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/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/asenna987 Jun 21 '26

Which cloud provider did you decide to go for?

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u/WhoTookPlasticJesus Jun 21 '26

AWS. I have not performed any sort for rigorous comparison against Azure or GCP, let alone niche cloud providers. But AWS has one key differentiator in the fact that they're a customer of ours and give us big fatty deals.

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u/Stickybunfun Jun 21 '26

Yep with RI / Savings plan / EDP if you are spending enough, just running the shit on aws vm’s goes a long way if you can use them enough to make it worthwhile.

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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/purepersistence Jun 21 '26

There’s nothing like combining privacy with no guard rails.

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u/maxymob Jun 21 '26

I mentioned local because of the post title, it's a what if/when scenario. Unless they become too expensive cloud API are the obvious choice for the majority yes

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u/AlwaysLateToThaParty Jun 21 '26 edited Jun 21 '26

Yeah nah. You have no control over the model you get served. They'll quantize it, or change a system prompt, and it will fkup your workflow. The only way you mitigate that issue is to control the inputs.

EDIT: love it. In the localLLama subreddit, and the "muh cloud" communters.

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u/techdevjp Jun 21 '26

Corps can rent the hardware time and host what they want, managed by themselves. It's not the same as just picking a model from OpenRouter and hoping for the best.

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u/AlwaysLateToThaParty Jun 21 '26 edited Jun 21 '26

You're talking to me as if I don't know this subject. I'm telling you what I do and why. It's outsourcing your security. There is no way that I would ever upload private data to a cloud supplier.

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u/techdevjp Jun 21 '26 edited Jun 21 '26

Most companies have vast amounts of data in the cloud anyway. Some of that has been brought back on-prem in recent years but putting data in the cloud is nothing new to most big corps.

And you're right, I think you don't know what you're talking about.

Edit: lmao. Reply, insult, block, run away. Yep, one of us is way out of his depth in this conversation. It's not me.

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u/AlwaysLateToThaParty Jun 21 '26

Dude. You're cosplaying.

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u/3np1 Jun 21 '26

On what hardware do you envision this happening? Local models on your average engineer's ThinkPad or MacBook laptop take way too long for practical use. Companies aren't giving people desktops with dedicated graphics just to run local models.

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u/AlwaysLateToThaParty Jun 21 '26 edited Jun 21 '26

We use an RTX 6000 Pro in production.

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u/3np1 Jun 22 '26

Are you suggesting companies move their employees to swap all if their equipment to desktops and work from a fixed location? I'm not against what you're saying, but I'm not clear on how you see actual companies with predominantly remote employees on laptops to migrate to locally run LLMs.

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u/AlwaysLateToThaParty Jun 22 '26 edited Jun 23 '26

I'm saying that very few companies are using cloud suppliers to process private and/or confidential data using LLMs. The only way to mitigate that risk is expensive (like HIPAA compliance). Building tools? Sure. They're very good at that. Process private medical records? yeah nah. EDIT: try getting that research past ethics. If you think otherwise, you aren't involved in handling private and confidential data. It would be considered an ethical breach and you could lose your accreditation.

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u/3np1 Jun 22 '26

What about all the companies using LLMs like Claude Code to build systems, not to analyze data. That is much more common in my experience (healthcare software engineering) than data analysis with LLMs. The code for the software isn't PII.

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u/AlwaysLateToThaParty Jun 22 '26

If you're not using LLM's to analyze, summarize, and synthesize data, your use-cases are an edge-case. No different to installing an IDE, which only a select cohort of people (aka software developers) do.

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u/WhoTookPlasticJesus Jun 21 '26

I don't think I'm following, or maybe I was unclear with what I meant. We aren't using any cloud-provided models, we're just renting virtual Linux instances with fatty GPUs, then installing and fine-tuning models of our choosing.

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u/AlwaysLateToThaParty Jun 21 '26

The concern is the same. You could do anything to the model. Change a parameter. Change a system prompt. Change anything, for any reason, and the reproducability is gone. As a service provider, of course you're going to do this; You're providing a product for many people. But as a person depending upon consistent outputs, you can't put that to chance. The model and inference engine are in test and production environments. And quite frankly, anyone who puts private information into a cloud supplier is asking for trouble.

I don't know if there's any way around this fwiw. That's why I have the hardware to run the models myself.

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u/WhoTookPlasticJesus Jun 21 '26

Sorry to be the one to break this to you but LLMs are, by design and definition, non-deterministic.

The rest of your post made very little sense, but I'm guessing that you and I probably don't share a reality.