GLM-5.3-Flash

https://artificialanalysis.ai/models/qwen3-8-27b?models=gpt-...

Wow, if you don't mind me asking. How and where?

Agree. It doesn’t even have to be local, using models in this size class through OpenRouter will reveal their limits if you work side by side with Opus level models regularly.

There are a lot of social media posts about people cancelling their Anthropic or ChatGPT subscriptions after installing a local LLM. I’ve used local LLMs a lot and I spend a lot of time with frontier models and the difference is still huge. As far as I can tell, the social media posts about local LLMs replacing frontier models are either wishful thinking, engagement bait, or people who must be working on much simpler projects with a much higher tolerance for slop than I have.

Opus 5 consistently comes at or near the top, but outputs constant unreadable jibberish. Meanwhile GPT 5.6 Luna medium tends to be rated pretty poor on agentic tasks compared to the Chinese lab open models, but I find the latter much more likely to lose track of their own behaviour during a long-horizon task or get stuck in a doom loop.

(This isn't a comment on GLM-5.3 Flash as I've not used it!)

I've probably wasted a good 40% of my weekly usage on Luna Max agents just thinking and not writing a single line of code.

It's what people know. Opus is just the common target.

> Smarter and cheaper than Luna xhigh, not as smart but less expensive than Luna max. Smashes deepseek v4 flash

The problem with this and DeepSWE is it goes for a very specific profile. I'm not convinced DeepSWE is any accurate in actual work. It's surely a different signal (compared to some that allow cheating) but it has its own issues, e.g. weak harness.

Luna is great at following instructions but bad instructions or anything not covered = death.

Deepseek is more analytical. Good for bug tracking.

GLM is a better all rounder in some ways. Better at creativity.

Nearly every TOS I've ever read has a "We can ban you for any reason, or no reason, are under no obligation to disclose any reason." line somewhere in it.

HN's for example

> We reserve the right, at our sole discretion, to change or modify portions of these Terms of Use at any time.

> You acknowledge that Y Combinator may establish general practices and limits concerning use of the Site,

> You further acknowledge that Y Combinator reserves the right to change these general practices and limits at any time, in its sole discretion, with or without notice.

> Y Combinator reserves the right to investigate and take appropriate legal action against anyone who, in Y Combinator’s sole discretion, violates this provision, including without limitation, removing the offending content from the Site, suspending or terminating the account of such violators and reporting you to the law enforcement authorities.

OpenAI revoked my Cyber verification, along with many others, asked to reverify (i.e. give my biometric information to Persona), had me do it 8 times, just to find out several days later that they silently implemented a nationality whitelist, and my nationality didn't make it (and no, it's not a sanctioned country).

Their support says they can't look into anything or do anything, and their public spokespersons on X deny everything.

I get tons of cyber refusals now (lots of reverse engineering), so it's only matter of time when my account is going to get banned.

At least Z.AI is being honest here. And no provider other than OAI/ANT had me submit my biometric information just to use Ghidra.

Then alternatives are:

- Grok - where I absolutely have 0 trust in X.ai's interst in "pushing humanity forward".

- OpenAI and Anthropic - which seem to try to be building the biggest moat they can by pushing to ban open models. And at the same time want to be an Arbiter of what level of intelligence I can use.

- Google and Meta - I don't need to talk about the practices of these companies.

Yes, the terms of service aren't great. But the alternatives aren't great either. I don't believe that a future which OpenAI and Anthropic are pushing for has my best interest in mind.

In any case what matters is what is enforced in practice. It will be a mild inconvenience to switch providers on Openrouter.

If Anthropic or OpenAI decide to apply those same arbitrary terms, you are SOL.

>Vague prohibitions on whatever may harm Z.ai’s "interests" or even the "national interests" of any country.

[...] may cause harm to Anthropic, our users, or third parties, we reserve the right to remove or take down some or all of such Third-Party Content using, where appropriate, algorithmic and human review.

You may not export or provide access to the Services into any U.S. embargoed countries or to anyone on (i) the U.S. Treasury Department’s list of Specially Designated Nationals, (ii) any other restricted party lists identified by the Office of Foreign Asset Control, (iii) the U.S. Department of Commerce Denied Persons List or Entity List, or (iv) any other restricted party lists

>Vague prohibitions on "disturbing" or "inappropriate" content, whatever that is.

we will use Materials for model training when [...] your Materials are flagged for safety review to improve our ability to detect harmful content, enforce our policies, or advance our safety research.

>Vague prohibitions on discussing Z.ai, even my posting this comment violates it.

>Can ban you if you, in the "sole and absolute opinion" of Z.ai, have violated these broad terms, and if you paid for the discounted yearly plan kiss your money goodbye.

To engage in any other conduct that restricts or inhibits any person from using or enjoying our Services, or that we reasonably consider exposes us—or any of our users, affiliates, or any other third party—to any liability, damages, or detriment of any type, including reputational harms.

Mind you, that's Anthropic's Terms of Use in Europe. I have zero doubts the TOS applied to the US is even worse and that merely mentioning your first born in a chat entitles them to a part of its soul.

I have prompted out a lot of disturbing and inappropriate content with GLM-5.2, that would have left other American models blanched in the face or clutch their pearls. I think this is mostly a reference to Anti-CCP stuff.

In fact, I don't think I've ever even had a prompt refused.

You will get around 2-4 concurrent streams of aggregate tokens at best for such a model and around 0.5B output tokens per month assuming you use loops and run it when you are sleeping. That's 500 (per mill) * 0.5$ = 250$ only at most.

Then there is maintanence and efficiency costs due to electricity usage and such, any down time, etc.

