p.enthalabs

GLM-5.3-Flash

z.ai · Read Story HN original

https://news.ycombinator.com/item?id=49450353

Comments

Standard API Pricing for GLM-5.3-Flash (per 1M tokens)

- Input: $0.15 - Output: $0.50 - Cached input: $0.03

Is that cheaper than DS4 flash?
All I can say is that even if it is, I was almost glad to go back to using DS4 Flash. Because 0XAlpha was just so friggin slow to complete a task because of the level of circular reasoning that it would go over and over into, sometimes even returning no output. If I just wanted something done I would switch from a free model to a paid one which is crazy.
Tbh it was also slow because it was being hammered by everyone making use of the free tokens
Possibly influenced by that, but I believe that is a different issue. I meant the way it processed a request. It went into so many more loops of thinking.
It's even cheaper than DS4's off-peak pricing. Seems like DeepSeek have some stiff competition now
Few weeks ago, I wouldn't expect this statement to be true. Accelerate!
Comparison should be to 0731
updated thanks
Hm. GLM is more expensive in all dimensions than DS but it has a lower weighted average input? How is that?? Something seems off.

EDIT: Looks like they are swizzling around the pricing dynamically on that page, on both the GLM and the DS sides, so who knows.

I mean, it implies that it has an even better cache hit rate that DS flash, which is impressive, as the chr on DS flash was already really good in my experience
I think the weighted average takes into account all providers (some DS4 flash providers are 'premium' providers and offering higher speeds for higher pricing) and these are tilting the scale
I'm starting to think that this whole sanctioning China may motivate and prompt them to do more and better in every field.

It's too big, bright and resourceful of a country to choose confrontation instead of collaboration.

This has been clearly stated as what would happen going back several decades at least.
Starting? This was obvious way back in 2019, when the US decided to give China a little push developing their own silicon industry.
Well the big problem with china is that they do not respect international law when it comes to technology theft. But that argument is very weak when it appears that a lot of what they do is out in the open for anyone to replicate.
"argument is very weak" regardless as I said.
yeah, America is totally out there respecting international law.

"problem" indeed.

No major power respects nor cares about international law.

Intellectual property is part of WTO agreements but enforcement is domestic.

US companies do it too, regularly, they simply hire and poach staff from competitors.

Proving it to be IP theft is difficult unless you can prove documents being passed. But often all you need is the know-how of the hired talent.

There isn't one global "international law" for copyright. There are treaties that countries negotiate with each other.

If the USA wanted a copyright treaty with China bad enough, we would negotiate one. China is not breaking any laws here, international or otherwise.

if the americans didn't want IP theft, they shouldn't have taught tens of millions of people how to make their IP
> I'm starting to think

That's good. Keep going.

> It's too big, bright and resourceful of a country to choose confrontation instead of collaboration.

It's not like we didn't try it. China first have to learn to make deals where both party benefits.

I would say the Trump Administration needs to learn this as well.
America knew how to do it. But they are learning quick from China.
> with all of this traffic served on Chinese AI chips

RIP Nivida shareholders

God I wish I could’ve shorted NVIDIA right now
It's earnings day for them...
Which 9/10 times hasn't been great anyway (stock reaction).
Of course the release was not coincidental - with the earnings days - I am sure.-
And two models released same day + openai chip
Whats stopping you? You could buy puts right now.

Get a 210 strike put contract and if your thesis is that nvidias current 10 day slide continues you could make some money.

Unless NVidia craters you are likely to lose money given the IV crush that will happen today.
This is the takeaway here: That's how they have been serving it at scale as Ox-Alpha. This is a definitional moment.-

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

Anyone knows what are those Chinese chips? Can they be bought? (Assuming im not i the US, And actually im in a 3rd world country).
They are high end really expensive Huawei ascend GPUs. It is kinda bruteforcing the performance on a older semiconductor processing tech, so total production is pretty low.
> comparable to mainstream NVIDIA GPUs

By this they probably mean RTX series GPUs? If so, then they are not comparing the hardware efficiency with the A100 / H100, etc. that are commonly used for training models

This is no surprise [0] [1].

