Anthropic updates their terms to verify age or identity

What about local models do you find preferable?

I guess "starting to find them preferable" suggests to me you think they work better, but this is surprising to me so I think I may have misunderstood, so I ask!

Like you're saying they work better than the proprietary models (in what ways?), or you find them mostly good enough and prefer the privacy or cost, or what?

What kind of machine is it running on ?

What is an "ephemeral" model in this context?

From a privacy perspective, your objective is to stay away from people who have interest to snoop on your conversations.

So from the perspective of your teen, they would benefit from using z.ai or ChatGPT or Claude, etc, rather than the local server where you can see all the conversations.

What uncensored model do you recommend using ?

How many tokens /sec?

> I run an uncensored, ephemeral model for my own use and it's an entirely different experience than anything you can pay for.

Dont. Goon. To. LLMs

The government is not going to enforce this, the game theory does not work in their favor.

The SCOTUS has made it exceptionally clear mathematics and software are protected by the First Amendment. The Atomic Energy Act of 1954 tries to make a very narrow exception for nuclear weapons, but

1. The law has never been challenged in court for being unconstitutional, and

2. It doesn't apply to model weights

Any attempt by the government to suppress open models will meet legal challenges on the grounds of (1) or (2).

Congress could amend the act to include model weights, but that won't prevent legal challenges on the grounds of it being unconstitutional (which it is).

Only if you let them.

How could it not? I get the whole fear of AI making robots and going anti-human, but after using the tech for a few months now that seems too absurd.

Maybe one of those trillionaires could help for a bit before leaving to make his own AI model, too.

And we are definitely not going to put our users on a watch list DB and send their data to the government?

And how do we prevent Chinese companies from training on our open AI models and offering their models for free?

i’d really love to be wrong, i don't think that the economics of it would let it happen.

the potential of wealth creation with AI is so high, and also the fact that research, pre-training and inference is so expensive that, that any open-AI would eventually become OpenAI.

We could all chip in

There is an understandable gap between the capabilities of closed models and those of open models. The current difference is primarily expressed in the cost of hardware necessary to sufficiently run a exactly comparable model. A single higher end graphics card running on your average gaming computer, is capable of running small to medium models that compare with those of their lab-born counterparts in the small-medium range. But the heavyweight models are still outside the realm of possibility for all but the most well-funded individual.

However, I would highly suggest more people experiment with these smaller models. They are incredibly capable in many ways that many people dont realize.

The perceived capabilities of the larger models are also much less the result of the model having more parameters/training cycles, but rather that they are being run through well-made harnesses, something which the open-source community is rapidly approaching with near-peer solutions of their own.

In short, much of the gap between between open-weight models and the larger proprietary models can be considered more of an issue of perception and not an issue of capability. There is a fundamental gap economically, but not so much in capability. The open source community is rapidly closing the gap on these larger labs, especially thanks to the amazing research being freely given openly by well funded chinese labs.

> I mean from a financial and sustainability standpoint, assuming they’re equally powerful as their proprietary counterparts.

Presently they trail SOTA by about 6-12 months, not on par (average across everything they do).

DeepSeek V4 Pro with Max reasoning is very affordable even if you pay per-token, this month I pushed about 486 million tokens through it (I will admit that >95% was cache hits, for agentic development pretty typical) and it cost me about 8 USD in total. Meanwhile with Opus or even Sonnet if I had to pay API prices, I would be a more sad camper. That model makes a lot of stupid things though, so not ideal.

Meanwhile GLM-5.2 that came out is also quote capable and is near Opus in many tasks, all while their coding plan is more cost effective than Anthropic's: https://z.ai/subscribe

I will still stick with Anthropic but consider downgrading from Max 5x to Pro which will change the monthly expenses from around 108 EUR down to <20 EUR (they have a discount too if you pay for a year up front), and probably get the yearly GLM Pro plan which should decrease my yearly expenses from around 1300 EUR total to about 750 total EUR while still giving me a fairly decent setup.

For the consumer, that is doable and practical.

