Alibaba's New AI Chip: Key Specifications Comparable to H20
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Alibaba has unveiled a new AI chip comparable to Nvidia's H20, sparking discussion on China's tech capabilities and the implications for the global AI chip market.
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https://www.ft.com/content/12adf92d-3e34-428a-8d61-c91695119...
How big a deal is it to be on the cutting edge with this? Given that models seem to be flattening out because they can't get any more data, the answer is "not as much as you would think".
Consequently, a generation or 2 behind is annoying, but not fatal. In addition, if you pump the memory up, you can paper over a lot of performance loss. Look at how many people bought amped up Macs because the unified memory was large even though the processing units were underpowered relative to NVIDIA or AMD.
The biggest problem is software. And China has a lot of people to throw at software. The entire RISC-V ecosystem basically only exists because Chinese grad students have been porting everything in the universe over to it.
So, the signal is to everybody around this that the Chinese government is going to pump money at this. And that's a big deal.
People always seem to forget that Moore's Law is a self-fulfilling prophecy, but doesn't just happen out of thin air. It happens because a lot of companies pump a lot of money at the engineering because falling off the semiconductor hamster wheel is death. The US started the domestic hamster wheel with things like VHSIC. TSMC was a direct result of the government pumping money at it. China can absolutely kickstart this for themselves if the money goes where it should.
I'm really torn about this. On the one hand, I hate what China does on many, many political fronts. On the other hand, tech monopolies are pillaging us all and, with no anti-trust action anywhere in the West, the only way to thwart them seems to be by China coming along and ripping them apart.
Microchip Inc partnered w US Govt on the aerospace angle and funded Canonical for linux ports. Their Polarfires and now Euro aerospace like Gaisler are heading in the same direction. US Govt/DARPA and others have been funding risc-v ports for years, to include mainly automated porting.
There are big differences between lowend profile-challenged SBCs and the work of NVDA, Microchip Inc, and the US Govt in the much more highend GPU related, and safety critical industries.
With Heavyweights like IBM/Redhat now on risc-v joining canonical and others, the SW side is definitely improving
TSMC btw, has always been about labor arbitrage
It’s also an interesting signal to the rest of the world that they’re going to be an option. American tech companies should be looking at what BYD is doing to Tesla, but they’re also dealing with a change in government to be more like Chinese levels of control but with less maturity.
"Speaker Johnson says China is straining U.S. relations with Nvidia chip ban" - https://www.cnbc.com/2025/09/17/china-us-nvidia-chip-ban.htm...
Translation: "We are angry with China that they wont let the US undermine itself, and sell its strategic advantages to them..."
Oh, the irony.
alicloud has many cluster outside china, so they probably can because many friendly country with china has it
but it would be the same with US power play, they only permit anyone that they accept
No amount of trade war politics will make up for a lack in infrastructure investment.
There won’t be 16A manufacturing here in the USA.
Probably ever.
We live in extremely dangerous uncertain times.
Any forecast that long is worthless.
https://wccftech.com/tsmc-cutting-edge-sow-x-packaging-set-f...
This is step in good direction for everyone except nvidia and its chinese distribution network
It was also frustratingly predictable from the moment the US started trying to limit the sales of the chips. America has slowed the speed of Chinese AI development by a tiny number of years, if that, in return for losing total domination of the GPU market.
That’s not to say I’m brave enough to short NVDA.
At least for me, Google has some real cachet and deserves kudos for not losing money selling Gemini services, at least I think it is plausible that they are already profitable, or soon will be. In the US, I get the impression that everyone else is burning money to get market share, but if I am wrong I would enjoy seeing evidence to the contrary. I suspect that Microsoft might be doing OK because of selling access to their infrastructure (just like Google).
A major reason Deepseek was so successful margins wise was because the team heavily understood Nvidia, CUDA, and Linux internals.
If you have an understanding of the intricacies of your custom ASIC's architecture, it's easier for you to solve perf issues, parallelize, and debug problems.
And then you can make up the cost by selling inference as a service.
> Amazon and I think Microsoft are also working on their own NVIDIA replacement chips
Not just them. I know of at least 4-5 other similar initiatives (some public like OpenAI's, another which is being contracted by a large nation, and a couple others which haven't been announced yet so I can't divulge).
Contract ASIC and GPU design is booming, and Broadcom, Marvell, HPE, Nvidia, and others are cashing in on it.
A long time ago I worked as a contractor at Google, and that experience taught me that they don’t like things that don’t scale or are inefficient.
My opinion, the problems for NVIDIA will start when China ramp up internal chip manufacturing performance enough to be in same order of magnitude as TMSC.
