> does the users who use Anthropic switch over to those even if they're available even as hosted models?

I'm currently spending $200 for Claude. That's around my maximum that I can afford. I could stretch that to $500 I guess. But I saw reports of people spending tens of thousands of dollars with Claude API. That's certainly outside of my budget.

So if/when Anthropic decides to stop subsidizing subscription (if they ever do that thing, I still not sure about that), I'll certainly look at the other options. And available "open weights" LLMs hosted by someone will be my first pick. Right now Claude 4.8 feels very advanced, but things move very fast...

The hotness we are seeing is smaller 'expert' models with an 'orchestrator' model in front that evaulates the prompts and routes to the appropiate small models and then synthesizes the collected answer. Easier to split across many smaller, cheaper servers and more efficient than a huge monolithic model.

I don't think you're appropriately understanding the full gamut. The individuals who only spent $200/months will be stuck. But the pie is increasing in size, it's not stagnant. There are a lot of orgs who can afford to run a 1T model and even more that can run a 600B model. These newcomers are what's being fought over

> Anthropic and Claude remains very popular among the people who use LLMs

Only because someone else is paying the bills. I use Claude Opus at work because my employer pays for the tokens and encourages me to do it.

At home, I use DeepSeek Flash. It's not as good, but it's maybe 0.7 quality for 0.001 cost.

> Try running the latest OS models on a normal Mac or PC.

It can be done through the magic of SSD offload. The worst case involves seconds-per-token speeds, but that's OK if you only care about low volumes of slow unattended inference, which maximizes utilization for the hardware.

(The real worst case, where you're streaming the whole model from the cheapest storage you could feasibly think of, involves multiple minutes per token for a single inference, or even hours per token batch if you're doing many inferences in bulk. That's a lot less helpful, so there's a space for smaller models at the edge, even for unattended workloads.)

> I disagree. It is not the model alone. It needs a system which capitalizes on it. And this is very complex.

AFAICT … despite saying you “disagree”, you appear to be agreeing with the parent comment that the model is less important and compute (all that complex infra) and data (also complex infra) are more important.

> > The bottleneck is compute and data, not the model.

> I disagree. It is not the model alone. It needs a system which capitalizes on it. And this is very complex. Hardware, software, architecture - it takes a lot to get it right.

What do you disagree with exactly?

For now I suspect however that the gigantic models are not needed and you will be able to do pretty much what you need in a specific domain with 120b or lower. There is so much trash in the frontier models. I don't need all the world's slam poetry for my coding tasks for example.

That’s really what Dario wants. Let’s hope he doesn’t get it

Yeah yeah, but after the IPO!

I struggle with the practicality of the whole thing.

The amount of tokens required to properly distill a frontier model is so large that by the time you could consume the # of tokens you would either be banned for extremely obvious abuse or a new model would be released, rendering your efforts less and less valuable over time. Intelligence is not a linear thing. Being behind just a little bit can have exponential consequences.

I'm uneducated on how distillation works at more than a basic level so forgive me if this is a stupid question.

Isn't "distillation" of another provider's model exactly how these models got training date in the first place: Massive amounts of the written word + Prompt -> Answer. Why wouldn't distillation produce similar "reasoning" in the new model? It's just inputs and outputs.

This is totally inaccurate, the APIs provide the reasoning logs. You ABSOLUTELY can distill from APIs, in fact, that's the primary way distillation is done currently.

They get to 80% of the top models for 10x cheaper, unless you don't care about the money at all, it's hard to ignore.

The second case is not what Anthropic did either, though. If you have their process internalized as "open freebsd, tell mythos 'find vulns', done" this is not what happened. They have a harness that went file-by-file, spawned a subagent for each file, told it to find vulns in that file, then a post-processing step (more on that in a sec).

In that sense: The AISLE replication still provides too much information to the model, but its not far off, and others have replicated Mythos' findings in a more clandestine manner on open source models. Some were totally capable of finding the same vulns Mythos found back in ~March (and today, the new Kimi K2.7 is looking extremely good, very little doubt it could do it).

The critical difference is that post-processing: the Mythos model/harness has some step to induce Mythos to actually exploit the vulnerability, leveraging its ability to do so as a ranking mechanism. Anthropic inferred that this led Mythos to discover vulnerabilities nothing else could discover, which is not true, and Anthropic should be held accountable for this weird artifact of that communication. However:

- An OSS model might find the vulnerability but rank it as a 3/10. Mythos finds it, chains it with a second vulnerability, now suddenly its an 8/10.

- An OSS model might find the vulnerability, alongside fifty other vulnerabilities. The operator ignores all of them.

The problem with automated vulnerability detection, including with LLMs, is that they find the haystack, not the needle. Every piece of hay might be a vulnerability, but whether its worthy of fixing is another matter. Mythos does represent a meaningful improvement; it better finds the needle.

This is a suicide shot for the American economy. The numbers only lined up for AI to rescue the USA from its debt if it captured a significant portion of the world's AI spend, and while it was a longshot before, there's basically zero percent chance the world trusts American AI when the government is pulling strings.

Consider this quote from the main article...

"When you further combine this realization with the company’s pronouncements about AI’s ability to conduct all economic activity, you realize that Anthropic’s leadership effectively wants to have power over everything and everyone."

This is fearful stuff on all sides, and none of the people involved might realistically be able to navigate the danger.

They don't even need to know they are. You can assume that if the model becomes available again, a lot of people will find themselves working for companies distilling these models that just happens to ultimately do work for foreign entities, whether or not the people accessing the models knows or not.

They cannot do it. Apart from all the practical, technical and talent reasons, it would still be exporting forbidden stuff.

The signal is clear enough though for the next Anthropic..

Individuals can leave, but the company cannot transfer restricted intellectual property.

Europe has extradition treaties, so the U.S. can force anyone in Europe back to the U.S. for criminal indictment who demonstrates inappropriate possession of this technology.

I think the overly sensitive filters reveals an alignment gap

if they had more success on alignment and safety research then I don't think the cludgy filters would be necessary

> the EU is hardly buzzing with AI innovation

Depends what you mean. The academic work seems largely... fine? Plenty of good work came out of Europe or European researchers. It seems the problem is more "trying to build a trillion-dollar company of any kind".

It's an interesting question: does the EU seek only to regulate successful modern American companies to death, or home grown ones too? Probably not a gamble worth taking.

No. If we cannot even have an EU CloudFlare, then we definitely do not have the infra for this kind of computing.

The EU options are not even close to what CF can do

UAE would be happy to pay for it

> Does any other place have the infrastructure

That's not the problem.

The US government can export ban GPUs like they do now to more countries if needed. Even if the infrastructure exists, the GPUs won't.

China

If you’re implying that the government is in on it and is doing this stuff intentionally in order to boost Anthropic, that’s ridiculous.

Incomparable domains. People routinely suffer illness. We can compare outcomes. These ideologues are building something completely unprecedented which, according to themselves apparently, can go paperclip-rogue if one is not careful. So the worst case is unprecedented. Then there is the more mundane matter of heating up the economy, something which also has no one blameworthy until any such supposed bubble actually pops.

> So... what, you just don't trust anyone good?

The baseline here is apparently that they are good, I’m just supposed to trust and shut up?

They are probably thinking of the "Board of Peace"