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Claude Opus 4.8

anthropic.com

221–230 of 1001 posts

Re: Claude Opus 4.8

#221

4.8 also seems like a regression and using it from the chat GUI results in 4.6 no longer showing up. If someone from anthropic is here, is it possible to readd 4.6 in the "other models" dropdown ? I feel like I got a bit baited/switched here.

Yeah, I was using 4.6 way more than 4.7. Pulling 4.6 from the web chat also means we lose access to Extended Thinking there. So they're saving on compute. It's hard not to assume this was part of the motivation behind the 4.8 release timing.

Re: Claude Opus 4.8

#222

At least it passes the Car Wash Test this time.

Meh, I feel that the car wash test is probably the worst question of all of those LLM test questions. The question is basically logically inconsistent and expect the model to work around the inconsistency.

Re: Claude Opus 4.8

#223
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.

Re: Claude Opus 4.8

#226
post #115

Earlier quoted context omitted.

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.

Same. So happy when I found that option.

Unfortunately, looks like 4.6 is now gone from the web ui.

Re: Claude Opus 4.8

#227
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…

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.

Re: Claude Opus 4.8

#228

Can anyone else see these X.Y updates aren't meeting the outrageous AI expectations that we were told we would see just a year ago?

They have a much stronger model named Mythos, it made quite a splash - you can google it.

These are just small fine tunes on top of the older model

Re: Claude Opus 4.8

#229
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've been using Claude Code regularly since the 4.5 release, and 4.7 was a significant regression: very unreliable, arguing about changes, deciding that fixes weren't needed, etc.

I'm hoping they recreate the magic of 4.5 but it's as much about the quality of harness, the memory and efficiency of the tools than simply the models at this point.

Re: Claude Opus 4.8

#230
Anthropic did a big strategic error. Normally they compare their models with their old models. Instead today, now that everybody knows how strong GPT 5.5 is at coding, they put it in the mix, basically showing all their customers that the benchmarks can't be trusted.
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