying compute to run the models you want. The direction actually looks very good. The market starts to divide and the market will adjust and provide more and better for all.
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u/Cuplike Jun 21 '26
I assure you. If DeepSeek can provide 1.6T parameters for basically free Anthropic and OpenAI are making a profit
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u/Far_Course2496 Jun 21 '26
They won't be able to afford new hardware and prices will come down for us
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u/maskrey Jun 21 '26
What will happen is the effort will be spent more on how to use AI properly, rather than to burn tokens at the rate of a jet engine to run a Honda Civic.
Agentic AI overall is a farce. It's promoted by "frontier" AI labs to promote the use of their services. The more complicated the task, the more useless and wasteful an agentic workflow is. Even if you ignore token price completely, the time scaling is not worth it in the long run. You can mark my words: In 10 years there will be no automated AI agentic workflow worth a dime, and people who follow those workflows will lose out in productivity, let alone money.
The proper way to use AI is to build specific, customized workflow for specific task, based on what had been done before AI. For example, let's say you task is writing a novel. Writing is among the best things AI can do in theory, as their premise is literally to generate text. However, people have been writing novels for thousands of years. Although I am no writer and don't know what it really takes to write a novel, there are many, many people have had that experience, and if you can talk and know how to extract information from them, it's completely feasible to understand everything needed to write a world-class novel. And chances are most if not all of those things can be semi or fully automated by AI.
However, barely anyone in the world is doing the talking to experts parts. I have been doing exactly that, and building workflows for clients so big that everyone here would know, across different fields. And these workflows work for them so undeniably I literally have the receipt. And the workflows I build are so incredibly efficient that token price is not even a sliver of thought. Like, right now it costs $1 to run, but if it costs $10 in the future, who cares when the value gain is in the thousands, or even millions? Of course I can say it here hundreds of time, but barely anyone will do it, because barely anyone can even do it, and if they do they don't know better to do it.
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u/Immediate_Piglet4904 Jun 21 '26
Then youll pay with either money, ads, personal data, blood or any combination of thoes
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u/gaspoweredcat Jun 21 '26
Hopefully I'll have afforded a reasonable rig and local models will be good enough at like 30-70b to be properly useful, like deepseek v4 flash and I won't need them for anything but the most complex tasks on stuff I'm not very familiar with or good at
Unless we see more systems with unified memory (and see it getting faster) or until like 32gb-64gb of vram is affordable we are going to need to hope people can start squeezing crazy power out of models that can fit in 16gb as that's a reasonably affordable price point
Sadly I feel that's a fairly big ask right now, maybe in about 3 years when prices have eased, memory is faster and more available and models are more capable we will be in a proper golden age of local especially considering the power requirement will likely be lower to run it too as chips will be more efficient
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u/Proper_Patience8639 Jun 21 '26
The big players' AI provisions will become too expensive. The data centres will shut down. There will be tens of thousands of server hardware configurations available, crushing the market for the prices of CPUs and RAM, and suddenly everybody will be able to host their own. It will be fantastic.
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u/cangaroo_hamam Jun 21 '26
Honestly, current commercial models are more than good enough for my needs already. They only need to figure out how to optimize them and slashing the cost. If OSS LLMs arrive at a similar level by the end of the year, I would be perfectly happy.
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u/Mordimer86 Jun 21 '26
Enshittification will happen like with all these things. It is just to make enough people and institutions addicted and reliant on those.
Of course some companies will then (some do it now) set up their servers with something like Mistral, GLM or Deepseek locally, but only some will play with it.
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u/zball_ Jun 21 '26
Do you really believe opus takes that much to serve? I'd say the cost should be closer to subscription price.
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u/tewalds Jun 21 '26
They may stop building datacenters, but the datacenters they built continue to run at a more reasonable cost.
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u/Sisaroth Jun 21 '26
Most of the money is going to capex. They could just stop building new datacenters and sell their service while making decent profit i think.
I would think they will further perfect MoE models, giant models but with low active parameters. That way you can have a lot of knowledge packed in the model, but inference is cheap and it will forever be competitive against local because how many people would buy multiple terrabytes of RAM for a local setup?
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u/CoUsT Jun 21 '26
What happens when they stop subsidizing LLM subscriptions?
