GLM-5.3-Flash (z.ai)

606 pointsby Philpax5 hours ago280 comments

mmastrac 5 hours ago

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.

kilroy123 5 hours ago

> get myself four sparks at a decent price

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

mmastrac 5 hours ago

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.

swiftcoder 4 hours ago

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

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

a3w 4 hours ago

I thought 4000 in sum. No wait, 4000 per, plus tax. Or EUR pricing to similar accord. Ouch.

swiftcoder 4 hours ago

Yeah, that little cluster costs about the same as a brand-new Dacia Sandero.

Bluestein 4 hours ago

Yeah, yeah. BUT, will the Sandero be ... load-bearing? :)

KptMarchewa 3 hours ago

It can bear the load of a few people, at least.

PcChip 4 hours ago

to save others from having to look up what that is like I did, it's a car

esafak 4 hours ago

Yes, but it was $200 off!

swatcoder 4 hours ago

Compare to the cost of professional-grade tools in other trades and craft hobbies.

Sure, $4000 can be a lot of if you're a casual hobbyist or are struggle to meet everyday lifestyle costs, but it's definitely not "insane" if this is the trade you make your living from or if you've established a lifestyle that affords disposable income for your hobbies.

And for some people, $4000 for a device you have complete control over and can repurpose and tinker with to your own needs and curiosities is a much much more justifiable expense than a $200/mo rental for some narrow-access tool that somebody else controls.

swiftcoder 4 hours ago

It's "insane" compared to the $1,500 it should have cost before the RAM crisis

chews 4 hours ago

I am pretty confident that given a $200 subscription on any of the big labs, you're getting $4000-$8000 per month in subsidized tokens... do what you wan't with your dough... and I too have a spark that I got really early (October 2025), but no, economically it does not compare to what's runnable locally in terms of quality from the frontier models. Economically, it looks like for as long as there are subscriber plans, you're better off renting.

Before getting the spark, I was just using a google colab account, their $49 dollar plan allows you access to h100's and I can run qwen there in a Jupyter notebook... and if I really need that web front end I can just use cloudeflair/tailscale/the local ssh client to reverse tunnel it.

overgard 3 hours ago

The cloud stuff is definitely a much better economic value, but I would argue:

1. You learn a lot more running this stuff yourself (especially since you can poke at its internals if you're interested or watch the reasoning chain.) Just being a consumer of this stuff doesn't really teach you much about it other than model & harness specific tricks that become obsolete pretty quickly. (IE, your Claude.md from 6 months ago probably needs a rewrite). Which is fine, I don't think you're going to be "left behind" if you're not a hardcore AI enthusiast or anything (I'm not), but as a guy that's always been interested in computer science I want to see how it ticks.

2. You can't really depend on this subsidization lasting forever IMO. I know the financials thing has been beaten to death but I guess I'm in the camp that it's good to be in control of your tools so that you can go elsewhere if the economics change.

I like to check in with ccusage pretty frequently, and honestly like if I were paying API prices for Claude I'd probably be paying thousands a month.

lukan 2 hours ago

3.privacy

Any organisation or individuals not wanting to have their sensitive data flowing away (either because of trade secret or data protection laws)

jrockway 3 hours ago

I am also not sure I would choose to use the cheap and easy to run at home model, given a choice. The marketing copy says this is a frontier model, but it's not. Sol and Mythos are the frontier right now. GLM 5.3 Flash simply isn't. I'd rather use the frontier model as they waste less of my time than even Opus.

booty 2 hours ago

Anecdotally, ~$500-1500/month token spend at API OpenAI/Anthropic pricing seems pretty realistic for full-time engineers at companies with "liberal but not unlimited" LLM spend policies.

This is of course anecdata. I know plenty of outliers, too. I know a principal engineer who uses many multiples of the number I quoted above. I am sure we also know many people making do with much much smaller budgets as well, via all kinds of well-discussed methods.

But, "$500-$1500 per month per full-time developer" is just kind of the personal mental baseline I use when making my decisions with regards to thinking about whether any of this makes any economic sense.

chasd00 2 hours ago

This should be obvious but with a model running on local hardware you can do your own RLHF and mod its behavior however you see fit. With cloud hosted models you can't. A few years ago when the models were smaller there were people undoing the guardrails, censorship, and general lobotomization with some form of a RLHF training. You can't do that on larger models unless you have the hardware like this person does.

Notice all the comments saying like "omg why so expensive so just use the API??". It's a trick for lockin even with, so called, "open" models. Keep trying to run them locally, keep undoing the lobotomies, mod model behavior so that they work for you and do what you want vs only what someone else says they're allowed to do.

rudedogg an hour ago

> You can't do that on larger models unless you have the hardware like this person does.

Or just rent something substantial for like $4/hr on runpod or w/e to do that.

My gripe is this persons compute is wasteful and makes it harder for me to buy something with like 64gb ram to do normal work and run containers while I keep using cloud models.

Someone else calculated the break even being 10 years, it’s just dumb. And I think it’s clear there won’t be a big rug pull anymore, there are too many open models and providers now.

vehemenz 3 hours ago

That's only half the reason it's expensive.

The other reason is that it would likely take years to spend $4000 (plus the real cost of electricity) worth of tokens on a 3rd-party provider that's running a similar limited, DS Flash type model. By that time, the hardware will be obsolete, assuming it's still operational.

swiftcoder 3 hours ago

> it would likely take years to spend $4000 (plus the real cost of electricity)

Since that cluster only yields 20-30 tok/s on that size of model, at least a decade before the hardware breaks-even with current token costs, and that's not counting electricity. Assuming continued downward pressure on token prices, and the cost of electricity, it never pays for itself.

dannyw 3 hours ago

As a counterpoint, my homelab/home-LLM hardware has appreciated in value by about 60% since I bought it.

Of course, it's not real unless I sell, and the value will eventually go down, but so far I have significant paper profits.

Also, DeepSeek token prices are continuing to _increase_, not decrease.

swiftcoder 3 hours ago

> DeepSeek token prices are continuing to _increase_

One increase does not a trend make. And the current crop of models are now undercutting deepseek flash...

Implicated 2 hours ago

You can't possibly think that it's going to get cheaper and cheaper to pay for tokens though. Right? Have you seen what's happening with Codex/Claude subscriptions? Deepseek raising API prices.. We've been getting subsidized tokens for some time now and as the hardware costs skyrocket these labs/people with inference compute are going to continue to clamp down.

swiftcoder 2 hours ago

> You can't possibly think that it's going to get cheaper and cheaper to pay for tokens though. Right?