>> "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

yay, I called it! :) (in the other thread)
Another self-inflicted own courtesy of US government policy.

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.

Revoked or not, just ever having those controls signals to the Chinese ecosystem that you're not necessarily a reliable supplier (Would you trust US export policy to remain stable for the next ~decade given the state of US politic?) and to the Chinese government just how strategically important you see these components.

This isn't the kind of thing you can hash out in public and go back and forth on. Once you put it out there, the other party will take steps to make sure they don't have to rely on us in the long run.

> The export controls were revoked before

Zai is on another "export control" list outside the broader 1. Doesn't help.

The export controls were not revoked, only reduced, and not before, but after China refused to buy low performing chips. Top gear was and is still sanctioned, as is any EUVL equipment.
And to add to the above: by building their own supply chain for chips, China is helping the unprivileged, those who can't front-run the market with long-term contracts. If China wasn't producing their own chips, the prices for us would be even higher.

Similar to the war-pricing of oil, China's reduction of imports is actually helping to keep our inflation from going even higher.

And it doesn't matter, it still pushed China to speed-up their AI related hardware development.
Long term it's irrelevant. The only relevant thing is that there's lots of money in chips that can do high performance inference. You see all kinds of competitor products in development or already on the market even here in the US where there are no such restrictions. Cerebras comes to mind. It's natural and expected that eventually Nvidia will either have to keep way ahead or competition will catch up with specialized products.

That doesn't mean by any stretch of the imagination Nvidia will disappear. But the entire stock market valuation, not just tech, has had me scratching my head for a while.

Cerebras "competes" with Nvidia in the same way a Vespa scooter competes with a Ford F-150. Groq and Tenstorrent are in a similar boat, ASICs don't really threaten CUDA.

Curiously, there is not a single real CUDA competitor anywhere in the world. We almost had one with OpenCL, but all of the American stakeholders abandoned it right before the crypto/AI takeoff. All of which means that Nvidia sets their own margins, exploiting American investors and taxpayers while letting China avoid their dominance. So the American economy subsumes the bulk of Nvidia's arbitrarily-priced debt, and the Chinese economy can direct SOEs to pour billions in liquid cash into real GPGPU research.

I'm an American and I'm pretty fond of Nvidia, but Jensen was right about this policy; it gives China everything they need to actually replace CUDA. It's reminiscent of America's attempts to deprive China of ARM and Texas Instruments IP, only to end up swimming in unlicensed clones after refusing to sign an IP deal.

Not really a brag: it ran like shit. Very slow (~20tps, VERY high latency) and it would timeout all the time.

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)

seems unlikely that they'll get nearly as much demand now that it isnt free
Sure, although I still expect it to become the most used model on openrouter.
Ox Alpha is a smaller model and it was running very slowly. Chinese AI accelerators are coming along, but nVidia’s lead is huge.
Has there been any confirmation about what that model even is?

Edit: Ah:

> This stealth model was developed and operated by ZAI, revealed to be ZAI GLM-5.3-Flash.

It's also in this very announcement, in the first paragraph:

> Before release, we tested GLM-5.3-Flash anonymously as ox-alpha on OpenCode and OpenRouter to gather user feedback. It quickly became the most popular model of the week — with all of this traffic served on Chinese AI chips.

It was being served for free. They were almost certainly being overloaded.
Presumably the efficiency numbers they're quoting are for the high concurrency state they were serving.

RAM was probably the bottleneck for the amount of context they were offering.

I assume it would run a little faster with lower concurrency but "RIP nVidia" is a little premature. The cutting edge inference hardware is amazingly powerful

> and it was running very slowly

... I'm at a loss for words here. It was being served for free. To the entire world.

GPT-5.6 Luna is also served for free to the entire world with a tokens per second rate nearly 10X higher.

> ... I'm at a loss for words here

No need to be so dramatic. I think it's great that they're developing chips, but the whole "RIP nVidia" claim was overly dramatic.

Do you know how much traffic luna was getting vs Ox Alpha?
Are you really comparing chatbot to agentic/code work?

