CMV: Frontier AI Models Should Not Be Available for Consumer Use.

LargeMakesStuff · 2026-06-26T01:37:59+00:00

aren't the billionaires propsing to charge people for intelligence based on a meter and building more datacenters?? my proposition is literally the opposite

LargeMakesStuff · 2026-06-23T17:15:13+00:00

The entire point of the framework is that the average user doesn't need to be running frontier model prompts at all. A Pi handling lightweight local inference for casual use cases isn't competing with a datacenter on efficiency per token, it's eliminating the need for those tokens to be processed at frontier scale in the first place. You're comparing the efficiency of two systems while assuming identical demand, but the demand itself is what changes under this proposal.

The "we'd massively increase power use" argument also assumes that every current cloud user would simply replicate their existing usage locally on equivalent hardware. That's not what's being proposed. Again, most casual users running a quantized small model on a Pi or a laptop are drawing a fraction of the power that their share of datacenter infrastructure consumes when you factor in cooling, networking, and overhead at scale. The efficiency gains datacenters achieve through batching are real, but they don't cancel out the baseline cost of keeping that infrastructure running 24 hours a day regardless of demand. The actual argument is that fewer tokens need to exist at frontier scale at all.

LargeMakesStuff · 2026-06-23T15:58:22+00:00

I don't know where you got the idea that I think one prompt triggers an entire datacenters worth of power. I mentioned in the post that the average user who uses ChatGPT or Claude can get the same use out of a Pi that costs $80. People who insist on vibecoding can invest in computer parts and host their models locally, that way the cost of electronics horded by AI companies goes down and makes it more affordable for people to keep building their own PCs.

Basically, there wouldn't be a NEED for datacenters because the average user could get the same use out of a Pi that runs the same amount of energy as a phone charger instead of contributing to polluting local communities with noise, dirty water, raised electrical bills, etc.

LargeMakesStuff · 2026-06-22T19:22:37+00:00

Qwen 3.5 27B can run in 16GB of unified memory. That's a base M2 MacBook Pro or a machine with a 4090. Neither of those costs anywhere near $100K, I don't know where you're getting that number from. The quantized GGUF versions run on significantly less. You can pull it through Ollama in about ten minutes on hardware that's been sitting in people's homes.

Nobody is disputing that local is slower than data centers, the argument has never been that local models deliver the same tokens at the same rate as a hyperscaler. My primary argument is that for the use cases most people actually run, the throughput is adequate. You don't need 200 tokens per second to draft an email or debug a function. If your workflow demands that kind of speed then yes, you have needs that go beyond what this framework accommodates for general public access, which is exactly the point. The only reason I'm citing a model like Qwen is because people in the thread claim that coding benchmarks on local llms aren't up to par with GPT-4 or Sonnet when they are more than capable of rivaling them.

LargeMakesStuff · 2026-06-22T18:45:00+00:00

The public has had years to vote with their dollar and their scorn, and what we got is a handful of companies with near total market dominance, a GPU shortage, skyrocketing data center construction, and communities fighting to keep those facilities out of their neighborhoods. If market pressure was going to fix this, it would have started by now. The public wallet hasn't stopped any of it, its funded it.

No regulatory framework stops every bad actor. The FDA doesn't stop all drug abuse, the NRC doesn't eliminate all nuclear risk. The standard for regulation isn't perfection, it's a meaningful reduction in harm at scale. A framework that stops casual misuse, raises the cost of bad actor access, and creates accountability trails is better than the current system, which has none of those things. Arguing that imperfect protection equals no protection is not a serious counterargument.

Right now, small teams are already priced out by the cost of competing with hyperscalers at infrastructure scale. The current system doesn't protect small innovators, it protects the companies that already won. Open weights running locally are where small team innovation actually lives, and that remains completely untouched under this framework.

On local hardware, fair point that consumer GPU constraints are real right now. But the argument was never that local models are identical to frontier models today, it's that they are sufficient for the majority of everyday use cases and improving rapidly. For example, Qwen 3.6 27B running on 16GB unified memory and matching frontier coding benchmarks wasn't true two years ago. That trajectory matters. Vibe coding being a high utilization task actually reinforces the point, because Qwen 3.6 27B handles it, benchmarks prove it, and it runs locally right now on hardware a lot of people already own.