Absolutely I do. Each generation of open-weight models has come with significant efficiency improvements, and there are significant hardware gains on the horizon: both increasing competition from Chinese chip manufacturers, and new custom silicon from the established players. And unlike Anthropic and OpenAI, most of the pure inference providers aren't massively leveraged - the more hardware they can bring online, the cheaper they can serve tokens.

maxglute an hour ago

$40,000 GPU is like few pennies in sand. Only mildly hyperbolic. But a GPU fresh out of fab is $2000 after ASML, TSMC and inputs get their 50-75% margin, then somehow $40k laundered through US financialization / Nvidia margins. Commoditized GPUs shouldn't cost more than 1-2% current price once there's competition.

nkozyra 2 hours ago

I don't understand how people don't consider this.

Plus you're spec'd out of near-SOTA level in months.

The only reasons to actually do this are a) you have a lot of dispensable income and are a hobbyist/tinkerer, b) you have real, legitimate privacy concerns or, relatedly, c) you're doing something you don't want to get flagged

billiam an hour ago

"you don't want to get flagged"

Ding!

nightski an hour ago

Not everything is about pure cost. Maybe I don't want to sell my soul supporting the frontier labs because they are straight up pure evil?

nkozyra 31 minutes ago

I barely see a difference between buying the hardware that feeds (and often colludes with) those labs, at least not as a moral stance.

Even if you trained your own model, you'd be committing some of the same sins, paying for the same hardware that drove it, etc. But if you're using some open model, you're standing on the shoulders of the same corrupt giants.

I feel like when people say this is due to moral reasons, it's to justify an expensive hobby.

KronisLV 35 minutes ago

But if you can use cloud models, why wouldn’t you use SOTA? For 2400 USD or less per year you can get pretty huge amounts of benefit out of that (though at the whim of whoever you are giving the money to).

croes 2 hours ago

For $200/mo you either have a SotA model you can’t run on those devices or you have a cheaper model where you pay less than $200 or have a really big amount of tokens without the energy costs and the risk of failing machine

booty 2 hours ago

Compared to pricing from 3 years ago, it's insane.

The Sparks admittedly are kind of anemic: 273GB/sec is the same bandwidth as a midrange 4060, although (depending on how you configure things) you can effectively have much greater bandwidth by connecting them.

Compared to 1-2 years worth of LLM tokens for a full-time software engineer making $100K+/year, a one-time spend of $12K for 4 Sparks for on-prem private LLM inference starts looking reasonable, particularly if privacy is an important consideration. It starts looking even more reasonable if running something like a private cloud to service multiple developers because then you likely need less hardware per developer.

(Also, it is going to be a long time until RAM+GPU prices return to what we used to call "normal." If ever. I am not endorsing the current state of affairs and I am not saying you wrong to find it insane, but it is definitely the new reality)

TacticalCoder 2 hours ago

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

It depends.

My bicycle was in the 5-digits brand new (now I paid it 1/5th of that and I do thank the first owner for that: the 8 000 out of 10 K I saved were put into stocks, that's his opportunity cost, not mine).

Or I know a great many a going to cry "audiofool", but I can say with certainty the following does sound better than the stereo setup of those crying audiofool:

https://youtu.be/TQg9FTBMcTQ

(not my setup but I've got those speakers: same thing, 15 K EUR brand new for the pair... Previous owner forked the money to buy these brand new and, well, I didn't... And I just hooked them to a wonderful, cheap, fully-integrated Yamaha amp: amazing sound).

If your hobby is DIY job around the house, the cost of tools can very quickly add up too: having 20 K worth of tools is definitely not unthinkable.

You like old cars? Pricey hobby.

Some here even track their cars: tires and brake pads budget (and overall car budget and depreciation)... Through the roof.

There's a saying that you're not really into computers if your setup doesn't cost more than your car.

Is $16 K ($4 K x 4) a lot? It's six months of rent for me and for many here I'm sure. It's not "crazy crazy".

Can anyone afford that? Definitely not. But there are way more insane things out there.

And thanks to the individuals that go through to all the pain of setting those up, we've got feedback, tutorials, explanation, numbers, etc. as to how to run those at home.

For example I helped my brother set up VMs and GPU passthrough and he's now running uncensored models locally and showing me the different answers between the uncensored models and the commercial, censored, ones.

So to GP who bought four of these: we need more people like you on HN, keep it going, blog about it, be "crazy"!

nijave an hour ago

"For new hardware in 2026 with 128Gi of high-speed memory"

Checked a couple days ago and looks like we're at about 3.5x 2020 memory prices (looking at just $/GB).

bmurphy1976 4 hours ago

~$4000 USD each on Amazon, $175 for the cable.

mmastrac 4 hours ago

The cables are ~USD $50 from AliExpress although I'm not sure what the tariff situation is for Americans (I think I paid $75 all-in CAD for them)

nijave an hour ago

Big "depends". Ali has "ships from China" and "ships from US" stuff. In a lot of cases, though, Amazon also tends to have cheap Chinese knockoffs for a comparable price (although sometimes their product ranking buries them and/or promotes the more expensive knockoffs)

Edit: Yeah I see an ONTi QSFP56 on Amazon for $45, 10Gtek QSFP112 for $62

cmrdporcupine 4 hours ago

I mean, I have the same machine and the pricing is only what it is because it has that 1TB nVME in it instead of larger. nVME prices are insane and have been for months.

Reality is on a single spark I'm constantly running out of room and it being an odd size M.2 slot it's a pain to upgrade. I'm setting up a NAS over RDMA via ConnectX though, that's fun.

mmastrac 4 hours ago

I already have a recycled QNAP-now-TrueNAS that has 10G connections into the fleet so the 1TB doesn't bother me at all. I did some rough math and I don't think I'll ever need to load weights off NFS for what I'm doing so far, but the capability is there.

ycui7 an hour ago

because it has 1T ssd not 4T

0xbadcafebee 4 hours ago

If you used the bare API pricing, 1M tokens @ 30% input/70% output/50% cached, you'd pay $0.05805. Even with four discounted sparks, how much are you paying for the same tokens/distribution?

swatcoder 4 hours ago

There's soooo much by way of experiments, explorations, tinkering, and even projects that you can't possibly pursue through a some SaaS API.

The more reasonable comparison is against rented GPU's, while looking at tradeoffs in latency and upload/download/storage/instance management overhead.

