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

GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

z.ai

Post reply on HN
Print view View original

61–70 of 540 posts

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#61

Post by mikehearn »

jaccola wrote: post #54
NiloCK wrote: post #29

Grey market fast-follow via distillation seems like an inevitable feature of the near to medium future. I've previously doubted that the N-1 or N-2 open weight models will ever be attractive to end users, especially power users. But it now seems that user preferences will be yet another saturated benchmark, that even the N-2 models will fully satisfy. Heck, even my own preferences may be getting saturated already. Op…

I have no idea how an LLM company can make any argument that their use of content to train the models is allowed that doesn't equally apply to the distillers using an LLM output. "The distilled LLM isn't stealing the content from the 'parent' LLM, it is learning from the content just as a human would, surely that can't be illegal!"...

The argument is that converting static text into an LLM is sufficiently transformative to qualify for fair use, while distilling one LLM's output to create another LLM is not. Whether you buy that or not is up to you, but I think that's the fundamental difference.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#62

Post by Aurornis »

ingenieroariel wrote: post #50
Aurornis wrote: post #19

Earlier quoted context omitted.

Apple devices have high memory bandwidth necessary to run LLMs at reasonable rates. It’s possible to build a Linux box that does the same but you’ll be spending a lot more to get there. With Apple, a $500 Mac Mini has memory bandwidth that you just can’t get anywhere else for the price.

With Apple devices you get very fast predictions once it gets going but it is inferior to nvidia precisely during prefetch (processing prompt/context) before it really gets going. For our code assistant use cases the local inference on Macs will tend to favor workflows where there is a lot of generation and little reading and this is the opposite of how many of use use Claude Code. Source: I started getting Mac Studi…

> With Apple devices you get very fast predictions once it gets going but it is inferior to nvidia precisely during prefetch (processing prompt/context) before it really gets going

I have a Mac and an nVidia build and I’m not disagreeing

But nobody is building a useful nVidia LLM box for the price of a $500 Mac Mini

You’re also not getting as much RAM as a Mac Studio unless you’re stacking multiple $8,000 nVidia RTX 6000s.

There is always something faster in LLM hardware. Apple is popular for the price points of average consumers.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#63

Post by throwaw12 »

NiloCK wrote: post #29

Grey market fast-follow via distillation seems like an inevitable feature of the near to medium future. I've previously doubted that the N-1 or N-2 open weight models will ever be attractive to end users, especially power users. But it now seems that user preferences will be yet another saturated benchmark, that even the N-2 models will fully satisfy. Heck, even my own preferences may be getting saturated already. Op…

not allowing distillation should be illegal :)

One can create 1000s of topic specific AI generated content websites, as a disclaimer each post should include prompt and used model.

Others can "accidentally" crawl those websites and include in their training/fine-tuning.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#64

Post by retr0rocket »

mythz wrote: post #58
btbuildem wrote: post #36

Earlier quoted context omitted.

> doesn't make financial sense to self-host I guess that's debatable. I regularly run out of quota on my claude max subscription. When that happens, I can sort of kind of get by with my modest setup (2x RTX3090) and quantized Qwen3. And this does not even account for privacy and availability. I'm in Canada, and as the US is slowly consumed by its spiral of self-destruction, I fully expect at some point a digital iron…

Did the napkin math on M3 Ultra ROI when DeepSeek V3 launched: at $0.70/2M tokens and 30 tps, a $10K M3 Ultra would take ~30 years of non-stop inference to break even - without even factoring in electricity. Clearly people aren't self-hosting to save money. I've got a lite GLM sub $72/yr which would require 138 years to burn through the $10K M3 Ultra sticker price. Even GLM's highest cost Max tier (20x lite) at $720/…

[dead]

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#65

Post by cmrdporcupine »

nwienert wrote: post #43
miohtama wrote: post #33

Earlier quoted context omitted.

In some ways, Opus 4.6 is a step backwards due to massively higher token consumption.

For me, it's just plain worse.

Try Codex / GPT 5.3 instead. Basically superior in all respects, and the codex CLI uses 1/10 the memory and doesn't have stupid bugs. And I can use my subscription in opencode, too.

Anthropic has blown their lead in coding.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#66

Post by drcongo »

I asked chat.z.ai with GLM 5 "How do I start coding with z.ai?" and got this in the answer...

> Z.ai (Personalized Video)

If you literally meant the website z.ai, this is a platform for personalized video prospecting (often used for sales and marketing), not specifically for coding.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#67

Post by Mashimo »

NitpickLawyer wrote: post #55
_joel wrote: post #16

Earlier quoted context omitted.

It's avaiable in mine, I think I paid about the same

> It's avaiable in mine Weird, mine (lite plan) says "Only supports GLM-4.7, GLM-4.6, GLM-4.5, and GLM-4.5-Air" and "Get same-tier model updates" ...

It seems like nothing is updated yet, expect the chat. https://z.ai/subscribe

It all just mentions 4.7

Seems like time will tell.

Edit: They updated it:

> The Lite / Pro plan currently does not include GLM-5 quota (we will gradually expand the scope and strive to enable more users to experience and use GLM-5). If you call GLM-5 under the plan endpoints, an error will be returned. If you still wish to experience GLM-5 at this stage and are willing to pay according to the Pricing, you can call it through the General API endpoint (i.e., https://api.z.ai/api/paas/v4/chat/completions), with the deduction priority being [Platform Credits - Account Balance] in sequence.

Re: GLM-5: Targeting complex systems engineering and long-horizon agentic tasks

#69

Post by vidarh »

mythz wrote: post #5

It's looking like we'll have Chinese OSS to thank for being able to host our own intelligence, free from the whims of proprietary megacorps. I know it doesn't make financial sense to self-host given how cheap OSS inference APIs are now, but it's comforting not being beholden to anyone or requiring a persistent internet connection for on-premise intelligence. Didn't expect to go back to macOS but they're basically the…

I don't really care about being able to self host these models, but getting to a point where the hosting is commoditised so I know I can switch providers on a whim matters a great deal.

Of course, it's nice if I can run it myself as a last resort too.

Post reply on HN