Hacker News Board Hacker News, browsed like a classic message board
Live data from Hacker News

Claude Opus 4.8

anthropic.com

Post reply on HN
Print view View original

331–340 of 1001 posts

Re: Claude Opus 4.8

#331

Post by wg0 »

pants2 wrote: post #160
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…

The Chinese models are only cheap on subsidized Chinese hosting. I have yet to find a USA-hosted Chinese model with a very clear value advantage over US models.

No true. Also - put Deepseekv4 Flash on your local with effort set to "high" and you'll see that many many are using that model on their own machines without paying anyone anything.

Its just that some of us didn't imagine having GPUs would be advantageous and were not gamers on the side. Those who had beefy GPUs or GPU rigs for any reason, they rarely need to go anywhere else.

At least I am so impressed with Deepseekv4 AFTER using Claude Opus 4.7 for significant amount of time that I am not going anywhere but Deepseekv4.

The model is just INSANE. Things I have done with it include attempting to write a 2.5D game engine in C with full animation and map rendering layer by layer.

Re: Claude Opus 4.8

#332

Post by [deleted] »

dwaltrip wrote: post #304
XCSme wrote: post #262

On my tests[0] it does a bit worse, and it's almost 2x expensive than Opus 4.7... I was surprised to see that it failed a Data extraction test (it gets it right 2/3 times, but one time it randomly returns null for a value instead). It makes sense a bit that it fails more Trivia/Domain-specific knowledge tasks (I think models are more and more trained towards agentic use-case than general intelligence). [0]: https://a…

Wait, doesn’t the blog post say the price is the same as 4.7? > Claude Opus 4.8 is available everywhere today. Pricing for regular usage is unchanged from Opus 4.7: $5 per million input tokens and $25 per million output tokens. Pricing for fast mode is $10 per million input tokens and $50 per million output tokens. Where do you see the 2x cost?

[deleted]

Re: Claude Opus 4.8

#333

Post by ethanpil »

The table comparing eval scores shows the following:

Agentic Terminal Coding (Terminal-Bench 2.1) Opus 4.8 74.6% GPT 5.5 78.2%

Then, when you scroll all the way down to the bottom Footnotes section it says

"Terminal-Bench 2.1: We reported scores for all models using the Terminus-2 public harness. GPT-5.5’s reported score with the Codex CLI harness is 83.4%."

Re: Claude Opus 4.8

#334

Post by mitjam »

legitster wrote: post #124
james_marks wrote: post #26

> One of the most prominent improvements in Opus 4.8 is its honesty. We train all our models to be honest—for instance, to avoid making claims that they can’t support. But a general problem with AI models is that they sometimes jump to conclusions, confidently claiming to have made progress in their work despite the evidence being thin. Early testers report that Opus 4.8 is more likely to flag uncertainties about its…

Part of the problem is also garbage-in/garbage-out. There's a lot of human information on the internet that is also confidently wrong. I use Sonnet a lot for learning about history or contextualizing news topics. It's really good at this for the most part. But there are a lot of topics where "consensus" between either academics or journalists is really "one secondary source which gets repeated a lot".

A failure mode I see more, recently is that it gives superficially correct answers but after digging deeper, I get answers that contradict the superficial answers - really an important thing to be aware of, in my point of view, and it often leaves me wondering if I dug deep enough.

Re: Claude Opus 4.8

#336

Post by SupLockDef »

XCSme wrote: post #262

On my tests[0] it does a bit worse, and it's almost 2x expensive than Opus 4.7... I was surprised to see that it failed a Data extraction test (it gets it right 2/3 times, but one time it randomly returns null for a value instead). It makes sense a bit that it fails more Trivia/Domain-specific knowledge tasks (I think models are more and more trained towards agentic use-case than general intelligence). [0]: https://a…

Releasing a new model is the new way to Jack up the price hehe.

Re: Claude Opus 4.8

#337

Post by roadside_picnic »

hellohello2 wrote: post #292
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" What insight do you have to make this claim?

Have you personally used any of the latest batch of even smaller local models? They certainly don't beat SotA models at coding... but with a good harness they are able to achieve things with SotA that I couldn't last year.

I've repeatedly given local models non-trivial projects that involve research and coding which they've successfully completed with minimal intervention from me (almost exclusively in the domain of reviewing the results). Again, nothing comparable with current SotA, but definitely tasks I could not have given SotA models last year (without agent harness).

Now that pure progress from these models seems to have slowed down, we're seeing a ton of options for both making models more efficient and other tools that help improve them (everything from agent harnesses to RLVR).

That's just looking at "what can small do today", when you look at what's possible with larger open models that are still much smaller than SotA from the major providers, their performance is extremely close to SotA, enough that for personal projects I'll just use Kimi instead of any anthropic offerings.

So it's not terribly hard to image a solution in the middle happening within a few years. We still have tons to learn about optimal sizes of these models and how to build them with maximal efficiency (and we've already seen a lot of recent improvements in this space).

Re: Claude Opus 4.8

#338

Post by techtuate »

Looking at the comments in this group, I'm not the only "stupid" one who hasn't noticed any discernable improvement in quality across the newer models. In fact my Claude code on re-login switched to Sonnet 4.6 and the vibe coding quality (with Opus 4.7 assisted prompts) has been good enough for me to lazily persevere with Sonnet for coding. Having said that I'm now on Opus 4.8 and will gladly come back here and eat humble pie should my opinion change. PS: Since my goal is embedding the best AI in B2B SAAS products, the key differentiator is not to use the shiniest Claude version (too expensive anyway) but to build a client aware RAG to enable bespoke learning and to use the right AI for my product - a combination of Gemini 3.0 Flash (image and not bad at reasoning), Grok (reasoning) work for me. Would love to hear more ideas (especially on open source as I'll look to cost optimize when I hit scale)

Re: Claude Opus 4.8

#339

Post by michaelchisari »

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…

| a 60-90B model can outperform current SOTA

My conspiracy theory is that Apple recognizes this.

Re: Claude Opus 4.8

#340

Post by semiquaver »

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...

Because that is the best way to talk about these things.

  > Second, all of us, including those who design them, possess only a limited understanding of their actual functioning. Indeed, current AI systems are more “cultivated” than “built,” for developers do not directly design every detail, but instead create a framework within which the intelligence “grows.” As a result, fundamental scientific aspects — such as the internal representations and computational processes of these systems — remain, at present, unknown.
https://www.vatican.va/content/leo-xiv/en/encyclicals/docume... para. 98

edit: apologies to __s who posted this before me and I didn’t notice

Post reply on HN