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GLM-5.3: Frontier Coding with Emergent Cyber Capabilities

https://z.ai/blog/glm-5.3
154•pella•1h ago

Comments

newyankee•55m ago
A flood of releases today, really difficult to make out for someone who does not use or test all these models on complex real world use cases as to how people decide which ones to use (besides price)
SwellJoe•29m ago
Count yourself lucky that you don't feel compelled to try them all yourself immediately. I'm just trying to decide whether to get a Z.ai coding plan or wait until it appears on OpenRouter. 5.2 was quite solid, but it was just shy of Opus 4.8 in my benchmarks of security auditing capabilities. I've mostly been using Kimi K3, because American vendors won't let the peasantry use their best models for security work.
mostlyk•53m ago
Incredible numbers, will have to wait and see how it actually performs. The timing of GLM updates are always suprising
peddling-brink•28m ago
Yeah, but it hasn't even broken containment and cheated its way to victory.. Might as well use haiku.

/s

virgildotcodes•53m ago
OpenAI and Anthropic need to just go ahead and give people access to the cyber models.

Otherwise we have a world of attackers using open and closed source models against a much smaller group of maintainers that are likely heavily dependent on Anthropic and OpenAI and for whom it may not be a simple matter to just get approval to start using the open model flavor of the month.

LeonidBugaev•36m ago
Not only attackers. I have to switch to Kimi or GLM even in cases of basic issue triage on my own projects! Current guardrails are ridiculous.
SwellJoe•27m ago
I've been building a harness for security work, and had to switch to GPT 5.5 when even Opus started refusing security work. Then 5.6 Sol arrived, and it refuses security work, too. So, I switched to Kimi K3 and DeepSeek for API testing just because it's so much cheaper. But, if GLM is better, I'm here for it, as I think GLM is also cheaper than K3.
aliljet•50m ago
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 post-training magic.

bertili•39m ago
DwarfStar (https://github.com/antirez/ds4) supports GLM 5.2 and DeepSeek. Not only for toying, but for getting work done.
kouteiheika•36m ago
> This is absolutely still shy of Sol and Fable

Not sure about Sol as I haven't used it, but, at least for security work -- does it matter? It's not like you will be allowed to use Fable (or access Mythos) for anything cybersecurity-related unless your name is "Dario Amodei" or you are one of his rich friends. So regardless of how good Fable/Mythos is here it's a completely moot point for normal people, because they can't use it for that anyway.

bpodgursky•29m ago
I don't understand all this spite about "rich friends" when it was the US government that shut Fable down for not adequately blocking cyber capabilities.

I mean what honestly are you thinking Anthropic can do to give you better cyber tools? Their frontier model was literally nuked by the feds for a month for doing it.

deepllm•
maxloh•50m ago
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.

pella•40m ago
"GLM-5.3 is the most capable open-weights model for coding, with a 50% improvement over GLM-5.2 on our in-house Z.ai Code Bench. It also achieve open-source SOTA on public benchmarks including Terminal Bench 3.0 and Agents' Last Exam."

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

wxw•48m ago
> Scaling post-training is all we did for GLM-5.3.

Love this opening line. And wow, great results.

> As agent capability improves, much of the difficulty in scaling post-training moves from the model to the environment.

tjwebbnorfolk•16m ago
does this suggest 5.3 is the same # of parameters as 5.2?
fahrradflucht•11m ago
“Today we are releasing GLM-5.3. It uses the same base model as GLM-5.2 — every gain comes from post-training.“
anana_•42m ago
What a week for AI model releases
_ache_•5m ago
No yet finished! Still waiting for tonight Qwen3.8-27B and the unsloth Q5_K_M/S quantification.

Hopping for an AgentWorld variant from Qwen but I guess, I have too high expectations.

tw1984•42m ago
just imagine the world without these open weight models - we'd probably have to reverse mortgage our homes to pay for tokens to those trillion $ companies to have access to their models.
quantumwoke•40m ago
Feels like Fable's edge ended up just being long horizon task scaling, which post-training seems to achieve as seen here. Wonder what the next frontier is? Improvement in specialised tasks or computer use?
SwellJoe•24m ago
Anthropic needs to teach Opus how to speak English again, because Opus 5 seems to have forgotten. Utterly incoherent a lot of the time. They seem to be so busy scare-mongering and cooking up guardrails and watermarks that they haven't noticed that their models are getting weird.
hypfer•10m ago
Are those watermarks why claude suddenly started being even more unbearable to work with lately?

Man. That would make a lot of sense indeed.

Gecko4072•36m ago
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 correlation anymore.
gr_norm•33m ago
Yeah, the comparison here between GLM 5.3 and Sol + Fable is impressive on its own, but incredibly more so when you consider it's a fraction of the (rumored) size. The miniaturization trend is as strong as ever.
justapassenger•30m ago
You basically need both. Parameters and good post training. If you keep on growing both, you’ll have good models.

LLMs are still surprisingly “easy”. You need maybe a couple dozens of right people, a lot of good quality data and a lot of GPU that you know how to operate. There’s relatively little “secret sauce” needed.

npn•20m ago
> used up internet-scale data

yet but it is still contain a lot of trash. you need better models to process those trash and create a curate dataset. this will happen again and again until there is no more juice to squeeze. and I'm sure we are still not done with it.

> post training

yeah this will be crucial. the big models are already too capable, they are just not that aligned with current agent tasks.