Wont it be enough to just solder on a large amount of high bandwidth memory and produce these cards relatively cheaply?
Perf is important, but ime American MLEs are less likely to investigate GPU and OS internals to get maximum perf, and just throw money at the problem.
> solder on a large amount of high bandwidth memory and produce these cards relatively cheaply
HBM is somewhat limited in China as well. CXMT is around 3-4 years behind other HBM vendors.
That said, you don't need the latest and most performant GPUs if you can tune older GPUs and parallelize training at a large scale.
-----------
IMO, Model training is an embarrassingly parallel problem, and a large enough cluster leveraging 1-2 generation older architectures that is heavily tuned should be able to provide similar performance to train models.
This is why I bemoan America's failures at OS internals and systems education. You have entire generations of "ML Engineers" and researchers in the US who don't know their way around CUDA or Infiniband optimization or the ins-and-outs of the Linux kernel.
They're just boffins who like math and using wrappers.
That said, I'd be cautious to trust a press release or secondhand report from CCTV, especially after the Kirin 9000 saga and SMIC.
But arguably, it doesn't matter - even if Alibaba's system isn't comparably performant to an H20, if it can be manufactured at scale without eating Nvidia's margins, it's good enough.
Cerebras get their chipped fabbed by them. I assume Eucyld will have their chips fabbed by them.
If there's orders, why would they prefer NVIDIA? Customer diversity is good, is it not?
Money talks. Apple asked for first dips a while earlier (exclusively).
AMD are, Cerebras are, I assume OpenChip's and Euclyd's machines will be.
Sure, but in my example Apple got access exclusively for a few months to a newer node, which would make a world of difference if you compete in the same space.
I am a long time fan of Dave Sacks and the All In podcast ‘besties’ but now that he is ‘AI czar’ for our government it is interesting what he does not talk about. For example on a recent podcast he was pumping up AI as a long term solution to US economic woes, but a week before that podcast, a well known study was released that showed that 95% of new LLM/AI corporate projects were fails. Another thing that he swept under the rug was the recent Stanford study that 80% of US startups are saving money using less expensive Chinese (and Mistral, and Google Gemma??) models. When the Stanford study was released, I watched All In material for a few weeks, expecting David Sack’s take on the study. Not a word from him.
Apologies for this off-topic rant but I am really concerned how my country is spending resources on AI infrastructure. I think this is a massive bubble, but I am not sure how catastrophic the bubble will be.
The US is burning good will at an alarming rate, how long will countries keep paying a premium to be spied on by the US instead of China?
This country used to have congressional hearings on all kinds of matters from baseball to the Mafia. Tech collusion and insider knowledge is not getting investigated. The All-in podcast requires serious investigation, with question #1 being “how the fuck did you guys manage to influence the White House?”.
Other notes:
- Many of them are technically illiterate
- They will speak in business talk , you won’t find a hint of intimate technical knowledge
- The more you watch it, the more you realize that money absolutely buys a seat at the table:
https://bloximages.chicago2.vip.townnews.com/goskagit.com/co...
(^ Saved myself another thousand words)
I mean. I think some of us knew this. There's a lot of issues with AI, some psychological, some are risk adverse individuals who would love to save hours, weeks, months, maybe years of time with AI, but if AI screws up, its bad, really bad, legal hell bad, unless you have a model with a 100% success rate for the task, it wont be used in certain fields.
I think in the more creative fields its very useful, since hallucinations are okay, its when you try to get realistic / look reasonably realistic (in the case of cartoons) that it gets iffy. Even so though, who wants to pay the true cost of AI? There's a big uphill cost involved.
It reminds me a lot of crypto mining, mostly because you need an insane amount to invest into before you become profitable.
Anyone who's listened to him (even those who align with him politically) for an extended period of time can't help but to notice so obviously so self interested to the point of total hypocrisy—the examples of which are too many to begin to even wanting to enumerate. Like—take the Trump/Epstein stuff, or the Elon/Trump fallout—topics he would absolutely lose his sh*t over if these were characters on the left. I find it hard to believe anyone actually ever took him seriously. Branding myself as a fan of his would just be a completely self-humiliating insult to my intelligence and my conscience IMO.
Their multiples don't seem sustainable so they are likely to fall at some point but when is tricky.
They've been trying really hard to pivot and find new growth areas. They've taken their "inflated" stock price as capital to invest in many other companies. If at least some of these bets pay off it's not so bad.
I'm open to considering the argument that banning exports of a thing creates a market incentive for the people impacted by the ban to build aa better and cheaper thing themselves, but I don't think it's as black and white as you say.