You will be lucky if you can squeeze more than 200$ of value out of it in a month.

I don't think people should buy local hardware for money reasons, by the time you will pay off a 10K USD machine, 2-3K USD machine will catch up and beat it by a significant margin.

Unless your expectation is that we will be in hardware winter for the next 10+ years. At 200$ per month it will take around 200 * 50 = 10k, that is, 50 months, so around 4-5 years.

Again assuming you are making the most of your hardware somehow, very hard to do in practice.

I don't recommend people to use compute as investment or payoff thing, but if you have the money to burn and can afford it why not, maybe with some software optimizations it will be cheaper but then again Z.ai is currently offering 50% discount and providers will offer cheaper rates for sure.

But either way you will never be able to burn more than 200$ worth of token on a cheap hardware device, because inference becomes more profitable the more you scale it up, you have separate prefill and decode engines/systems, and a lot of nuance, but assume for every 10x increase in infra you increase margins by 5-10%.

So from 10K to 100K to 1M to 10M to 100M.. I don't think this curve continues beyond 100M but I have no idea about that scale unless some AI lab is interested in hiring me lol.

So a 100M infra will have ~30% better margins than you at 10K, then there is software optimizations but that's cheap enough, though some of it is only viable at scale.

Either way assume 10K is the price of privacy if you really want to buy it. Don't worry about making the most out of the usage, you will always be in a net loss but I would assume for you 10K doesn't matter.

Further quote:

"Compared with our initial baseline on the same hardware, we achieved a 3× improvement in end-to-end serving performance, reaching hardware efficiency and per-token cost comparable to mainstream NVIDIA GPUs. This demonstrates that Chinese chips can support frontier-model inference efficiently and economically at scale."

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

And I don't see a situation where serious API payers are OK with handing the Chinese state all their data. Like manufactures of decades past did and learned a hard, even existential, lesson for it. The state mantra has been "Collect and Copy" for a long time now, tech just hasn't had that moment to experience it yet.

So that leaves local hosting/leasing, but one of those has totally non-practical economics and the other doesn't have enough compute to meet any kind of real demand.

I also have yet to meet a single person who isn't neck-deep in the tech space mention a Chinese LLM. It's 100% the big American three.

If anything it's custom chips from the labs that threatens Nvidia.

While I think China would always get to hardware self-sufficiency eventually, all export controls have done is (1) accelerate China's development, and (2) divert revenue that would've otherwise gone to NVIDIA/AMD/etc instead.

Nvidia will do just fine. (Disclaimer: not a shareholder. At least, not directly.)

I'm sure the chips are fine, but they clearly didn't have enough capacity for the demand they had (that 100T/day claim was asbolute bs)

>> "They are already there on open weight models and Jensen knows that it is only a matter of time until China catches up with GPUs or other AI accelerators."

It is also why Nvidia becoming a bank for other AI companies who are unable to find VCs to fund them isn't really a good thing and that is bearish.

[0] https://news.ycombinator.com/item?id=49397204

[1] https://news.ycombinator.com/item?id=49431231

This announcement doesn't really mean anything at all. It means the very few people who are already using Z.ai's API will continue to do so, but the vast majority of money going to Nvidia is through the massive amount of business going to Anthropic, OpenAI, and other western cloud providers and inference providers, who are mostly using NVidia chips for inference.

Also, NVidia chips are still sold out and supply constrained.

https://github.com/JustVugg/colibri

FWIW, people were saying "ASICs will kill CUDA demand!" since the crypto mining boom. Then a few months later, CUDA found another niche application in LLM applications.

With the mounting demand for robotics, surveillance and autonomous weapons, I don't see how Nvidia couldn't keep their spot. They have their pick of the litter with hundreds of market segments, and unlike the rest of FAANG they're not afraid to branch out.

For implementation tasks, where I have the problem already defined and researched, or just simple task, I'd definitely use something like Luna xhigh or max. If the task is vague, or involves planning, I'd rather use Sol medium, even though it's theoretically worse on benchmarks.

It's at least close (even if not better) from the Ox Alpha runs. For the price it's definitely great.

│ https://openrouter.ai/api/v1/chat/completions model: stealth/ox-alpha auth: OPENROUTER_API_KEY status: 404 Not Found response: {"error":{"message":"Thank you for participating in the Stealth Ox Alpha testing period. This model was ZAI's GLM-5.3 Flash.

│ Use it now: https://openrouter.ai/z-ai/glm-5.3-flash","code":404},"user_...":"}

Have been using it as my primary harness for personal work for I'd say 6 months. I recommend everyone create their own harness at least to learn. There are a lot of practical benefits.

* me raises hand.-

Think z code gives a token bonus though

With GLM 5.1 and 5.2, the big problem was tool calling and long-horizon coherency. 5.3 was more trustworthy at the cost of longer thinking traces, and now Flash seems to improve on it once again with a more concise, smaller model. As long as there aren't any noticeable regressions, I could see myself defaulting to this for >90% of my day-to-day coding work.

edit: nevermind. it is there in the artifical analysis scatter plot, but is greyed-out.

MUCH more interesting is that in that chart, their cost is WAY off. The actual chart shows GLM 5.3 Flash at $0.09, but their chart shows $0.045...

What I'm saying is, if you're expecting a model that can be run on a 16GB or 32GB machine with the intelligence/knowledge of Mythos or Sol, it will never happen. It cannot happen, just like you cannot watch the Odyssey saved as a 16MB file.

Smaller models can get faster and smarter, but by definition they can never compress all of the knowledge of a frontier model and they will approach a limit by which they cannot get better.

That's good. Keep going.

Give it a day or two. More will pop up.