Why is Luna not free on OpenRouter? :)

Lead doesn't really matter anymore. I just ported a very old cuda library to rocm, so it can be run on MI300s. 2 years ago this would have been a nightmare. Today it was an afternoon.
Exactly. Coding for inference is solved. CUDA is no longer a moat.
Ox Alpha was also serving 10T+ tokens a day for free.

When it first launched on OpenRouter I was getting nearly 70 Tokens/second.

I don't see a situation where subscription payers move outside American LLMs (chatgpt, claude, gemini)

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.

Genuine question but who do you put as the "three" in big three.

Because I genuinely can't tell if you mean Google or SpaceX/X.ai lol.

Google probably serves more tokens then OAI and Anthropic combined, even if many of those tokens aren't from explicit gemini requests, but from AI overviews and other service integrations.

xAI is already selling spare compute, and basically exists just to gas spacex's perceived valuation.

I can easily see a situation where most non American AI usage is on Chinese models on Chinese chips though.
These open models serve as price / performance pressure. Not all tasks require frontier models and cheap open models can be quite good for in-app assistants, if you're building that sort of thing. We also aren't sure the subscriptions will continue to be sustainable. They're currently subsidized to the tune of 50-70x. As someone who is hitting limits weekly that would easily cost me over $10k month per sub.
Casual consumers are using American models because their usage is low. As usage scales, the economics heavily favor open weight models. The API pricing from American companies is absurd. This is particularly true in an enterprise setting.
Open weight model hosts don't have the compute to meet enterprise demand. A large part of why these models are so cheap is because overall demand for them is incredibly low. Back in May, Gemini alone was doing about a month's worth of Openrouter tokens every day.
I disagree totally. DeepSeek raised prices because they couldn’t serve the demand. But there are tons of American vendors ready to fulfill it. Many enterprises, including the one I work for, are swapping to open weights.

Why wouldn’t you?

I am not ok with handing all my data to American companies that are best friends with the American surveillance state. I still remember the Snowden revelations. Chinese companies are a much better option in that regard.
you don't have to hand them your data, the models are available so you can run them on bedrock yourself (or use another US housed inference service). and for what it's worth in my job i have access to data that gives a picture of the way companies are doing inference, and they're using a lot of chinese models (deepseek-v4 is a huge percentage of inference requests for example)
Most US companies that have anything to do with government, finance, medical, etc. already have contractual or regulatory obligations which prevent them from using Chinese hardware or services, even before the AI boom. That's a huge market.

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

> Most US companies that have anything to do with government, finance, medical, etc... That's a huge market.

Compared to the rest of the world?

I don't have any pie charts in front of me, but yes, I would estimate it's a decently big slice of the world market.
bigger than RotW
Not really. Chinese AI companies were never using NVidia AI chips.

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.

Weights on HF here: https://huggingface.co/zai-org/GLM-5.3-Flash

I decided to take the plunge and get myself four sparks at a decent price (and bought the QSFP cables from AliExpress because they are literally 1/2 the price of Amazon), even knowing Apple was going to release new hardware and there's probably a spark 2 on the horizon. It looks like this is going to be a decent fit for what I need. I've been experimenting with a two-node DS4 and it's _good_ at some tasks, but it really just spins its wheels when it hits the limit of what it can reason through.

I can offload mundane/basic tasks to DS4 on two sparks, but I've been pushing it harder on some novel work and it just can't run on its own at all beyond a certain complexity level.

I would love to see an Opus-4.8-level local model but TBH I just haven't got there yet. The models I've tried so far _are_ good but they aren't able to solve tough technical challenges, regardless of harness/prompting/etc.

> get myself four sparks at a decent price

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

I bought 4x Asus GX10 with the 1TB option. I don't understand why, but it's the only model in the whole lineup that isn't priced insanely.

They were briefly on sale with a $200-off coupon, but they show up on warehouse deals from time-to-time as well.

> it's the only model in the whole lineup that isn't priced insanely

$4,000 isn't priced insanely? ye gads

I thought 4000 in sum. No wait, 4000 per, plus tax. Or EUR pricing to similar accord. Ouch.
Yeah, that little cluster costs about the same as a brand-new Dacia Sandero.
Yeah, yeah. BUT, will the Sandero be ... load-bearing? :)