If the only ingredient needed to support massive innovation and cost cutting is banning exports, wouldn't we have tons of examples of that happening already - like in Russia or Korea or Cuba? Additionally, even if the sale of NVIDIA H100s weren't banned in China, doesn't China already have a massive incentive to throw resources behind creating competitive chips?
I actually don't really like export bans, generally, and certainly not long-term ones. But I think you (and many other people in the public) are overstating the direct connection between banning exports of a thing and the affected country generating a competing or better product quickly.
Apparently that was an issue for them when it came to hiring people to work at their US fabs as well.
South Korea might have the capability to play this game (North Korea certainly doesn't), but it hasn't really had the incentive to.
Which brings us to the real issue: an export ban on an important product creates an extremely strong incentive, that didn't exist before. Throwing significant national resources at a problem to speculatively improve a country's competitiveness is a very different calculation than doing so when there's very little alternative.
That's just one of the ingredients that could help with chance of it happening, far from being "the only ingredient".
The other (imo even more crucial) ingredients are the actual engineering/research+economical+industrial production capabilities. And it just so happens that none of the countries you listed (Russia, DPRK, and Cuba) have that. That's not a dig at you, it is just really rare in general for a country to have all of those things available in place, and especially for an authoritarian country. Ironically, it feels like being an authoritarian country makes it more difficult to have all those pieces together, but if such a country already has those pieces, then being authoritarian imo only helps (as you can just employ the "shove it down everyone's throat until it reaches critical mass, improves, and succeeds" strategy).
However, it is important to remember that even with all those ingredients available on hand, all it means is that you have a non-zero chance at succeeding, not a guarantee of that happening.
Lost months are lost exponentially and it becomes impossible to catch up. If this policy worked at all, let alone if it worked as you describe, this was a masterstroke of foreign policy.
This isn't merely my opinion, experts in this field feel superintelligence is at least possible, if not plausible. This is a massively successful policy is true, and, if it's not, little is lost. You've made a very strong case for it.
doing a lot of heavy lifting in your conjecture
I don't see myself there, but, given that even the faint possibility of superintelligence would be an instant national security priority #1, grinding China into the dust on that permanently seems like a high reward, low risk endeavor. I'm not recruitable via any levers myself into a competitive ethnostate so I'm an American and believe in American primacy.
2. CUDA has been a huge moat, but the incentives are incredibly strong for everybody except Nvidia to change that. The fact that it was an insurmountable moat five years ago in a $5B market does not mean it’s equally powerful in a $300B market.
3. AMD’s culture and core competencies are really not aligned to playing disruptor here. Nvidia is generally more agile and more experimental. It would have taken a serious pivot years ago for AMD to be the right company to compete.
It's the CUDA software ecosystem they have not been able to overcome. AMD has had multiple ecosystem stalls but it does appear that ROCm is finally taking off which is open source and multi-vendor.
AMD is unifying their GPU architectures (like nVidia) for the next gen to be able to subsidize development by gaming, etc., card sales (like nVidia).
Does Nvidia have patents on CUDA? They're probably invalid in China which explains why China can do this and AMD can't.
https://rocm.docs.amd.com/projects/HIPIFY/en/latest/index.ht...
The CUDA moat is extremely exaggerated for deep learning, especially for inference. It’s simply not hard to do matrix multiplication and a few activation functions here and there.
What is this racialized nonsense, have you seen Jensen Huang speak Mandarin? His mandarin is actually awful for someone who left Taiwan at 8.
So for data centers, training is just as important as inference.
Sure, and I’m not saying buying Nvidia is a bad bet. It’s the most flexible and mature hardware out there, and the huge installed base also means you know future innovations will align with this hardware. But it’s not primarily a CUDA thing or even a software thing. The Nvidia moat is much broader than just CUDA.
See, Mojo, a new language to compile to other chips. https://www.modular.com/mojo
Sure, you can keep buying nvidia, but that wasn't what was discussed.
Lol this is how I know no one that pushes mojo on hn has actually ever used mojo.
You're completely wrong here. That's the "what's wrong with it".
To say Mojo doesn't use Python, when clearly that is a huge aim of the project, makes me think you are splitting hairs somewhere on some specific subject that is not clear by your one liners.
Key aspects of Mojo in relation to Python:
• Pythonic Syntax and Ecosystem Integration: Mojo adopts Python's syntax, making it familiar to Python developers. It also fully integrates with the existing Python ecosystem, allowing access to popular AI and machine learning libraries.