Buying hardware for local models is meeting a wholly different need than buying tokens through OpenRouter or whatever.

mmastrac 4 hours ago

For me it's entirely because I have a bunch of projects with my own personal data that would be tough to do with openrouter/claude or any other cloud.

For example, I have a small posix-shell-based LLM harness that can SSH into my NAS and run organization tasks using the local DS4Flash that I have right now. It's already been a massive help for me to keep me organized, and that's just 2x DGX Spark's worth of compute.

vehemenz 3 hours ago

It cuts both ways. A GPU in your basement is a depreciating asset with fixed computing power and consumes electricity. Switching model providers is trivial.

bityard 2 hours ago

> A GPU in your basement is a depreciating asset

All decades prior and up to about a year ago, I would have agreed with you. My Framework Desktop, however has appreciated in value by 75% since I bought it. Will it stay there for a long time? Probably not. But it shows that there are no hard and fast rules about things anymore.

topato 2 hours ago

I just bought a Framework Desktop. Would have been nice to get it at the introductory price, or perhaps the new 192gb model refresh they’re now teasing, but I settled and got a 64 gb model. At the time, the 128’s price had already risen again, but the 64’s price was still at a lower price.

64 can still easily do a Qwen 4.8 model, so I’m relatively happy with my purchase… plus, it’s price change has caused it to quickly appreciate in value… so I could sell it if my situation ever turned dire lol

Implicated 2 hours ago

At the current point in time I'd argue it's more about opportunity cost/value.

If I'm a professional photographer chasing the best possible end product, I'm not buying cameras because they're economical. I'm buying the best camera I can get my hands on to get the best product I can produce within reason under the understanding that it doesn't have to equate to the best economic decision to be the _right_ decision.

If you're in a position to be able to take advantage of the local inference - it's a no brainer. If you're not sure how that would be done, then it's not a good move.

Implicated 2 hours ago

If your usage wouldn't change with local inference and you don't have security/privacy concerns then at the currently heavily subsidized pricing, sure.. not economical.

But things change real fast when you're no longer bound by costs/apis/rate limits. All of a sudden it's not about "how can I do this right and efficiently" and more about "I can poke at and test _all the things_ that might make this better".

I think most people who can't see this value in the local inference approach are likely still copy/pasting from their web LLM ui's or don't even come close to subscription quotas. Meanwhile, 1b tokens a day is a light day for me with 3 $200/m subscriptions + some level of sub at basically every frontier level provider. Had I been less frugal and ponied up for the hardware before things got crazy I wouldn't need 80% of that - just the frontier models for the most complex tasks, the open weight models would handle the rest easily _and_ I'd get to do a lot more exploratory work without concern about quotas.

hypfer an hour ago

What do you do with all those tokens?

Aurornis 4 hours ago

> 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.

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.

disiplus 4 hours ago

To be fair, there is no 3 turns that I don't have to jump in into what Opus 5 is doing. There is either some regression or my prompting skills are so much worse now. Flash is not perfect and honestly some things depend on how big context do you keep. So I'm keeping like a really short context with my flash, but it works okay, even though it has a tendency to overthink, and yeah, I run it always in max effort mode.

Implicated 2 hours ago

Use Opus 4.8. 5 is absolute garbage.

Don't use DS4 Flash in max effort mode. It's just spinning its wheels, in my experience (I have a harness for testing models with 25 real bugs/features/etc from my real projects that I measure outcomes against) DS4 flash does _worse_ with max effort. It will literally have the right approach and reason itself away from it.

disiplus an hour ago

i have heard that for max effort in flash and it can be true, but overall it still performs better then the high, i run a mixed q2q4 quant.

KronisLV 25 minutes ago

I don’t know how 5 can do so much better in benchmarks but absolutely suck to use in practice compared to 4.X. Fable feels better, Kimi and GLM also feel better sometimes but tbh all of them make plenty of annoying mistakes.

weitendorf 3 hours ago

I have exactly the same opinion

Over the last couple years I’ve had to learn sales and understand the thought process behind this better, and I think I’m beginning to understand it

The psychology is that most people aren’t really trying to optimize for productivity (even most people who think they are) on an ROI basis, because their compensation is too decoupled from their actual raw output, and more closely coupled to how differentiated their marginal contribution is to peers. They’re much more incentivized to spend their personal/work time optimizing for being more skilled or acquiring some kind of competitive advantage relative to baseline.

Most people don’t consciously run the numbers of “I get paid $X/hr to add $Y of value” or model pay at work as something with variable inputs (eg something that can be increased with high performance), so it makes sense to them to spend 20 hours of time to save $100 or to make themselves 5% less efficient to take home 0.5% more or avoid doing something they don’t want to start doing.

NOT saying this always happens or that they’re stupid for doing so. I didn’t even realize how much I had been doing it myself until I started recognizing it, and shifted to having my own comp/performance fully aligned with the company’s P/L.

It actually makes a lot of sense IF you can accurately estimate incremental upside (which is much harder and more diffuse than modeling downside if you’re salaried a employee) or if the upfront skill/knowledge investment that looks like bikeshedding pays off in the long run.

chasd00 2 hours ago

These are great points. It's a little off topic but what you bring up is why i advise new grads to spend the first couple years of their career in small eat-what-you-kill companies. I think software devs who start out in large companies get this distorted view that their twice a month direct deposit is just magic and comes from the ether no matter what they do. The whole industry would be better off if everyone started out in a "you don't deliver, you don't eat" company and grew from there.

weitendorf 2 hours ago

Strong agree, but I also think some roles in big companies (for me, infrastructure) or in certain industries (eg trading/finance) can help build the same understanding without as much of the variance/raw exposure to bottom line.

Now that the role of the ticket-cruncher is on the path towards full commoditization, and individuals can move much more quickly (and even more carelessly!), I think product roles will probably shift towards one where developers are more deeply embedded in the product/business process so that they own/understand what to build without as much separation between the decision-making and prioritization of what to build. Or at least, they should.

