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conradkay 10 hours ago

Wow, seems worse even on price/performance than GLM 5.2, which is only 744b parameters.

From the system card: "On CyberGym vulnerability discovery, Claude Sonnet 5 is less capable than Sonnet 4.6, and far less capable than Opus 4.8 and Mythos 5

As with the other evaluations in this section, these results were achieved with all safeguards turned off. When run with our default mitigations, Sonnet 5 scored a 0 on CyberGym"

sixtyj 9 hours ago | parent | next [-]

I have tried to rewrite an article with GLM-5.2 and with Sonnet 4.6. Completely different results as LLM is non-deterministic. But GLM-5.2 made a lot of subtle mistakes that needed to be corrected by hand. On the opposite, Sonnet found and corrected all mistakes in the second round.

Similar situation was with planning and coding. GLM-5.2 seems to be good “on paper” but the real usage results was different.

And I am not an attorney for Claude or GLM-5.2… :)

But as I’ve been using LLM models daily since Nov 2022 I have realized that all common tests have to be confirmed in your project - there is no “one model rules them all” - you need to dig out a specific model from that LLM haystack with thousands of models.

Benchmarks help but they start to be similar to fuel consumption specs in car ads - real consumption is different for everybody :)

Retr0id 10 hours ago | parent | prev | next [-]

Finally, a viable business strategy - sell security-oblivious code monkeys for cheap, then charge premium rates for agents capable of cleaning up the mess.

usef- 5 hours ago | parent | next [-]

Judging by the events of recent weeks, I'm guessing the low cyber results are why they were allowed to release it

JacobAsmuth 9 hours ago | parent | prev [-]

I think instead they should sell super hackers and get their product banned instantly and go bankrupt

loufe 9 hours ago | parent | prev [-]

Not to single you out, parent commenter, but I really hope the quality of discourse on HN will move past these basic comparisons eventually. It seems like every thread on every model release has the exact same comments.

"Wow, X models is Y% better or worse than Claude Z model on T benchmark"

"That's irrelevant, they're just benchmaxing."

"Not useable for daily coding or agentic workloads, the vibes are totally wrong."

"It's almost as good, and costs a lot less, so I will absolutely use it."

"I cannot imagine justifying using these, as the step change means open models lower costs do not make up for the productivity loss"

I'm an unhappy Anthropic customer and really rooting for open models and non-gatekept intelligence, but how do we move on from this now meme-like model release discourse rigamarole. I do not know what that would be. I don't design LLMs nor benchmarks, and I genuinely appreciate that people do their best to provide information, even if non-perfect here. I'm sure most of you who actively read these comment pages on announcements must feel similarly, though, right?

tripleee 9 hours ago | parent | next [-]

I'm not sure what else can be said? I've found benchmarks to be a very weak signal for how good/bad the model is, but it's the #1 thing the companies highlight.

20 minutes after the announcement there's no real useful statement that can be made about it.

conradkay 7 hours ago | parent | prev | next [-]

Yeah you definitely have to be skeptical regarding sentiment for open/local model capabilities, since there's bias from what people want to be true.

I generally agree with this in spirit https://www.seangoedecke.com/are-new-models-good/ , but I think you can read Anthropic's results showing Sonnet 5 as almost strictly worse than Opus 4.8 as very credible/meaningful, and then draw comparisons from that

9 hours ago | parent | prev | next [-]
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tiahura 9 hours ago | parent | prev [-]

"It's totally obvious they quantitized Claude Z"