• Performance Focus: Unlike interpreted Python, Mojo is a compiled language designed for high-performance execution on various hardware, including CPUs, GPUs, and other AI ASICs. It leverages MLIR (Multi-Level Intermediate Representation) for this purpose.
• Systems Programming Features: Mojo adds features common in systems languages, such as static typing, advanced memory safety (including a Rust-style ownership model), and the ability to write low-level code for hardware.
• Compatibility and Interoperability: While Mojo aims for high performance, it maintains compatibility with Python. You can call Python functions from Mojo code, although it requires a specific mechanism (e.g., within try-except blocks) due to differences in compilation and execution.
• Development Status: Mojo is a relatively new language and is still under active development. While it offers powerful features, it is not yet considered production-ready for all use cases and is continually evolving.
What if I told you I used to work at modular? What would you say then to this accusation that I'm "missing the nuance"?
The rest of this is AI crap.
Do you really think Mojo is not based on Python? Or they are not trying to bypass Cuda? what is the problem?
The rest might be marketing slop. But I'm not catching what your objection is.
It's all about investment. If you are a random company you don't want to sink millions in figuring out how to use AMD so you apply the tried an true "no one gets fired for buying Nvidia".
If you are an authoritarian state with some level of control over domestic companies, that calculus does not exist. You can just ban Nvidia chips and force to learn how to use the new thing. By using the new thing an ecosystem gets built around it.
It's the beauty of centralized controlled in the face of free markets and I don't doubt that it will pay-off for them.
Also AMD really didn't invest enough in making their software experience as nice as NVIDIA.
Or would china be different because it's a mix of market and centralized rule?
Until 2022 or so AMD was not really investing into their software stack. Once they did, they caught up with Nvidia.
If AMD really wanted to play in the same league as NVidia, they should have built their own cloud service and offered a full stack experience akin to Google with their TPUs, then they would be justified in ignoring the consumer market, but alas, most people run their software on their local hardware first.
HN has a blindspot where AMDs absence in the prosumer/SME space is interpreted as failing horribly. Yet AMDs instinct cards are selling very well at the top end of the market.
If you were trying to disrupt a dominant player, would you try selling a million gadgets to a million people, or a million gadgets to 3-10 large organizations?
They have never had a focus on top notch software development.
A reimplantation would run into copyright issues.
No such problem in China.
And NVIDIA will lose its dominance for the simple reason that the Chinese companies can serve the growing number of countries under US sanctions. I even suspect it won't be long before the US will try to sanction any allies that buy Chinese AI chips!
They are vendor locking industries, i don't think they'll loose their dominance, however, vendor locked companies will loose their competitiveness
Simple example being TikTok.
Its just a matter of time really.
Most of Meta's engagement comes from video content. Continuous engagement is how it is able to generate its revenue.
Thats all I need to say!
Yet, we see Ford as extremely innovative and revolutionary. I think we can draw lots of parallels between a 19th and early 20th century industrializing US and current China.
Russia has none of that at the scale needed.
China, admittedly full of smart and hard working people, then just wakes up one day an in a few years covers the entire gap, to within some small error?
How is this consistent? Either:
- The Chinese GPUs are not that good after all
- Nvidia doesn't have any magical secret sauce, and China could easily catch up
- Nvidia IP is real but Chinese people are so smart they can overcome decades of R&D advantage in just s few years
- It's all stolen IP
To be clear, my default guess isn't that it is stolen IP, rather I can't make sense of it. NVDA is valued near infinity, then China just turns around and produces their flagship product without too much sweat..?
No, that's not really why. It is because nobody else has their _ecosystem_; they have a lot of soft lock-in.
This isn’t just an nvidia thing. Why was Intel so dominant for decades? Largely not due to secret magic technology, but due to _ecosystem_. A PPC601 was substantially faster than a pentium, but of little use to you if your whole ecosystem was x86, say. Now nvidia’s ecosystem advantage isn’t as strong as Intel’s was, but it’s not nothing, either.
(Eventually, even Intel itself was unable to deal with this; Itanium failed miserably, largely due not to external competition but due to competition with the x86, though it did have other issues.)
It’s also notable that nvidia’s adventures in markets where someone _else_ has the ecosystem advantage have been less successful. In particular, see their attempts to break into mobile chip land; realistically, it was easier for most OEMs just to use Qualcomm.
I wouldn't exactly say it was a failure, all those chips ended up being used in the Nintendo Switch
There are almost 5 billion smartphone users; sales of 300 million a year would imply that those are only replaced every 16 years, which is obviously absurd.