It was eye opening to me to run the math of "should X people work for Y months on this project to save Z per year?" and realize that in so many cases, the time and effort it would cost to stop "wasting" money on things is WAY more than you could actually save on it. Even "small" projects can very quickly become $1M+ investments in time and resources, and the diminishing returns add up quickly (but also a good way to justify the value of your contributions, when done). But the job only exists if it saves money or makes money...

disiplus 4 hours ago

I will give it a try, but from the benchmarks it never exceeds the DS4 flash benchmarks by significant margin and And I feel that the throughput that you will get on those machines or what I'm getting with my local hosted flash will be so much worse that it's not worth it.

wolttam 3 hours ago

Hopefully you also bought a switch

whalesalad 2 hours ago

they have 2 interfaces each so you typically daisy chain them

wolttam an hour ago

That will hurt latency and latency is very important for good tensor-parallelism performance

metadat 3 hours ago

Qwen 3.8 27B is around Opus 4.8 level of capability on the Agentic Intelligence Index (52 vs 57). In my testing the locally hosted Qwen is good enough that looking at a given piece of work output I couldn't tell you which model was behind it.

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

Implicated 2 hours ago

As a counter to that - I've tried various flavors/quants/full weights and Qwen 3.8 27B has been entirely useless at anything non-trivial. Sure - it can do some boilerplate work (though, even armed with a well written spec and working within a very well known framework it went off the rails and did things in a way that were... um... questionable at best) but I don't see it as anything more than a personal assistant style model. Zero chance I'd "work" with it, I spent days trying to get it to do something for me that was usable that I didn't have to have reviewed and refined by a frontier level model or myself. Couldn't do it. The idea that qwen 3.8 27b is _anywhere near_ Opus 4.8 is laughable. Pure benchmaxxing.

DS4 Flash 0731, on the other hand, wildly opposite experience. Would recommend.

GLM 5.2 - even quanted down to a hybrid 4/3 bit setup is amazing for everything but the hardest/most complex stuff in the same projects/realm.

skohan 2 hours ago

I've had the exact opposite experience. I've been using 3.8 for my daily driver since last week, and I've gradually been giving it more and more complex tasks as it continues to deliver high quality results. Now I am basically handing off large complex features, and 3.8 is doing the planning, task breakdown, implementation and review with just a few notes from my side.

The tradeoff is time (especially on RDMA4 hardware) - it does take a long time and spend a lot of tokens to get to the result, but I've found I can trust the results enough that I can queue a lot of work, essentially have it running all the time and achieve a decent velocity.

It's the first small local model I've felt like I can do real work with.

szundi an hour ago

Fascinating that after years of for me this for me that, literally no one writes 2-3 other words like “i do react frontend” or whatever just for us to know why the results are different

throwaway240403 34 minutes ago

lol, exactly.

mmastrac an hour ago

What harness? I've had similar results as _Implicated_ said above - it's not done well in any of the tests I've tried with it. I currently have it hung off DS4Flash as a pseudo-vision tool and subagent only because of this.

DetroitThrow 2 hours ago

Lately I've been throwing tasks at Qwen and a frontier or recently-frontier model (as well as Kimi, GLM, etc) and the smaller parameter models are not really comparable to Opus when it comes to making intelligent decisions about greyer areas of good software architecture.

Amazing results for open weight and that size, but a really long way off, and I'm extremely skeptical of benchmarks that show these smaller models as being anywhere close to Opus 4.8 (or even earlier Opus's).

zerd 33 minutes ago

I’ve been doing the same thing, giving the same tasks to Qwen 3.8 27B and Opus, and the main difference is that Qwen does not consider edge cases which Opus catches. It’s good at the happy path, but even when hinting that there are uncovered edge cases and gotchas it’s oblivious to it. So I feel like I need a bigger model to do planning/review.

Jeremy1026 38 minutes ago

I gave Qwen 3.8 27B and Opus 4.8 the same task in the same codebase. They both came up with the same diff. It wasn't a particularly challenging task (removing a feature flag and updating applicable specs), but it was character for character.

comandillos an hour ago

I am surprised. I've been using DS4 Flash (0731) for weeks now and it works perfectly fine as a replacement for Claude in a large variety of cases. It requires a few more iterations, sure, but it's useful enough to not need a Claude subscription anymore. Among the things I do I've been reverse engineering, writing complex C++ code...

badatnames an hour ago

DS4 Flash absolutely kicks ass for reverse engineering and bug hunting. Almost no point in considering paying for a bigger model, although it's possible the stuff I've fed it (wide variety of older DOS/Windows stuff and device firmwares) might be easier targets.

comandillos an hour ago

I've been reverse engineering LEON3-FT SPARC v8 BE code, so I wouldn't say it's common :D. When attached to Ghidra through a MCP the things you can do with this are simply crazy.

badatnames an hour ago

Curious what MCP setup you use? I'm not sure which one I have wired up, but I have to restart Ghidra every time I change file. I think it's either LaurieWired's original or a fork of it

comandillos an hour ago

https://github.com/bethington/ghidra-mcp . Works flawlessly.

badatnames an hour ago

Ha - I saw this, but took one look at the slopfest README and it sorta scared me away. Will give it a go thanks.

mrngld 4 hours ago

Chinese labs are so used to manipulating benchmarks to try to flatter inferior models that when they finally have one that's really pretty good I think the official announcement here undersells it.

https://deepswe.datacurve.ai/

That's pretty solid. Smarter and cheaper than Luna xhigh, not as smart but less expensive than Luna max. Smashes deepseek v4 flash, and even worse it matches v4 pro at a tiny fraction the cost. Roughly equivalent to sol medium, at a fraction the cost.

They should've just lead with real, up to date data, because it's good, not the silly old tactics like comparing to Opus 4.8 when 5.0 is out in many of their charts.

Congrats to them!

redox99 4 hours ago

It's also better than Sol (at whatever effort) at designing pretty UIs. I have a Codex sub and I've been using this model for UI stuff.

mkagenius 2 hours ago

> I've been using this model for UI stuff.

The flash one?

redox99 2 hours ago

Yeah, when it was secretly called Ox Alpha.

glub 2 hours ago

Yes. I have no UI experience, and wanted a model that could produce something good without me telling it how anything should look like.

My prompt was something like: "here's data I have, here's what matters to me, create HTML mockup".

All GPT 5.6 models were laughably bad. And I don't want to downplay it - they were just absolutely, objectively horrible. Every single attempt was what I could probably call "if json was ui".

Claude models produced... "claude look".

GLM 5.3 - somewhere between GPT and Claude.

Kimi k3 - each attempt produced beautiful UIs. It used components that I didn't even know existed and wouldn't even know to ask for. But expensive, very expensive.

ox-alpha (GLM 5.3 flash) was very close to K3. And at this price point, it's already configured as "designer" model in my oh-my-pi.

redox99 2 hours ago

Yeah, exact same for me. K3 used to be my go to for UI but it's quite expensive. Ox alpha being so cheap and so comparatively good at design is crazy.

