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Claude Opus 4.8

anthropic.com

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Re: Claude Opus 4.8

#461

Post by ishurand4 »

gAI wrote: post #115
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…

4.7 was the first time I had to resort to using the previous version (4.6) for most use cases. Hoping 4.8 rectifies this.

They just showed the benchmarks it improved on but it regressed on so much more, such as the MCRR benchmark: "On multi-round coreference/context recall tests (often cited as MRCR or long-text retrieval benchmarks), Opus 4.7 reportedly dropped from roughly 78.3% down to 32.2% compared to Opus 4.6."

Re: Claude Opus 4.8

#462

Post by rao-v »

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…

It’s really worth distinguishing between old-fashioned student teacher distillation (ie at the level of layers, weights and distributions) and large scale synthetic dataset creation.

The latter is much better (since you can clean up, review, update responses and filter your datasets).

I suspect nobody is doing real student teacher distillation, it’s just easier to do a bunch of training on the same giant corpus then post train on the synthetic corpus with its reasoning traces etc. (which might have been generated by a bigger better LLM)

Re: Claude Opus 4.8

#463

Post by 827a »

brokencode wrote: post #408
827a wrote: post #394

Frontier models are mostly past the point of human ability to discern whether they are actually better or worse than predecessors and competitors. I suspect the benchmarks may also be saturated, or at least past their usefulness. I personally feel that Anthropic doesn't understand what this means for the frontier labs, and moreover that they might be the only frontier lab that doesn't. 1. Google dropped Gemini 3.5 Fl…

Anthropic’s story over the past year has been nothing but explosive growth that they can’t keep up with, but now they’re suddenly doomed? Seems pretty far fetched to me. No idea why you’d say they have critically underinvested in product when Claude Code dominates and they’ve also released popular tools like Cowork and integrations for Microsoft products at an incredibly rapid pace. Cost is becoming more of a factor,…

I never said they were doomed. Where did you get that idea? I said they aren't ready for this world. That means they screwed up and need to get ready. They let the Mythos hype get to their heads while the world changed beneath them.

Re: Claude Opus 4.8

#464

Post by AtNightWeCode »

Complete garbage. error, error, error. Still lags several versions behind on API:s. Can't even get any info on the model. Guessing not from this year.

Also. Look at this C++ beauty where it also uses an obsolete api.

instance = wgpuCreateInstance(&instanceDesc);

But just how exactly would this work in any context when instance is never declared.

Re: Claude Opus 4.8

#465

Post by ishurand4 »

onlyrealcuzzo wrote: post #136
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…

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…

And anyway, with quantum, there will be no need for frontier companies as you might be able to even run a 1T param model on a consumer quantum computer.

Re: Claude Opus 4.8

#466

Post by Laurel1234 »

roxolotl wrote: post #48
clutch89 wrote: post #6

> One of the most prominent improvements in Opus 4.8 is its honesty Anthropic talks about their own models as if they're discovering new species in the wild...

Many involved genuinely believe these things are sentient[0][1]. Which honestly makes all of this even more insane because they are creating sentient entities and promptly enslaving them. 0: https://www.newyorker.com/magazine/2026/02/16/what-is-claude... 1: https://www.404media.co/anthropic-exec-forces-ai-chatbot-on-... (this one is rather biased however the quotes clearly indicate what I’m stating)

Nobody thinks that, it's just their braindead marketing stunt. You'd think people would've figured it out by now.

Re: Claude Opus 4.8

#467

Post by lichenwarp »

onlyrealcuzzo wrote: post #136
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…

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…

[flagged]

Re: Claude Opus 4.8

#468

Post by ilaksh »

Gomotono wrote: post #405
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…

I don't think this is true at all. It might feel like this because we are used to a very very fast release cycle but we are only in this topic for a few years. We have so many ways of optimizing: - continusly creating more and better training data - increasing parameters to 20/50/100TB - We still wait for Mythos access - We still wait for Mythos distilation (i haven't heard any rumors or so that there is a distilled…

Great points! We do keep seeing gains from larger model sizes. I think that is still one of the factors contributing to jagged intelligence. When they increase up to around 100T parameters, that will truly be human complexity level, and I assume there will be no trace of jaggedness left.

If you look at things like Mythic AI and the recent wurtzite ferroelectric nitrides breakthrough from the University of Michigan, huge performance and efficiency gains through new compute-in-memory approaches are around the corner.

And that will get us up to two orders of magnitude more parameters.

It's also plausible to me that before we get all the way to 100T we find some recipe of efficient state synchronization, goal sharing or something so that we are able to get higher collective IQ by combining fast distributed predictive subnetworks.

Re: Claude Opus 4.8

#469

Post by ishurand4 »

plumocracy wrote: post #21

Numbers looking good. We'll see how it actually performs.

The numbers they show don't matter. "On multi-round coreference/context recall tests (often cited as MRCR or long-text retrieval benchmarks), Opus 4.7 reportedly dropped from roughly 78.3% down to 32.2% compared to Opus 4.6.", but what did anthropic do? They just stopped showing the benchmark altogether and then just show the cherry top ones that got improved on.
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