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

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

#201

Post by dymk »

jsheard wrote: post #53
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…

I think AI may be the only place you could get away with calling a 2x350W GPU rig "modest". That's like ten normal computers worth of power for the GPUs alone.

That's maybe a few dollars to tens of dollars in electricity per month depending on where in the US you live

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

#204

Post by throwup238 »

Aurornis wrote: post #181

The benchmarks are impressive, but it's comparing to last generation models (Opus 4.5 and GPT-5.2). The competitor models are new, but they would have easily had enough time to re-run the benchmarks and update the press release by now. Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly…

> Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly some benchmaxxing going on.

Agreed. I think the problem is that while they can innovate at algorithms and training efficiency, the human part of RLHF just doesn't scale and they can't afford the massive amount of custom data created and purchased by the frontier labs.

IIRC it was the application of RLHF which solved a lot of the broken syntax generated by LLMs like unbalanced braces and I still see lots of these little problems in every open source model I try. I don't think I've seen broken syntax from the frontier models in over a year from Codex or Claude.

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

#205

Post by re-thc »

l5870uoo9y wrote: post #195
algorithm314 wrote: post #171

Here is the pricing per M tokens. https://docs.z.ai/guides/overview/pricing Why is GLM 5 more expensive than GLM 4.7 even when using sparse attention? There is also a GLM 5-code model.

It's roughly three times cheaper than GPT-5.2-codex, which in turn reflects the difference in energy cost between US and China.

It reflects the Nvidia tax overhead too.

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

#206

Post by yieldcrv »

Aurornis wrote: post #181

The benchmarks are impressive, but it's comparing to last generation models (Opus 4.5 and GPT-5.2). The competitor models are new, but they would have easily had enough time to re-run the benchmarks and update the press release by now. Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly…

come on guys, you were using Opus 4.5 literally a week ago and don't even like 4.6

something that is at parity with Opus 4.5 can ship everything you did in the last 8 weeks, ya know... when 4.5 came out

just remember to put all of this in perspective, most of the engineers and people here haven't even noticed any of this stuff and if they have are too stubborn or policy constrained to use it - and the open source nature of the GLM series helps the policy constrained organizations since they can theoretically run it internally or on prem.

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

#207

Post by syntaxing »

woeirua wrote: post #190

It might be impressive on benchmarks, but there's just no way for them to break through the noise from the frontier models. At these prices they're just hemorrhaging money. I can't see a path forward for the smaller companies in this space.

Tim Dettmers had an interesting take on this [1]. Fundamentally, the philosophy is different.

>China’s philosophy is different. They believe model capabilities do not matter as much as application. What matters is how you use AI.

https://timdettmers.com/2025/12/10/why-agi-will-not-happen/

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

#208

Post by tw1984 »

visarga wrote: post #189
tw1984 wrote: post #169

Earlier quoted context omitted.

> In 2 years you could make that investment back in pay raise. you can't be a happy uber driver making more money in the next 24 months by having a fancy car fitted with the best FSD in town when all cars in your town have the same FSD.

But they don't have the same human in the loop though.

that software is called autonomous agents, the term autonomous has nothing to do with human in the loop, it is the complete opposite.

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

#209

Post by dymk »

visarga wrote: post #91
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…

Your $5,000 PC with 2 GPUs could have bought you 2 years of Claude Max, a model much more powerful and with longer context. In 2 years you could make that investment back in pay raise.

This claim has so many assumptions mixed in it's utterly useless

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

#210

Post by algorithm314 »

throwup238 wrote: post #204
Aurornis wrote: post #181

The benchmarks are impressive, but it's comparing to last generation models (Opus 4.5 and GPT-5.2). The competitor models are new, but they would have easily had enough time to re-run the benchmarks and update the press release by now. Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly…

> Although it doesn't really matter much. All of the open weights models lately come with impressive benchmarks but then don't perform as well as expected in actual use. There's clearly some benchmaxxing going on. Agreed. I think the problem is that while they can innovate at algorithms and training efficiency, the human part of RLHF just doesn't scale and they can't afford the massive amount of custom data created a…

Can't they just run the output through a compiler to get feedback? Syntax errors seem easier to get right.
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