I haven't tried it but I think Qwen Max is also very good at design.

seaal 4 hours ago

Only 73K output tokens too. Anthropic should really be embarrassed with their Sonnet 5 price/performance.

stavros 3 hours ago

Opus 5 is better than Fable in this benchmark?

zarzavat 3 hours ago

Even Artificial Analysis has Opus 5 better than Fable in their aggregated "Intelligence Index" which combines 9 benchmarks. Opus 5 is heavily benchmaxxed.

re-thc 3 hours ago

> They should've just lead with real, up to date data, because it's good, not the silly old tactics like comparing to Opus 4.8 when 5.0 is out in many of their charts

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.

cameronh90 3 hours ago

Maybe others have found otherwise, but I find the benchmarks drastically different to real world "feel" of a model, even within the same harness. I'm not sure if this just reflects personal interaction styles, or if it is indicative of benchmaxxing or unrealistic automated benchmarking methodology.

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!)

trey-jones 3 hours ago

I've been using 5.3 since they initially announced it and my gut feel is that it's not as good as 5.2 for agentic tasks. I'm still using it - I don't think it's bad. I'm just not convinced it's better.

disiplus 2 hours ago

idk i think that i spend significant tokens with both to be able to tell 5.3 is way better overall.

https://kommodo.ai/i/IFSUUQYT522uZXWvePZ1

it still fells stupid sometimes and it is benchmaxxed for sure. but its good enough that im building all the hobby projects with it.

glub 2 hours ago

I don't know how anyone can actually use Luna max on ANY real workload. I've had Sol orchestrate a bunch of Luna agents, these agents were explicitly given small chunks of larger objectives and they still filled their entire context windows with just reasoning tokens, until compaction hit, and then reasoning again.

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.

amluto an hour ago

The one time I tried asking Sol to use subagents for a small project, it took a surprisingly long time, used up the entire usage limit in one go, and basically failed the project.

I’m pretty sure that plain Sol, serially, could have finished the task faster, cheaper, and far more accurately. I’m also pretty sure that any competent subagent orchestration could have gotten it done with even very simple subagents quickly and cheaply.

(Is it really that hard to set up a handful of subagents that all use the same initial context and to load that context with what actually matters? The APIs certainly support it.)

John7878781 32 minutes ago

Luna max is all I use. In my experience, it works really well for overnight tasks.

kilroy123 28 minutes ago

I feel the same. I just use it for planning and chatting. Not real coding work.

bertili 3 hours ago

This is going so fast! What a time to be on hackernews:

July 16th: The "Kimi K3 moment" - China has caught up to Opus!

4 weeks later: GLM 5.3 - Same performance, but cut the amount of parameters and cost to a third!

12 days later: GLM 5.3 Flash - Almost GLM5.3 performance but cut the parameters in half, cut prices to a fifth and serving on Chinese chips!

jatins 2 hours ago

except besides benchmarks, most of these models don't meet reliability of Sol/Opus in coding work. Opus unfortunately talks very weirdly so not a great out of the box experience

Alifatisk 2 hours ago

And don't forget the coolest part, DeepSeek, Qwen, Z.ai and Moonshot have almost caught up while being open about their research and their model weights. We can mostly speculate about OAI and Anthropic models, nothing else, how fun huh?

kzrdude 2 hours ago

Exactly, DeepSeek, Qwen etc are catching the attention because they put out their tech docs and papers, so we can read about how the models work and what they think their innovation was this time.

matheusmoreira 4 hours ago

You guys read Z.ai's terms of service, right?

Broad and perpetual license over inputs and outputs, and even your name and profile picture.

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

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

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.

Lwerewolf 4 hours ago

The model weights are MIT licensed.

matheusmoreira an hour ago

I'm talking about the Z.ai service specifically.

g3f32r 4 hours ago

Isn't this practically every TOS though?

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.

matheusmoreira an hour ago

> Isn't this practically every TOS though?

Not even close. Even OpenAI and Anthropic aren't bad enough that they claim literal ownership of your inputs and outputs.

> HN's for example

You're not paying to use HN. Getting banned here has essentially zero consequences.

If Z.ai uses its absolute powers to ban you because you wrote a review about them or something, then you lose actual money. This is especially relevant if you're looking to take advantage of their discounted yearly payment option.

KronisLV 19 minutes ago

Consider the reputation implications of them banning someone who can get their complaint about it to the front page of HN and into the YouTube drama loop. They’d get swarmed with activist cancellations.

At most I suspect the A.I. providers will just come up with yellow banners like Anthropic did where naughty smut writers get put in the time out corner.

zaj00l 3 hours ago

I get all that.

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.

bestouff 3 hours ago

Or Deepseek, Qwen, any other open model hosted by whoever you trust most.

zuzululu 3 hours ago

All the American companies you mentioned still follow American law and regulation. Skirting that blatantly has big consequences.

Chinese companies do not follow American laws and there are absolutely no consequences for violating it.

Moreover, the average American is not even aware of exactly what the legal/judicial environment is like in China. If your code and data is stolen, you can't fly to China and demand justice in the courts.

croes 2 hours ago

Aren’t those American companies sued because they didn’t follow American law?

Implicated 2 hours ago

> All the American companies you mentioned still follow American law and regulation. Skirting that blatantly has big consequences. > Chinese companies do not follow American laws and there are absolutely no consequences for violating it.

... lmk when anthropic/openai/spacex/xai are held accountable for anything. Anything at all. Hard to be when you're _writing_ the rules.

twobitshifter an hour ago

Is copyright infringement an American Law?

jst1fthsdys 20 minutes ago

> All the American companies you mentioned still follow American law and regulation. Skirting that blatantly has big consequences.

No, they don’t. This is an absurd statement to make in 2026.

matheusmoreira an hour ago

> I don't believe that a future which OpenAI and Anthropic are pushing for has my best interest in mind.

I don't believe in that either, but these totalitarian terms are absolutely unacceptable.

zarzavat 3 hours ago

It's China. It's a given that they use your data for training. At least they're nice enough to be honest about it.

yogthos 3 hours ago

It's not like US companies don't do the same either.

trvz 2 hours ago

It’s implied that they do, but don’t have the balls to tell you they do.

scotty79 3 hours ago

TOS is and will ever be just a "pretty please".

microtonal 3 hours ago

The model is MIT-licensed, so run it on any of the non-Chinese inference providers that will host it in a few days.