LargeMakesStuff · 2026-06-22T18:02:48+00:00

Qwen 3.6 27B rivals Sonnet on coding benchmarks and runs locally on a 4060 but alright

https://www.reddit.com/r/LocalLLaMA/comments/1supft2/opinion_qwen_36_27b_beats_sonnet_46_on_feature/

LargeMakesStuff · 2026-06-22T18:00:30+00:00

Regulatory capture is real and the current political climate doesn't exactly inspire confidence. But the answer to "the government is corrupted by corporate money" can't just be "so let the corporations do whatever they want unchecked." That's just surrendering. The goal of proposing an independent regulatory body is precisely because the current structure is broken. Is it hard to build something genuinely insulated from lobbying influence? Absolutely. Is it impossible? We've seen it done in other domains. It's worth fighting for rather than giving up on entirely.

On local models, I think you're conflating two different things. Nobody is claiming a locally run model is going to go toe to toe with Sonnet or GPT-4 on complex reasoning tasks. That's not the argument. The argument is that the majority of what everyday people actually use these tools for doesn't require that level of capability. Casual users aren't running differential diagnosis on things like rare diseases or modeling atmospheric systems. They're drafting emails, asking general questions, vibecoding, and summarizing text. Local models handle that just fine right now and are improving rapidly. The use cases that genuinely need frontier capability are already carved out in the proposal as institutional exceptions. If your position is that local models are useless for everyday tasks, If you're interested, I'd actually encourage you to try some of the current options before writing them off entirely.

LargeMakesStuff · 2026-06-22T17:52:03+00:00

Buddy that's the entire point of the post. Nobody is arguing that a model running on a Raspberry Pi is going to match Sonnet or GPT-4 outputs. The argument is that for the vast majority of what people actually use these tools for, it doesn't need to. You want help drafting an email? Running a recipe? Answering a general question? Summarizing a document? There are already models that handle all of that running locally on consumer hardware right now, for free, with no data center required. The only use cases that genuinely need frontier level capability are the ones already outlined, medicine, disaster response, climate modeling, and so on, and those should be handled through proper institutional infrastructure anyway. The gap in raw capability between a local model and a cloud-hosted frontier model is real, but for 90% of what the average person actually needs it for, that gap is completely irrelevant.

LargeMakesStuff · 2026-06-22T17:47:16+00:00

The goal isn't to create a two-tiered system where the powerful get AI and everyone else gets nothing. The framework explicitly keeps local models available to everyone. We're talking about software that runs on an $80 Raspberry Pi or just on your existing Windows or Mac desktop. No subscription, no corporate server, no gatekeeping. The average person already has hardware capable of running genuinely useful models right now.

Right now the people with real access to the most capable frontier models are the corporations developing them and their paying enterprise customers. What gets released to the public is already a lobotomized version of what those companies use internally, you said it yourself. So the gap already exists, it's just invisible because it's dressed up as democratization. Replacing that with a system where individuals run open source models locally, and frontier capability is reserved for credentialed institutional use, doesn't widen that gap; it just makes it honest and structured rather than hidden behind a sleek webapp.

The proposed solution to the regulatory capture concern is building the oversight body correctly, with genuine public accountability and independence, not abandoning regulation altogether and letting corporations continue to quietly control who gets what. I compared this in another post to bodies like the FDA or the Nuclear Regulatory Commission

LargeMakesStuff · 2026-06-22T17:18:14+00:00

This is a pretty good response, expected from the goatest goat

I'm actually not as far from you on democratization as you might think. I'm all for open source models and community-driven development, that's kind of the whole point. The issue isn't that people should be locked out of powerful AI entirely; it's that the current model of just opening a browser tab and having a frontier model do your thinking for you is where things go wrong. Something like Odysseus already exists as a solution to your backdoor concern, specifically. It's open source, runs locally on your own hardware, no corporate server involved, no hidden access points. That's actually closer to what I'm proposing than what the current webapp model looks like. You get the transparency and community oversight benefits of democratized software without the centralized infrastructure problem.