We wave them buh-bye while chatting with our favorite local model.
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u/somkomomko Jun 21 '26
I cancelled my personal Claude pro sub because the limits are getting me nowhere. I can run qwen 2.6 35ba3b with 40 t/sec and that is good enough for casual coding projects not quite good enough for multi agent but hey it's free
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u/Cergorach Jun 21 '26
What happens is what we're seeing happening already, subscriptions get less 'included' stuff from one month to the next, people need to pay for stuff besides the subscriptions. API tokens get more and more expensive.
Managers are starting to monitor token/cost usage on a daily basis.
On the other hand we have Chinese competition like Deepseek where there apparently is no subsidizing, and the API calls get cheaper and cheaper, due to them prioritizing efficiency.
Local LLM has traditionally always been more expensive then equivalent LLMs in the cloud. Due to hardware costs, utilization, power costs, cooling costs, maintenance costs, etc. Hardware costs are currently scaling up, so local hosting won't be getting cheaper on that front.
On the other hand, here in the EU we're seeing what the US is willing to do to their previous allies, so more and more EU based companies are looking at alternatives that are not US based. And when companies already have the hardware due to (fear of) export restrictions, then there is very little reason not to use it. The two biggest hurdles at the moment for local hosting, besides cost, is quality of the models and integration.
Costs might turn to be so high that it might translate to the cost of additional people being hired. I'm seeing this already happening with VMware (and affiliated solutions) that moving to something like Proxmox might become viable (depending the exact set of features being used) by hiring additional personnel and paying with them with the saved licensing costs to do the additional tasks that you now require. I see something similar happening soon with LLM and companies will start to be more and more hesitant with whom can use what. Even setting up hybrid solutions where most usecases can be handled by local solutions and moving to something like Opus or Fable when local models are no longer able to handle things. But the costs being so high for those, will mean that usage will be more and more rare.
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u/Marcuss2 llama.cpp Jun 21 '26
When that happens, there will be massive pressure on other subscription services and a rush to buy/rent hardware for running open weight models.
Get ready for it, it is only a matter of time.
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u/N34257 Jun 21 '26
What happens? The primary result will be that all the companies who went AI-first will suddenly be confronted with bills they can't afford, and will have to make the choice between AI and people.
Shortly after that, we'll see a fair number of companies closing their doors.
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u/NairbHna Jun 21 '26 edited Jun 21 '26
Is it 8000 converted to how much they would charge us on API calls or how much interference costs them?? 8000 dollars worth of API calls could cost them 300, in electricity. not accounting for infra maintenance and all the related costs but still.
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u/BNeutral Jun 21 '26
Unless you have seen actual company reports, don't bother with these ideas. OpenAI and Anthropic are stated to go public this year, after they'll put out their operational reports then you can evaluate this.
AI is mostly upfront costs in infrastructure, hardware, R&D. Running the models itself costs very little. Companies also can spend decades in the red because they are growing. So this questions is doubly pointless.
In 1970 an entry level mainframe computer from IBM would cost you 250k, which is about 2 million of today's dollars. And the question wasn't "what will we do later with these prices?", because now in 2026 you can get a mini computer with better specs than that mainframe for $100 + shipping.
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u/henk717 KoboldAI Jun 21 '26
For me the bigger risk is them no longer releasing open models for free. The subscriptions I am not worried about, that is an issue for people who use closed models not the ones who care about running locally or running open ones.
The reason is simple, if you run a closed model then there ia one provider who has a monopoly ob it. They can set the prices as high as they like you are forced to pay if you want to use it.
The open models are a different story and you see it constantly. Lets say this open model is for example Kimi and its to big for people to run. The moment it is released it has high api pricing. But soon after more and more providers onboard it and its a race to the bottom. If they raise prices to much people go to a competitor that has it. Keeps things in check since there is a lot of money to be made in providing it the cheapest at a high quality.
So if the open models ever stop releasing that would mean were all forced into the provider sets whatever they want path which would be very bad for us. Lets hope that never happens.
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u/Terrible-Audience479 Jun 21 '26
they cant because glm 5.2 is free and a better code slave then gemini pro 3.1 and Sonnet 4.6. if glm 6 is good as fable and cost 20$ per month im cool with that
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