PhilippGille 44 minutes ago

NovitaAI is already hosting it: https://openrouter.ai/z-ai/glm-5.3-flash#providers

realusername 3 hours ago

They all do that, some are just more honest to tell you upfront than others.

NicoJuicy 3 hours ago

Chinese laws are not valid in the EU

jtbayly 2 hours ago

That’s pretty funny to say when the EU claims GDPR applies worldwide.

croes 2 hours ago

What they don’t do. They claim that the GDPR applies if you provide your service in the EU, and that’s a valid claim.

singularity2001 3 hours ago

I blocked Z.ai as soon as they were loading 10 different external providers including Alibaba who was just proven to execute silent sound fingerprinting mechanisms.

colingauvin 3 hours ago

Who the hell cares when I can run it myself?

throwawayffffas 3 hours ago

None of that applies if you run it at home. Also 3rd party providers will start serving this pretty soon under different terms.

matheusmoreira 44 minutes ago

> None of that applies if you run it at home.

Yeah, running frontier open weight models on my own hardware has essentially become my dream at this point. I hope the hardware manufacturers step up production to meet consumer demand.

mrinterweb 3 hours ago

Give it a couple days, and there will be plenty of other inference companies hosting it. Don't like z.ai's TOS? Use the model on a provider with TOS that you agree with.

glub 2 hours ago

> Can ban you if you, in the "sole and absolute opinion" of Z.ai, have violated these broad terms.

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.

matheusmoreira an hour ago

> 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)

How did you discover this?

I opened the Persona tab once, closed it and the tab never opened ever again. "Precheck failed".

What countries are banned? I'm from Brazil.

I went as far as initiating an LGPD (brazilian GDPR) process against them due to this. At some point I got it in writing that I'm allowed to make a new account and try again. Until now I was assuming it was just some weird account state. If I'm banned from TAC due to my nationality that's seriously disgusting...

glub 21 minutes ago

When they initially revoked TAC for a bunch of users due to a "technical error", the TAC verification flow opened a Persona iframe where you select the document country first. I was able to select it there (Georgia, in my case), went through the entire flow, and then got locked out after 8 attempts. Persona itself was successful end to end, so it failed somewhere on the OAI side. Other users then started reporting the exact same issue on the OpenAI forum.

A week later, I tried testing the TAC flow on my SO's account, which had never had a TAC attempt before. Selecting Georgia in the Persona iframe now says, "We are unable to verify identities in this country."

But I know this isn't a Persona limitation, as I verified with Anthropic using Persona the same day.

So what I think happened was this: OpenAI silently implemented a country whitelist on their end and revoked TAC for affected individuals who already had it, calling it a "technical issue". They forgot to disable those countries in Persona, so everyone just got a cryptic error. Then they disabled them in Persona too.

Interaction with support was AI with human names, which essentially just repeats what you said. And it ended with:

> I’m unable to provide additional details about verification outcomes, and Support cannot manually override the result. At this time, Trusted Access for Cyber verification does not support retries or appeals.

I even provided them my credentials, and support AI was basically: lol wat we're here to check technical errors, your credentials are of no relevance.

culi 2 hours ago

you can abliterate any open model like this. This is pretty standard stuff in a TOS. I'd be surprised if you couldn't find the same in OAI or Anthropic's

deadbabe an hour ago

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

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.

wewtyflakes an hour ago

It is cliche, but I haven't had good luck with having Chinese models openly discuss historical topics like Tienanmen Square. The US models don't seem to have a problem discussing history, even if it points an unglamorous light on the US government.

dzonga 2 hours ago

> 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.

Just like that we are witnessing an open burial. It's now in everyone's interest to keep the valuations in the 'A.I' economy as they're though it's apparent they're not justified.

whether it's the cost to develop models, cost of hardware, cost of serving ie inference.

preommr an hour ago

So the vagueposting by googlers about Ox Alpha was just... what exactly?

Like I get that they have to be careful about comms, but surely senior members of the team can clarify when something is NOT them, when everyone is gosspiing it is them.

qeternity 32 minutes ago

Trolling. GLM is heavily distilled from Gemini.

XCSme an hour ago

Nice, finally they fixed the huge reasoning tokens count.

Now it's similar cost to DeepSeek v4 flash, but smarter.

My tests: https://aibenchy.com/compare/z-ai-glm-5-3-flash-max/deepseek...

sunbum 5 hours ago

> with all of this traffic served on Chinese AI chips

RIP Nivida shareholders

ChoosesBarbecue 5 hours ago

God I wish I could’ve shorted NVIDIA right now

browningstreet 5 hours ago

It's earnings day for them...

re-thc 5 hours ago

Which 9/10 times hasn't been great anyway (stock reaction).

Bluestein 4 hours ago

Of course the release was not coincidental - with the earnings days - I am sure.-

vdfs 3 hours ago

And two models released same day + openai chip

kingstnap 4 hours ago

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.

outworlder 3 hours ago

Unless NVidia craters you are likely to lose money given the IV crush that will happen today.

Bluestein 5 hours ago

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

xtracto 21 minutes ago

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).

rvz 5 hours ago

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

ThouYS 4 hours ago

yay, I called it! :) (in the other thread)

dannyw 4 hours ago

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.

ignoramous 4 hours ago

The export controls were revoked before it triggered Chinese protectionism: https://www.silicon.co.uk/e-innovation/artificial-intelligen... / https://archive.vn/B2pah

mlinsey 4 hours ago

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.

re-thc 4 hours ago

> The export controls were revoked before

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

bigbadfeline 4 hours ago

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.

bigbadfeline 3 hours ago

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.

anramon an hour ago

And it doesn't matter, it still pushed China to speed-up their AI related hardware development.

mrngld 4 hours ago

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.

bigyabai 14 minutes ago

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.

redox99 4 hours ago

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)

nchmy 4 hours ago

seems unlikely that they'll get nearly as much demand now that it isnt free

redox99 4 hours ago

Sure, although I still expect it to become the most used model on openrouter.

Implicated 2 hours ago

> it ran like shit. Very slow (~20tps, VERY high latency) and it would timeout all the time.

Boy, do you have a rude awakening in store.

Aurornis 4 hours ago

Ox Alpha is a smaller model and it was running very slowly. Chinese AI accelerators are coming along, but nVidia’s lead is huge.

knowaveragejoe 3 hours ago

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.

cortesoft 2 hours ago

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

VulgarExigency 3 hours ago

It was being served for free. They were almost certainly being overloaded.