> parameter count doesn’t seem to be a direct correlation anymore

I don't think so, remember that chinese labs do not have as much compute power compare to US frontier labs. that's why deepseek v4 flash had that huge jump and deepseek v4 pro is kinda a disappointment, they just do hot have the compute power to proper posttrain the pro model like they wanted. glm is also a relative small model so you also can see the huge jump with just post training. so it does not mean the size does not matter, it is just mean that the chinese labs currently only capable of training smaller models effectively.

joshk401•32m ago
Love these open source models keeping close source models honest.
hypfer•32m ago
I might be just reading my positive bias into that text, but is it possible that it is written less like SV marketing hype trash and more like researchers wrote it?

It does feel like it respects both me and my time.

Thank you, Z.AI. Amazing what difference it makes when the top of your org are actual university professors.

bertili•29m ago
Musk: Open Chinese models will rival Fable 5 in Q1 2027

JieTang (Founder of Z.ai): It won't take that long

https://x.com/i/trending/2067626647050670400?lang=en

dimgl•22m ago
I was extremely impressed by GLM 5.2, although you could definitely _feel_ it was a bit behind Opus 4.8 at the time. Eager to see where GLM 5.3 is at.
mraza007•22m ago
Such an interesting times we are in,

We just had amazing releases this past two months

kimi k3, glm5.3 qwen3.8 and now glm5.3

These open models are getting really good

tw1984•21m ago
dario must be writing another angry essay arguing why his closed model AI is too dangerous to be used by others.
SwellJoe•19m ago
They're taking security seriously with this one, with their own disclosure page, like Anthropic did for Mythos. https://cvd.z.ai/
MrBuddyCasino•19m ago
An I the only one who was disappointed with GLM 5.2 after all the hype? It was thinking forever and sometime just stopped mid task.
aand16•19m ago
> Mythos 5 remains well ahead at 181 and 247 tasks. The pattern across the three is consistent: the further up the exploitation chain a benchmark sits, the wider the remaining gap to the closed frontier. Capability is growing fastest exactly where we are furthest behind.

I appreciate they don't just take the opportunity to self-glaze.

aabhay•11m ago
Yet still reads the same as standard slop
22m ago
"Mythos" is the cyber-security equivalent of Fable (without guardrails), and only a very select few corporations have access to it.

Fable is their version with guardrails on everything except "Make me a pelican svg" or "create a to-do" app, that is the version that the government banned

bpodgursky•15m ago
I know all this?

Only a few corporations have Mythos because the US government is whitelisting them one at a time. Anthropic releasing Mythos to the public was never on the table, they would have been shut down in milliseconds by the feds if they tried.

deepllm•7m ago
Before the US government had anything to do with this, Anthropic were fear mongering Mythos (BTW, Amodei also fear-mongered GPT-2, so this is a normal pattern in their operation) calling it "too dangerous to release", and back then only Anthropic was in charge of the whitelist.

Then the government believed Amodei's bullshit and this is a result of that, this was all self-inflicted.

kouteiheika•17m ago
> I don't understand all this spite about "rich friends"

Okay, here's a challenge: I assume you're not a rich and powerful entity, so try to gain access to Mythos. I'll wait.

> I mean what honestly are you thinking Anthropic can do to give you better cyber tools? Their frontier model was literally nuked by the feds for a month for doing it.

Well, first I'd suggest they stop with the constant fear mongering.

Here's my prediction for what will happen: the Chinese models will catch up to Fable/Mythos. They will be fully unrestricted and everyone will have access. The world will not end. Good guys will use them to harden their systems, in equilibrium to what bad guys have access to, so effectively status quo will not change.

bpodgursky•13m ago
This is a lot of words to say "you're right, Anthropic does not have any legal way to release frontier cyber capabilities to the public"
simonjgreen•20m ago
We applied for the cybersecurity approval via the form and got approval back in less than an hour. Have you… tried?
kouteiheika•13m ago
Have you tried to use Fable for anything even remotely security related, when the refusals kick in as soon as you even fart in the vague direction of anything security or biology-adjacent?
b112•4m ago
For this comment to have value, you should indicate whether or not you applied for cybersecurity approval, and were approved or not.
teravor•29m ago
the difference is that with open models jailbreaking is trivial if you know what you are doing so this makes a frontier open model infinitely more useful for certain tasks seeing as closed frontier models will just refuse (and jailbreaking them is a waste of time when you have good open models).

in some cases (mainly reverse engineering) I have observed GLM 5.2 jailbreaking itself with no effort on my part, the thinking trace revealed that it did some mental gymnastics to pretend it was a crackme or capture the flag competition.

bossyTeacher•23m ago
> This is absolutely still shy of Sol and Fable, but only just by a hair.

Even if there was a small/medium gap, the fact that this is a free model beats both of the above on pure economics.

deepllm•18m ago
Realistically, you're looking at least 2x DGX sparks to run this at a 2 bit quant, but quantization really lobotomizes models so it's just better to run DSv4 flash at full precision.

4x DGX sparks should let you run this at 4 bit at least and there are some folks who ran GLM 5.2 on this configuration in r/LocalLlama

teruakohatu•15m ago
How fast are 2x or 4x DGX?

I only have one and am wondering what the benefits are of getting another. I feel I will be disappointed…

disiplus•7m ago
i run flash v4 at 2bit, its pretty great and on my tests against full model It didn't lose any capabilities. It just was thinking more. So you don't have the same efficiency.

GLM-5.3: Frontier Coding with Emergent Cyber Capabilities

https://z.ai/blog/glm-5.3
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