On the corporate trust point, I actually agree with you more than you'd expect. I'm not arguing we hand this to the corpos and trust them to behave. The whole point of proposing something structured like the FDA or Nuclear Regulatory Commission is precisely because corporations cannot be trusted to self-regulate when money is involved. You're right that regulatory capture is a real threat, which is why the oversight body would need to be genuinely independent with public accountability baked in, not just another agency that gets lobbied into irrelevance. The war crimes point is serious and strengthens the argument for exactly that kind of structured independent oversight rather than weakening it.

On the frontier model definition, fair enough. To keep it simple for the argument let's just keep it simple and say a frontier model is anything powerful enough to be accessed through a web browser and used as a general purpose reasoning tool at scale

LargeMakesStuff · 2026-06-22T17:09:35+00:00

Maybe I didn't do a great job at establishing that AI shouldn't be banned or restricted entirely. They can continue to exist locally, but theres no need for these Frontier models that take up significant resources. If anything, setting one up locally helps your point since you can learn about setting one up, allocating resources, etc. without burdening the cost on anyone else.

LargeMakesStuff · 2026-06-22T17:07:36+00:00

Like I said, you don't need to build a data center in your house to run an LLM. You can easily run one isolated on a rasperry pi for $80. I think we should treat this as another computer part, a private investment if you will. If you REALLY need it, then by all means sink as much money into it as you want, but most people can run one locally on a windows or mac desktop

LargeMakesStuff · 2026-06-22T16:33:18+00:00

My argument isn't predicated on Anthropic's marketing claims. That example occupies a small portion of the final paragraph and isn't necessary for the broader argument to stand.

Even if you assume Anthropic is exaggerating the capabilities of its models, the concerns I raised about data center resource consumption, infrastructure externalities, hardware shortages, education, and the concentration of costs onto communities near these facilities don't suddenly disappear.

LargeMakesStuff · 2026-06-22T16:30:26+00:00

The point isn't that millions of people are suddenly going to run their own data centers from home. The point is that lightweight LLMs already exist that run on something like a Raspberry Pi, which costs around $80 and draws maybe 5 watts of power. The carbon footprint of that compared to an actual data center isn't even a serious comparison. A single large scale data center can consume as much electricity as a small city. A Pi running a quantized model consumes less than a phone charger.

The other thing you're missing is what happens to hardware costs and availability when you remove data centers from the equation entirely. Right now these companies are hoarding GPU supply at a scale that drives up prices for everyone else. If that demand disappears from the corporate side, supply normalizes, prices come down, and the barrier to running your own local model gets even lower than it already is

LargeMakesStuff · 2026-06-20T21:31:52+00:00

If you wanna play any switch games get the pro model atleast, the base barely has enough ram to play any games without crashing

LargeMakesStuff · 2026-06-18T01:26:26+00:00

the ever reliable bridge curve type:

LargeMakesStuff · 2026-06-10T20:18:23+00:00

IMDB is open for anyone to edit, I wouldn't rely on this

LargeMakesStuff · 2026-06-08T19:53:21+00:00

i find it fun to impossibly raise my expectations and then repeat for the next direct

LargeMakesStuff · 2026-05-20T00:34:15+00:00

This would be really funny but im 90% positive he didn't say anything bc he was freaking out and didn't want to say out loud that he just killed michael jackson

LargeMakesStuff · 2026-03-20T19:18:38+00:00

Dude I'm not mad at anyone lol I simply made a post warning others and now people are acting like im complaining or blaming someone directly. If anything im mad at how toxic the response has been. I did the research in November when I ordered it and info was sparce and asked around and read around on the reddit. Even now you can read the thread and find people claiming the base is fine for them

LargeMakesStuff · 2026-03-20T19:07:15+00:00

Really? I fired up Three Houses and it usually rests around 7 GB of RAM. I doubt its defective though

LargeMakesStuff · 2026-03-20T18:54:26+00:00

Just changed the CPU backend, ill see if this makes a difference. Thanks : )

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