Aurornis an hour ago

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

Implicated 2 hours ago

> and it was running very slowly

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

Aurornis an hour ago

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.

WarmWash 4 hours ago

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.

Jcampuzano2 4 hours ago

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.

WarmWash 3 hours ago

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.

pianopatrick 2 hours ago

I can easily see a situation where most non American AI usage is on Chinese models on Chinese chips though.

uhfraid 2 hours ago

What about the current situation, where serious API payers are increasingly OK with using open-weight models running on US providers?

https://www.ft.com/content/32a70a3c-7d28-40b4-808e-36edb58c7...

rapind 2 hours ago

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.

bityard 2 hours ago

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.)

cheema33 38 minutes ago

> 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?

saberience 2 hours ago

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.

revolvingthrow 5 hours ago

> 320B total parameters and just 18B active parameters

This is pretty hefty for a "flash" model, even a 256 GB setup is insufficient at q4 - and q4 is already the worst-but-still-acceptable quant in my experience. The benchmarks look great, especially since GLM tends to be more honest than the average Chinese lab, but you’ll need to splurge to run it at home.

@edit: so many releases that I forgot to math. This fits just fine in q4, realistically the minimal hardware would be 192gb - so blazing fast on double rtx 6000 pro and usable on 256gb unified memory. You could even go with 5bit quant on 256gb.

… you’ll still need to splurge, though.

colingauvin 5 hours ago

That's 160GB-ish for Q4...how is 256 insufficient?

dannyw 4 hours ago

Looks like the M5 Ultra Studio wait times are going to increase again. Already at 10-12 weeks, I wonder how long it'll go?

speedgoose 4 hours ago

I guess like the M3 Ultra, at some point normal customers won’t be able to buy it.

pietz 3 hours ago

With tiny models surpassing huge, 6 months old models on benchmarks, does anybody have some smart words to share on how these still "feel" different?

Artificial Analysis ranks GPT 5.6 Luna similar to GPT 5.4, but that never matches my real world experience. AA seems to do a good job making a single number as representative as possible but there is still so much benchmarks don't communicate.

KptMarchewa 3 hours ago

I agree. They are definitely good - no issues with instruction following for example - but they miss the "intelligence" larger models have.

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.

TaLiTr 5 hours ago

> it outperforms GLM-5.2 across benchmarks and real-world workloads at one-tenth the price, while approaching Claude Opus 4.8 on coding and agentic benchmarks.

From a biased source, but would be big if true. I've had great results with GLM 5.2.

From their subscription page, the smallest plan gives you about 97M tokens weekly for 5.3 but 292M for 5.3 Flash. Not exactly 10x the limit.

re-thc 5 hours ago

> From a biased source, but would be big if true. I've had great results with GLM 5.2.

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

wolttam 4 hours ago

The recent and slightly smaller DSv4 Flash is also GLM 5.2 equivalent (or close enough)

tokai 3 hours ago

DSv4 hallucinates much more than GLM-5.2 though.

lxe 4 hours ago

Is the actual Z.AI ecosystem good enough to replace the main drivers like Codex and Claude? Because it looks like Z Code is just a Codex fork. Just like the Kimi Code one is.

What irks me about this is that the harnesses seem to be just an afterthought here.

Don't get me wrong, I love messing around with installing Pi, getting it hooked up with OpenRouter, and just trying all kinds of different stuff, local models, etc... but when it comes to literally just setting up a productivity environment and trusting my entire machine with it, I just run Codex.

I have heard from anecdotes where people have indeed replaced their main drivers with DeepSek V4 Flash or GLM and state that "it's almost as good as... [claude/gpt]" but I never hear anyone say "yeah, this is the model/harness that I now run on my machine and don't mess with it"

Bluestein 3 hours ago

> "yeah, this is the model/harness that I now run on my machine and don't mess with it"

* me raises hand.-

Havoc 3 hours ago

Their list of allowed tools is extensive so just use whatever you want within that list

Think z code gives a token bonus though

ygouzerh an hour ago

You can use OpenRouter directly in Claude Code as well, it's quite nice!

Sphax an hour ago

Both can be true though. I had the max coding plan since january and I kept using with Pi since then, even though it wasn’t as good as opus until glm 5.3. It definitely can be a daily driver if you don’t want to use Anthropic or OpenAI. It’s going to be even better with native vision now available. And i’m not messing with my setup either.

packetlost 5 hours ago

For those who didn't read, this is the identity of the mysterious "Ox Alpha" model

Bluestein 5 hours ago

They even give this over the API now:

│ 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_...":"}

AbsurdCensor 4 hours ago

Yeah, made me suspicious of how well the Ox Alpha was performing that it wasn't some 'new group' making the model.

cootsnuck 4 hours ago

If we fast forward say 5 years, I don't see how we don't end up in world where people (and enterprises) are more savvy with how they use LLMs. Meaning, more models, smaller models, weirder models, more specialized models, etc. And all of it running on a variety of hardware (edge devices, personal computers, on-demand cloud compute).

I don't see how NVIDIA can keep their spot as belle of the ball. If LLMs and friends are truly to become as useful and ubiquitous as everyone thinks they will, then commoditization is the only option.

drob518 4 hours ago

We need to figure out what the real pricing is for a going concern. Right now, everyone is subsidizing and discounting to grow (or maintain) market share. The big question is whether the steady state, market derived inference pricing is above or below what we’re seeing today. I honestly don’t know. Anthropic had said that inference is profitable, but they’re clearly not yet profitable overall with training and buildouts still happening.

bigyabai 2 hours ago

> I don't see how NVIDIA can keep their spot as belle of the ball.

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.

claudeIsDown 4 hours ago

On OpenRouter the pricing is: Input $0,075/M - Output $0,25/M - Cache Read $0,015 /M

How is the business model of Anthropic/OpenAI will sustain?

dakolli 3 hours ago

They're obviously in a pickle, nobody is going to continue to pay $15-50 a mm tokens here soon. There's a reason OpenAI stopped training large models last week, and it's not because of "saftey" or "alignment" they know these gigantic models are not worth the squeeze.

polski-g an hour ago

This is a bad model. Worse than Luna in every way; slower, dumber.

pphysch 33 minutes ago

OAI/Anthropic shareholder? Speed and intelligence are not "every way". Cost is essential. Hence the Pareto boundary illustrated in TFA.

vatsachak 42 minutes ago

I think anthropic is behind but Luna on a Jalapeno seems profitable

yipinwong 4 hours ago

When reading this type of announcements, always have keen eyes on graphs.

e.g. "Agent Coding Performance by Effort Level" cuts Y-axis from 0~20.

