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GLM-5.3: Frontier coding with emergent cyber capabilities

z.ai

81–90 of 626 posts

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#82

Earlier quoted context omitted.

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize. These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin. I just don't see how you justify a trillion valuation for US AI labs when the underlying models are…

> Providers can just run them, offer cheap tokens, and pocket the margin. There’s an assumption that you can spin up the infra and acquire customers within that margin

Which is not unreasonable. Just hosting it in the EU and promising not to retain / sell the data let's you charge a healthy extra and compete in many areas other players can't.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#83
post #5

This is absolutely still shy of Sol and Fable, but only just by a hair. Ridiculous results. There's still not a compelling economic reason to drop OpenAI courtesy of the ludicrous reset addiction that's taken place, but it feels like we're on the precipice. How are you all toying with running this kind of thing in a mega quantized way locally? Two weeks out from released weights, but this is still just GLM 5.2 with p…

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize. These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin. I just don't see how you justify a trillion valuation for US AI labs when the underlying models are…

I suggest you think why OpenAI was worth billions before ChatGPT. The valuation is not about how the current set of models can be monetized.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#84
> Open Source: We will release the weights in two weeks after launch, once safety evaluation and hardening are complete.

What safety evaluation? What safety hardening? They already evaluated it and found it to be highly capable at exploiting security vulnerabilities. So we know it is not "safe", and they don't seem to plan to do anything against it. What could be more dangerous than hacking? Biological weapons research? I don't think Chinese labs are doing anything against this either.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#85

People familiar with the topic, how will models continue to get better? Post training it seems? Labs have already used up internet-scale data, so are there any limits to architecture improvements and post training or can we expect this trend to continue? ByteDance is training a 10T-parameter model. Here, GLM 5.3 outperforms models 3-4x its size of roughly 700B, so parameter count doesn’t seem to be a direct correlati…

GitHub dumps are about 115 terabytes. The common crawl is in the petabyte range uncompressed for every year. Apparently there are dumps of Reddit too in spite of their efforts to ban bots and it's not solely due to the use of residential proxies. For a 1:20 parameter to token ratio, you can still train up to 10 trillion parameters so 10T parameters times 20 is about 200 trillion tokens. Then each token is 4 bytes so 200 times 4 is about 800 terabytes, which is not inconceivable, the common crawl alone has more data than that. So does the internet archive if you donate to them, Anna's archive is 2 petabytes including images, etc etc not all of it is text, but training on multimodal data increases model intelligence by virtue of being multimodal

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#86
post #6

No Hugging Face link yet. I wish they would release it under a true FOSS license. Kimi and QWEN are now moving on to a restricted-usage license, which, although is still better than the proprietary American models, is a step back from the open source Chinese LLM culture.

Let's just commit that FOSS business is really difficult for LLM industry that depends so heavily on massive financing. Making weights freely available to indie devs, small companies, and research purposes is good enough and might be the most ethical move which is financially continuable.

Let those companies with thousands of GPU making millions pay. They should.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#87
Their coding plan switched to credits, didn’t it? What are the rate limits like, compared to Anthropic or Kimi K3?

I remember trying their Coding Plan out before the change and the 5 hour limits felt too restrictive then even for light/medium work, especially cause of the whole peak and off-peak thing: https://blog.kronis.dev/blog/z-ai-s-glm-5-2-is-a-great-model...

Nowadays, I’d probably go with their Max plan if the rate limits are okay? Anyone using them now?

Oh also unrelated but ZCode was surprisingly good, which is surprising for a tool that came out of nowhere - even some of the critiques in my blog post have been patched out. Sadly they don’t support using Claude Code as an agent so can’t use it like Paseo or Kepler or Agent Orchestrator.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#88
post #72

Earlier quoted context omitted.

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize. These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin. I just don't see how you justify a trillion valuation for US AI labs when the underlying models are…

I think at this point the question is: will the US government be willing and capable to justify the trillion dollar valuation for _one_ of the companies via regulatory capture? The US has a workforce of 170m, so 1.7 trillion would come down to 10k per person, or a discounted cashflow at 3% of 25 USD per month - not including private use, students etc.

Why would you restrict to the US workforce? ChatGPT has a billion users.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#89
post #5

This is absolutely still shy of Sol and Fable, but only just by a hair. Ridiculous results. There's still not a compelling economic reason to drop OpenAI courtesy of the ludicrous reset addiction that's taken place, but it feels like we're on the precipice. How are you all toying with running this kind of thing in a mega quantized way locally? Two weeks out from released weights, but this is still just GLM 5.2 with p…

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize. These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin. I just don't see how you justify a trillion valuation for US AI labs when the underlying models are…

Hmm.. how you justify?

Provoking war, this is how the empire "defends" itself, usually.

I just hope that this time it will get stuck in your throat.

Re: GLM-5.3: Frontier coding with emergent cyber capabilities

#90
post #5

This is absolutely still shy of Sol and Fable, but only just by a hair. Ridiculous results. There's still not a compelling economic reason to drop OpenAI courtesy of the ludicrous reset addiction that's taken place, but it feels like we're on the precipice. How are you all toying with running this kind of thing in a mega quantized way locally? Two weeks out from released weights, but this is still just GLM 5.2 with p…

OpenAI and Anthropic are both seeking trillion IPOs, while Chinese labs are pumping out open-weight models that are free for US providers to host and monetize. These Chinese models cost less of US SOTA models to run, even if they are less capable. Providers can just run them, offer cheap tokens, and pocket the margin. I just don't see how you justify a trillion valuation for US AI labs when the underlying models are…

Another interesting potential market here will be 'LLM in a box'. All the hardware and other tooling in a prebuilt, but modular, package ready to go. Pay one up-front cost, get a system running [whatever open LLM] with a token rate of [x], optionally configured to be immediately ready for distributed usage. Basically the opposite of cloud stuff: no rent, no dependency, 100% guaranteed uptime, guaranteed security/privacy (at least subject to your own actions), and so on.
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