For the people actually running these models, who knows - at least DeepSeek and others are trying to make the models more efficient so the numbers are more feasible.

Also have run Qwen3.6 35B A3B on prem and it kinda sucks. Way better than models that size a year ago, but still lags behind Sonnet and also DeepSeek V4 Flash due to the size limits. Plus to even run myself I'd need a pretty beefy setup, most likely a pair of Intel Arc Pro B70s with 32 GB of VRAM each that I could still run off of my PSU but the actual model output would be kinda bullshit and I'd have to spend an unpleasant amount of time fixing it.

Sort of. A full trillion-parameter model needs about $300k of server hardware to run in and a lot of electricity, making it feasible only for very wealthy individuals, but quite practical for businesses and institutions above a certain size...although they in turn would typically gatekeep access.

You can drastically reduce the requirements by running models at a lower bitrate, which somewhat reduces accuracy but not that much - think of the difference between an MP3 vs uncompressed audio. With this and other tricks, you can get high end models down to a size where they can be run on a high spec desktop workstation affordable by an individual or small business.

Obviously I'm heavily oversimplifying here. I think a useful parallel is to consider situations from the past where you would once have required corporate budgets equivalent to the price of a house to run a large database, but over time it became accessible to anyone with the requisite expertise and relatively affordable hardware.

See my comment to parent. I've been using local LLMs for practical, personal tasks for a few months now very successfuly.

You can run fantastic local models if you have either:

- M-series Apple device with ideally >= 24GB of VRAM

- RTX [345]090 GPU

I'm fortunate enough to have both and use an M-series laptop as basically a persistent server (I don't use it much and when traveling typically just use my work laptop). My desktop doesn't act as a persitent server but I fire up llama.cpp on it all time for quick chat sessions.

If you have one of the above devices and can dedicate it as server there are additional layers of tooling you can use that dramatically improve the experience. In particular Open WebUI allows you to add tons of useful tools (image gen, web search, code eval, etc), and agent harnesses like Hermes can make the current gen small models very capable. I have an agent in chat on my phone that basically handles all the sys-admin for the server it runs on.

I'm also curious, specifically about the cost of training vs inference, and comparing that to other industries that can have high R&D costs. My instinct says that open weights aren't feasible because of the obvious issue where there is no incentive to develop your own model rather than just taking someone else's model. However, I could see a scenario where a hardware company designs a model that is open weights but optimized strongly for their own proprietary hardware, cutting their costs of inference low enough to be competitive with a hypothetical other company that doesn't have any R&D expediture.

It depends entirely on what you want to do and think is feasible. Small models can almost certainly run on the computer that you already have. They can do good tool calling.

Yes they are you can use Qwen, DS4 Pro and GLM 5.2 if you have the hardware to do so.

They are not SOTA in various ways but they have better economics.

If attractive, cloud providers could develop open models with their own investment, and sell hosted access as a business model. While Google checks these boxes, I haven't seen a Google much marketing focus upon their open models (Gemma) coupled with hosting. groq could conceivably train its own models, but groq's business model hosts open models (GPT OSS, Qwen 3, Llama 4 are currently their prominently advertised models on their site... which seems out of date to me) trained by other organizations.

I hope/wonder if it will go the way computers did. We may learn to more effectively build RAM or parallel compute, and use it more effectively, in the coming decade in such a way that we can democratize more and more like we did with processors to the point that they're ubiquitous.

Is this satire? I really can't tell.

>This is a serious competitive advantage

Given they have laughable uptime and I have yet to find a useful project mostly written by claude... I doubt it.

These things are always a slippery slope. They rarely, if ever, achieve their safety goals but they almost always achieve the goals of the corporate interests to garner further data for advertisers and increase surveillance of the populace by the government through proxies that buy said data and then sell to the government.

I think the general assumption is that it only aids in surveillance.

It is not merely showing proof of age

It is using the proof of age requirement to require a much larger ask -- full proof of identity

Age verification could be done with any of a variety of mathematical systems showing you have a proven age-valid ID but not revealing your identity. But no one is suggesting they build and use such a system.