- This makes it as if GLM-5.3-Flash made a bigger jump than it claimed as the Y-axis does not increase much (stupid trick used in biz reports)

I did mention that ox was working ok for me, and having an open-weight comparable to close to SOTA makes it very compelling for me to try it out locally (well, only if I got more VRAM)

nchmy 4 hours ago

they also conspicuously omitted GPT 5.6 Luna from comparison. It scores lower, but is also cheaper. MiMo 2.5 is not a valid comp at this point

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...

mrtesthah 4 hours ago

The web page says 5.3 flash is discounted right now.

drob518 4 hours ago

Seems disingenuous to draw frontier graphs with starter pricing.

seaal 4 hours ago

Well, Luna debuted with 5x higher pricing than is currently available. With the pace of recent development these models might not be relevant by Thanksgiving.

drob518 3 hours ago

Of course. Pricing is always changing, but typically it goes down over time, not up. So, if you're showing artificially low pricing from the start based on a teaser rate, IMO, you shouldn't be using that to show where you appear on a frontier graph. Place yourself on the graph based on your expected long-term pricing. Then, over time, adjust your position based on your standard rate, whatever that might be. Games are always being played for things like this, but this seems excessive.

yipinwong 2 hours ago

I don't know if that's the standard pricing for US models to go down overtime, while Chinese ones go up (start cheap but pay more).

I don't have enough metrics to compare those costs but still Chinese models have been cheaper except against Luna for me.

FWIW, Luna does everything so well, I just keep using it for all my agents by default.

drob518 2 hours ago

I haven't noticed the Chinese models going up in price for the same model. They do release new versions of the models with different prices that are higher. But everybody is doing that. One fine point is that deepseek-v4-flash-0731 is really a different model than deepseek-v4-flash and it's priced higher.

singularity2001 3 hours ago

At the current 50%-off GLM-5.3-Flash price ($0.075/M input, $0.25/M output; cached input $0.015/M), surprisingly, roughly $400–900/month would buy token throughput comparable to fully exhausting Claude Max 20×

syntaxing 2 hours ago

Ironically, our administration pushing for ban of the AI chips to China is forcing them to make smaller and more efficient models which seems like a requirement for running on Chinese chips. I wouldn’t be surprised this model was tailored to run purely on Chinese chips. Same thing with Deepseek MLA, the drastically lower KV cache memory requirement was born out of necessity so it runs on the Huawei chips.

adroitboss an hour ago

This is exactly what Jenson said in all of his interviews. Banning it in the short term would have long term consequences.

yousif_123123 2 hours ago

Will we need all the data centers being built or will improvements in software and hardware allow the majority of AI workloads to run locally or in the cloud but way more efficiently than was projected when all the plans were laid out?

Like were executive at Google and AWS and Microsoft expecting this kind of performance from models smaller than what openai/anthropic have been doing? Are we really in a "compute desert"?

jatins 2 hours ago

I was quite surprised that Zai had deep pockets to serve this free for a week. My first guess was this was an American lab like xai or google

mariopt 5 hours ago

It's only 320B, local frontier AI is getting closer, sooner than expected.

oceansky 4 hours ago

Can't come soon enough!

saberience 2 hours ago

It's not possible to keep shrinking down parameters and keep "frontier" performance, it's like saying it's possible to take a 3 hour movie and compress it down to 3 megabytes, there are information theoretic limits on the amount of bits of information that can be compressed.

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.

hypfer an hour ago

You can fit Shrek 1 into a 13mb gif tho

https://www.deviantart.com/sssfjknfvdknj/art/the-ENTIRE-shre...

twobitshifter 38 minutes ago

The current models are not close to approaching the limit of compression for intelligence. They aren’t even focused on it like Chinese labs are. The training of Qwen’s 27B parameter model showed that by structuring model training from fundamentals to more difficult topics they were able to drastically reduce the number of parameters needed.

The ‘frontier’ models rely on scale to achieve their results but that’s not the only approach. Eventually we will hit up against the fundamental limits but we are not close with Sol and Mythos.

BeetleB 3 hours ago

The key difference between this and all other GLM models is it's multimodal. You cannot send images to the other GLM models.

mrinterweb 3 hours ago

I really wish GLM models had vision capabilities. I've worked around that in the past to use a vision MCP in my harness that GLM can call. It is not the same, but it allows the model to query images.

BeetleB 3 hours ago

Well, now one of them does!

iamsyr 5 hours ago

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

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

Xunjin 5 hours ago

Is that cheaper than DS4 flash?

javier123454321 5 hours ago

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.

denysvitali 5 hours ago

Tbh it was also slow because it was being hammered by everyone making use of the free tokens

javier123454321 4 hours ago

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.

swiftcoder 4 hours ago

It's even cheaper than DS4's off-peak pricing. Seems like DeepSeek have some stiff competition now

arizen 4 hours ago

Few weeks ago, I wouldn't expect this statement to be true. Accelerate!

nateb2022 4 hours ago

Slightly more expensive than the (post-price hike) DS4 flash pricing, but in the ballpark.

https://openrouter.ai/compare/deepseek/deepseek-v4-flash-073...

walrus01 4 hours ago

Comparison should be to 0731

nateb2022 4 hours ago

updated thanks

drob518 4 hours ago

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.

garo-pro 5 hours ago

> Combined with our latest 30T-token multimodal pre-training corpus [...]

Is the optimal formula still 20x the amount of model params in tokens for training? Could this mean we're getting a GLM with 1.5t params?

epolanski 5 hours ago

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.

esperent 5 hours ago

This has been clearly stated as what would happen going back several decades at least.

ricardobeat 5 hours ago

Starting? This was obvious way back in 2019, when the US decided to give China a little push developing their own silicon industry.

himata4113 4 hours ago

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.

nananana9 4 hours ago

That's how you catch up when you're behind.

Now the US is behind in EVs can you guess what they're doing? [1]

[1] https://evwire.com/p/video-ford-ceo-jim-farley-says-they-fly...

himata4113 4 hours ago

"argument is very weak" regardless as I said.

cyanydeez 4 hours ago

yeah, America is totally out there respecting international law.

"problem" indeed.

epolanski 3 hours ago

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.

fwip 3 hours ago

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.

pshirshov 3 hours ago

> I'm starting to think

That's good. Keep going.