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Claude Opus 4.8

anthropic.com

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Re: Claude Opus 4.8

#231

Post by dominotw »

irthomasthomas wrote: post #223
NiloCK wrote: post #77

A rambling comment: I think this is the first time we've had a third minor version bump on a frontier Anthropic model. (I count the 0.5s as major here, because they've been issued non-sequentially and also corresponded to massive capability leaps, eg, Sonnet 3.5, Opus 4.5). So now the Opus 4.5 family has successors 4.6, 4.7, and 4.8, each posting fairly modest claimed gains. My own experience w/ 4.6 and 4.7 are that…

Given that 4.7 was a brand new model, trained from scratch with a unique architecture and tokenization scheme, I don't see the same pattern. It seems arbitrary.

i dont understand the nuances here. what does this mean. 4.8 is trained on same model as previous one then? what does brand new mean.

Re: Claude Opus 4.8

#232

Post by ertgbnm »

YetAnotherNick wrote: post #206
onlyrealcuzzo wrote: post #136

Earlier quoted context omitted.

I won't be surprised if the next gen frontier models are the last. There's orders of magnitude of low hanging juice to squeeze out of smaller models. It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years (design not certain, probably unlikely). It is far less clear that a 1.2T model will be meaningfully better enough to justify training it. As far as reasoning is con…

> It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years. I am ready to bet against this. Knowledge benchmark like SimpleQA isn't increasing for small models. > It is far less clear that a 1.2T model will be meaningfully better enough to justify training it. Well for one, we know for certain there is Mythos which is meaningfully better. And I think there is a lot of j…

Knowledge benchmarks can't really be improved upon via distillation or RL. It requires those facts be added to the training corpus and for the model to memorize them better. Neither distillation or RL really do that and thus we shouldn't expect improvements on SimpleQA unless some other interventions are being made.

Model intelligence and knowledge aren't necessarily directly related. If we can pack greater intelligence and agency at the cost of it forgetting factoids, that would actually be a good thing. We don't need LLMs to memorize facts, we need them to learn how to interact with the world such that they can find the facts that are necessary and surface them to the user.

If we could distill all of the knowledge out of an LLM and just be left with a very agentic model that only knows facts in it's context, I think some very interesting stuff would happen.

Re: Claude Opus 4.8

#233

Post by spwa4 »

supern0va wrote: post #177
onlyrealcuzzo wrote: post #136

Earlier quoted context omitted.

I won't be surprised if the next gen frontier models are the last. There's orders of magnitude of low hanging juice to squeeze out of smaller models. It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years (design not certain, probably unlikely). It is far less clear that a 1.2T model will be meaningfully better enough to justify training it. As far as reasoning is con…

>It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years. I don't disagree, but how much of this ends up being distillation? I can't help but imagine that 4.8 was probably trained in part by leveraging Mythos. If the very large models turn out to be very expensive to run relative to the benefits, it's possible that they could end up still being trained, but ultimately…

> I don't disagree, but how much of this ends up being distillation?

A lot, so you can bet tens of millions are flowing to congress to have distillation declared illegal before this happens. And then it'll happen anyway.

Re: Claude Opus 4.8

#234

Post by TIPSIO »

northern-lights wrote: post #23

> Not only that, but we plan to release a new class of model with even higher intelligence than Opus. As part of Project Glasswing, a small number of organizations are currently using Claude Mythos Preview for cybersecurity work. Models of this capability level require stronger cyber safeguards before they can be generally released. We’re making swift progress on developing these safeguards and expect to be able to b…

Seems like they might be hinting that if you are not a billionaire or multi-billion dollar company you will just get a limited and nerfed Claude Code slash command /mythos-security-audit or something.

Hope this isn’t the case and that normal average Joe’s of the world don’t get policed out of access.

Re: Claude Opus 4.8

#235

Post by peheje »

raincole wrote: post #154
wg0 wrote: post #104

There is a hole in the boat's bottom due to Chinese models. They might not be as good but they are not bad either or at least I had hard time finding any issues with Deepseekv4 Flash and Pro variants. They get their job done sometimes rarely giving up till they are done what they are after. So even for enterprise deployments, as the dust settles down, CFO/CTOs might find out that deploying on an internal cluster of G…

I had been saying this on HN repeatedly: people are going to use the smartest models for coding. They don't care how cheap your tokens are if they don't have the highest probability of solving your programming tasks. And I was dead wrong. Now I mostly use DeepSeek Pro myself.

I mean indsight is 20/20, but saying that is like saying "everyone will just use the best tools". That's not what we see most places in the world for most types of resources.

Re: Claude Opus 4.8

#237

Post by onlyrealcuzzo »

jruz wrote: post #227
onlyrealcuzzo wrote: post #136

Earlier quoted context omitted.

I won't be surprised if the next gen frontier models are the last. There's orders of magnitude of low hanging juice to squeeze out of smaller models. It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years (design not certain, probably unlikely). It is far less clear that a 1.2T model will be meaningfully better enough to justify training it. As far as reasoning is con…

Absolutely that’s why they’re rushing to IPO now to squeeze the last drop of the bubble they know this is a dead end.

It's unclear it's a dead-end within 5 years.

There's still several orders of magnitude of improvement that are almost certainly left - it's just not clear how much is left on the frontier end.

Most people will be very glad to pay Anthropic, OpenAI, Google etc $200 a month to get things done 20x faster than they could IF they had a $8000 MacBook and could theoretically do it locally.

Some people would pay $200 a month forever not to have to open the terminal one time...

Re: Claude Opus 4.8

#238

Post by dcchambers »

raincole wrote: post #154
wg0 wrote: post #104

There is a hole in the boat's bottom due to Chinese models. They might not be as good but they are not bad either or at least I had hard time finding any issues with Deepseekv4 Flash and Pro variants. They get their job done sometimes rarely giving up till they are done what they are after. So even for enterprise deployments, as the dust settles down, CFO/CTOs might find out that deploying on an internal cluster of G…

I had been saying this on HN repeatedly: people are going to use the smartest models for coding. They don't care how cheap your tokens are if they don't have the highest probability of solving your programming tasks. And I was dead wrong. Now I mostly use DeepSeek Pro myself.

I think two things happened:

1. The sheer number of tokens that a coding agent can use flipped the math upside down on this equation. If you use the most expensive model for everything those costs quickly become untenable, even for software companies.

2. We realized many of the coding problems we're solving aren't incredibly difficult.

Re: Claude Opus 4.8

#240

Post by lukan »

jruz wrote: post #227
onlyrealcuzzo wrote: post #136

Earlier quoted context omitted.

I won't be surprised if the next gen frontier models are the last. There's orders of magnitude of low hanging juice to squeeze out of smaller models. It is almost guaranteed that a 60-90B model can outperform current SOTA in coding tasks within 2-3 years (design not certain, probably unlikely). It is far less clear that a 1.2T model will be meaningfully better enough to justify training it. As far as reasoning is con…

Absolutely that’s why they’re rushing to IPO now to squeeze the last drop of the bubble they know this is a dead end.

On the other hand, I think I have been hearing that for a while, even before Opus.
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