You could say the same about China, where only 7% of people can vote. In the US, 72% of people can vote.

Why is that any different? What’s to stop that company sharing information with the government?

with sufficiently many public/private partnerships, what's the difference?

The point is that you're all shitting on China 24/7 while not recognising that you're slowly but surely building something very similar at home right now

Also the Chinese social credit system is not what most think it is - https://en.wikipedia.org/wiki/Social_credit_system#Misconcep... .

Because we dismantled class and caste. It’s a “meritocracy caste” system (nevermind that you likely get huge advantages based on your origin)

It’s funny, 30 years ago the argument was the exact opposite: China opening up and doing business with the rest of the world would force them to liberalize.

That has been going on for a while AFAIK

> For better or worse, those are hard sells in the countries you mentioned.

For good reasons, sometimes. The "all automation is good automation" sentiment on places like HN isn't shared as widely outside this tech bubble. There are very real concerns with historical precedent that only those at the top will benefit from the automation, which is overall bad for society (unless you're a hardcore capitalist and/or one of said capital owners).

For better or for worse, not all nations subscribe to the competition treadmill.

GLM-5.2 meets my needs for "thinky" tasks, which for me is code and documentation reviews, technical chats and rubber ducking. (I've tried agentic coding and gone back to writing by hand; besides ethical and skill atrophy concerns, I mostly do hardware design and have not been satisfied with any model's RTL output.) API rates are cheaper than Haiku, with benchmarks around Opus 4.6. I've managed to run GLM-5.2 at home, very slowly, but still neat that this is possible. I personally find it less grating to talk to than Opus.

I use a local Qwen3.6-35B-A3B (@ Q4_K_XL) for my documentation search harness. It works well for its assigned task, which is:

- I dump in a bucket of PDFs and/or source code.

- I ask a question.

- Qwen greps, fuzzy-searches, views rendered PDF pages to check diagrams, possibly gives up and reads everything, and possibly gives up on that too and writes its own scraper with PyMuPDF in a Pyodide sandbox.

- Qwen gives me an answer consisting mostly of citations and links back into the source material.

This approach with local Qwen can extract useful answers from the Armv9-A manual, which at 17k pages is possibly too big for any context window. Qwen has just enough knowledge baked in to know what to search for and understand what it's looking at. A more knowledgeable model would be a waste because even Fable makes shit up, and I want citations, not hallucinations.

DeepSeek v4 Flash gets an honourable mention: somehow all three of fast, capable and cheap. Zero-data-retention providers are available for both GLM-5.2 and DSv4F. I trust OpenRouter ZDR about as much as I trust Anthropic ZDR, since I can audit neither.

Overall I don't miss my Claude subscription, but take what I say with a grain of salt. I was just a Pro subscriber, not a heavy user like some other folks here.

Probably this stuff which caused backlash:

https://www.wired.com/story/anthropic-responds-to-backlash-o...

They aren’t, but we’re riding an exponential here. It’s like saying ‘you can still build a computer out of transistors’ in 1976 - as true and irrelevant today as it was then.

The British company doing age verification for Discord got hacked and the hackers got about 70k user identity documents. Discord claimed that the scanned documents would be deleted after verification. Surprise! They were not deleted at all.

https://www.theguardian.com/media/2025/oct/09/hack-age-verif...

What about a signed attestation of your identity based on your passport? I don’t particularly want a future where we need to present ID for any online service, but for certain high-risk services (e.g. financial services, medical records, government portals) I’d rather a proper identity system than cobbling something like this together.

As an aside, when traveling internationally it’s not uncommon to need to provide your passport information if you want to get a sales tax rebate. I’ve never purchased something expensive enough abroad to bother with it.

I'd have a problem with that too. In fact, I'd have a problem not being allowed to use cash.

I am deeply inconsistent on this.

Maybe they should. It would be far less intrusive for venders who wish to sell age restricted goods to simply have it built in like that.

neither does my face but that isn't stopping them, so what exactly are we doing here