On a separate note, speaking of the average lifespan of a phone, I'm fairly sure that with how expensive they're becoming, smartphone lifespans are increasing. Especially with:
* hardware performance largely plateauing (not in the absolute sense, that of "this phone can do most of what I need")
* the EU pushing for easy battery and screen replacement and also for 7 years of OS updates
* the vast majority of phones having cases to protect against physical damage
I'm always a little surprised that Nvidia is _so_ highly valued, because it seems inevitable to me that there is a tipping point where big companies will either make their own chips (see Google) or take the hit and build their own giant clusters of AMD or Huawei or whoever chips, and that knowledge will leak out, and ultimately there will be alternatives.
Nvidia to me feels a bit like dot-com era Sun. For a while, if you wanted to do internet stuff, you pretty much _had_ to buy Sun servers; the whole ecosystem was kinda built around Sun. Sun's hardware was expensive, but you could just order a bunch of it, shove it in racks, and it worked and came with good tooling. Admins knew how to run large installations of Sun machines. You could in theory use cheaper x86 machines running Linux or BSD, but no-one really knew how to do that at scale. And then, as the internet companies got big, they started doing their own thing (usually Linux-based), building up administration tooling and expertise, and by the early noughties Linux/Apache was the default and Sun was increasingly irrelevant.
The H200 is the next generation of the H100.
However they've also got a fair amount of generality, anything you might want to do that involves huge amounts of matmuls and vector maths you can probably map to a GPU and do a half decent job of it. This is good for things like model research and exploration of training methods.
Once this is all developed you can cherry pick a few specific things to be good at and build your own GPU concentrating on making those specific things work well (such as inference and training on Transformer architectures) and catch up to Nvidia on those aspects even if you cannot beat or match a GPU on every possible task, however you don't care as you only want to do some specific things well.
This is still hard and model architectures and training approaches are continuously evolving. Simplify things too much and target some ultra specific things and you end up with some pretty useless hardware that won't allow you to develop next year's models, nor run this year's particularly well. You can just develop and run last year's models. So you need to hit a sweet spot between enough flexibility to keep up with developments but don't add so much you have to totally replicate what Nvidia have done.
Ultimately the 'secret sauce' is just years of development producing a very capable architecture that offers huge flexibility across differing workloads. You can short-cut that development by reducing flexibility or not caring your architecture is rubbish at certain things (hence no magical secret sauce). This is still hard and your first gen could suck quite a lot (hence not that good after all) but when you've got a strong desire for an alternative hardware source you can probably put up with a lot of short-term pain for the long-term pay off.
Are they as good as Nvidia? No. News reporters have a tendency to hype things up beyond reality. No surprises there.
Are they useless garbage? No.
Can the quality issues be overcome with time and R&D? Yes.
Is being "worse" a necessary interim step to become "good"? Yes.
Are they motivated to become "good"? Yes.
Do they have a market that is willing to wait for them to become "good"? Also yes. It used to be no, but the US created this market for them.
Also, comparing Chinese AI chips to Nvidia is a bit like comparing AWS with Azure. Overcoming compatibility problems is not trivial, you can't just lift and shift your workload to another public cloud, you are best off redesigning your entire infra for the capabilities of the target cloud.
They also weren't starting from scratch, they already had a domestic semiconductor ecosystem, but it was fragmented and not motivated. The US sanctions united them and gave them motivation.
Also "good" is a matter of perspective. For logic and AI chips they are not Nvidia level, yet. But they've achieved far more than what western commentators gave them credit for 4-5 years ago. And they're just getting started. Even after 6 years, what you're seeing is just the initial results of all that investment. From their perspective, not having Nvidia chips and ASML equipment and TSMC manufacturing is still painful. They're just not paralyzed, and use all that pain to keep developing.
With power chips they're competitive, maybe even ahead. They're very strong at GaN chip design and manufacturing.
Western observers keep getting surprised by China's results because they buy into stereotypes and simple stories too much ("China can't innovate and can only steal", "authoritarianism kills innovation","China is collapsing anyway", "everything is fake, they rely on smuggled chips lol" are just few popular tropes) instead of watching what China is actually doing. Anybody even casually paying attention to news and rumors from China instead of self-congratulating western reports about China could have seen this day coming. This attitude and the phenomenon of keep getting surprised is not limited to semiconductors.
China shouldn't be buying H20s. Those are gimped 3 year old GPUs. If Nvidia is allowed to sell the latest and greatest in China, I think their revenue would jump massively.
I believe about 1000 S&P points down - to just above the trade war lows from April.
https://news.ycombinator.com/item?id=45275070
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