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Claude Opus 4.8

anthropic.com

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Re: Claude Opus 4.8

#561

Post by krupan »

TIPSIO wrote: post #311
alansaber wrote: post #247

"Our models are more honest" honey the quarterly marketing spin for a ML term has come. Forget "task alignment" now we're going for "truth index". I suppose this is the only way to generate hype when you're selling/releasing the same product over and over again.

When doing some electrical, Opus 4.7 essentially told me to wiggle a wire to see if it was hot or not with my bare hand. I called it out. It then gave me one of the most super heartfelt honest and sincere apologies I have ever received. Glad the safety team was there for me and able to make such an honest model or I would have been very upset about it.

I honestly cannot tell if you are being sarcastic or not

Re: Claude Opus 4.8

#562

Post by BoorishBears »

kakugawa wrote: post #547
gibspaulding wrote: post #488

Earlier quoted context omitted.

I’m pretty sure that switch has always been there, but turning it off doesn’t do what you want. It disables thinking entirely.

Opus 4.7 does not support disabling adaptive thinking (web, Claude Code). [1] Like the OP, I experienced similar issues and I'm glad that they brought back the ability to disable adaptive thinking in Opus 4.8. [1] https://code.claude.com/docs/en/model-config#adaptive-reason... > Opus 4.7 and later always use adaptive reasoning. The fixed thinking budget mode and `CLAUDE_CODE_DISABLE_ADAPTIVE_THINKING` do not apply to…

> Opus 4.7 and later

The source of truth should be the API docs which make it clear 4.8 didn't bring back extended thinking: https://platform.claude.com/docs/en/about-claude/models/over...

Any UI settings probably just map to changing the effort nudge on adaptive thinking

Re: Claude Opus 4.8

#563

Post by elfly »

guluarte wrote: post #367
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 think the future will be enterprise clients will train their own models based on their needs and data.

I honestly doubt this; very few companies have enough data. Maybe we could see mergers so it happens but basically it would mean everyone would need to be Google sized for it to work.

Re: Claude Opus 4.8

#564

Post by iLoveOncall »

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'm pretty sure they're releasing 4.8 because they massively shit the bed with 4.7 and people aren't using it.

I have ONLY heard negative feedback about it, and trying it myself also yielded really awful results.

Re: Claude Opus 4.8

#566

Post by cesarvarela »

hereme888 wrote: post #544

Early ArtificialAnalysis.ai results show GPT 5.5 is still the better bang-for-your-buck. OpenAI solves tasks with about 50% less output tokens. https://artificialanalysis.ai/?intelligence=coding-index&int...

I give Codex a try with every new version, and we don't match, so this isn't true for everyone.

Claude would need to be much more expensive for me to switch.

Re: Claude Opus 4.8

#567

Post by ThunderBee »

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…

IME the most noticeable performance boosts are in complex multi-agent workflows.

EX. You call an orchestration agent and define an implementation plan with the help of a number of sub agents planning out different features. You and the lead agent review all of the plans and send them off to a set of agents that write tests which get send back to the orchestrator then passed along with the plan to a set of coding agents who implement the features in their own worktrees. That gets passed back to the orchestrator which hands it off to another set of agents doing the code review and merging the features before sending it back to you.

Re: Claude Opus 4.8

#568

Post by cgg1 »

I find it surprising that the gap between tool usage and non-tool usage in HLE is relatively small (~10%) but the absolute numbers continue to go up

Re: Claude Opus 4.8

#569

Post by fragmede »

simonw wrote: post #73

I generated pelicans riding bicycles on both thinking level low and thinking level high: https://gist.github.com/simonw/68560eddb0b268a8417f80ceb7304... The high one is notably better - the bicycle frame is the correct shape, unlike thinking level low. For comparison, here's Opus 4.7: https://gist.github.com/simonw/afcb19addf3f38eb1996e1ebe749c...

For comparison, what's GPT-5.5 producing today?

Re: Claude Opus 4.8

#570

Post by yieldcrv »

vlovich123 wrote: post #257
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…

Took me a while to find what you were referring to by gram. Arxiv paper from 9 days ago that's not properly indexed by search engines. (G)enerative (R)ecursive re(A)soning (M)odels. They really wanted the acronym. https://arxiv.org/html/2605.19376v1

G return G
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