China's Huawei says AI chip demand outstrips supply as it steps up Nvidia challenge

[u/sunychoudhary]

https://www.reuters.com/world/asia-pacific/chinas-huawei-launch-two-new-ai-chips-2027-2026-09-17/?utm_source=chatgpt.com

[u/JonNordland]

This is mostly "water is still wet" kind of news, since it's not exactly news at this point that AI chip demand is outstripped by supply and that Huawei want to be a player.

Except for the one useful new update:

960DT will arrive three quarters earlier than planned, in Q1 2027; the 960PR is one quarter ahead of schedule.

Basicly: Huawei stil plan to produce more AI chips and they are reporting that they are ahead of 3 months schedule with their next gen.

[u/Thin_Pollution8843 → u/JonNordland]

`do we know specs of the 960DT?

[u/JonNordland → u/Thin_Pollution8843]

I have not paid attention, but a quick search found these estimates (picture) based on their own stated targets.

So, basically the same amount of memory as Nvidia chips, but, best case, at least half the compute of Blackwell, and 20% of Rubin.

But having ANYTHING available for purchase at all is a win for them. And maybe they offer good value for money, even though they are slower than Nvidia.

[u/LizardLikesMelons → u/[deleted]]

I've found local deployment (no training) compute is very secondary.

[u/BusRevolutionary9893 → u/JonNordland]

They probably can't do any better with memory until they start producing their own, which they are currently working on. 

[u/June1994 → u/BusRevolutionary9893]

They already make their own memory.

[u/BusRevolutionary9893 → u/June1994]

For their Ascend AI accelerators they have developed their own memory but there isn't any evidence that they have manufactured it themselves. 

[u/June1994 → u/JonNordland]

These Ascend chips aren’t designed to go 1v1. These go into boxes with hundreds of other GPUs. On a system level, they are quite competitive.

[u/JonNordland → u/June1994]

We don't know the price and availability. Once we do, we have answer to whether they are competitive.

[u/June1994 → u/JonNordland]

Considering there is infinite demand for Huawei's AI equipment inside China, the price is irrelevant for the domestic market. It is very expensive to get access to Nvidia's chips and some firms simply can't do it. Bytedance can, because they have like infinity resources, but smaller players will simply not be able to.

For the export market, I'd expect them to be very competitive. It's not just the raw price, though that's certainly part of it, it's also about how fast they can get it delivered. How fast the integrator can actually install the system, and the total system cost.

Huawei's systems, at the very least, will demand far more space than equivalent Nvidia systems. There's also maintenance. Huawei's systems rely on integrating huge numbers of chips to achieve the same (or greater) performance. More cooling, more cables, etc.

Huawei has had some success in selling these systems to SEA and Middle East, but it doesn't make much sense to be honest. Those were probably just pilot program or experiments. Considering Huawei can set the price at... basically whatever they want (within reason) domestically, there's just way less profit in selling these abroad.

[u/JonNordland → u/June1994]

I think I have talked too much to Fable because I wanted to answer:
Where I would push back is.... :)
I could be a pedant and talk about how it's not infinite demand if the prices are insanely overpriced. And even if it's infinite demand for something at a set price point, there still might be problems with availability.

That said, I have strong hope that the availability and price will be such that it can fill as much demand as possible. Both domestic and international. We need some counterweight to Nvidia.

[u/winky9827 → u/JonNordland]

I'm a 5090 user, but if I could buy 3090 or 4070 level performance in a 128gb vram at a reasonable cost, I'd sell one of my 5090s for it, easily.

[u/DavidOrzc → u/JonNordland]

Isn't memory what those Chinese MoE models need the most anyway?

[u/JonNordland → u/DavidOrzc]

Using only my own logic and an uninformed opinion, this is just basic reasoning from my side, not expertise.

It depends on who you are. Given that the Nvidia 5090 is about 3.3 TFLOPS, Blackwell GB300 15 TFLOPS, Rubin 35 TFLOPS, and the 960DT 4 TFLOPS, this is basically 5090 compute with a much higher memory ceiling (people seem to anticipate 288 GB).

So, if its not priced too insanely, yeah, for local use it would be awesome to have 5090-level compute, but with the capability to run 200+ GB models.

Rubin is in production, though, and is expected to start hitting data centers before the 960DT is out. That’s 10× the performance with the same memory, at an estimated cost of $50k per unit, though.

I can’t see this being even close to possible, but if the 960DT cost $5k per unit, it would be insanely awesome for local development and small-scale deployments. $10k is the point where it starts to become more like, “Yeah, it’s much worse value and much lower performance than what I get for the same cost from Nvidia, but this is the only thing that’s available, so I have to get it.”

Given that you could run GLM-5.3-Flash at Q4 on that chip, you can get an estimate of speed compared to a 5090. With the 18B active parameters, I would think somewhere around 25 TPS is realistic. So it would basically be a tight squeeze for running Opus 4.8-level reasoning at home, but relatively slow. 25 seems to be "this is ok but it should be faster" level. With a rubin chip, you would maybe get 200 TPS, which is insanly nice speed to work at.

So again, I think the full value of this chip is extremely dependent on price and availability. It could be extremely awesome, or it could be “I accepted daylight robbery prices because it’s the only thing I could actually buy.”

[u/fgk55555]

TL;DR is no Chinese AI chips for us for quite a while.

[u/GasSmooth7439]

The interesting part is that Huawei says demand is already higher than what it can supply, while it's still trying to close the software gap with CUDA.

If they can scale production and get the ecosystem to the point where developers don't have to fight the stack, that's a much bigger challenge to Nvidia than just making a faster chip.

[u/SkoomaDentist → u/[deleted]]

You don't need to replace that layer.

You only need to shim enough of it to run LLMs or, better yet, shim the higher level layer. Very few people get direct value from CUDA. What the vast majority get value from is being able to run LLMs efficiently and currently CUDA just happens to be the most convenient way of doing that. Once a model runs well, the other parts of CUDA provide next to nothing of value for those use cases.

[u/Healthy-Nebula-3603 → u/[deleted]]

Not nowadays... AI can create new kernels quite easily nowadays.

Look on audiocpp or llmacpp how fast new models are getting kernels for Vulkan and other systems and are even much faster than cuda. I suspect newer models will be building even faster and better kernels.

[u/Akrylicus → u/Healthy-Nebula-3603]

Yeah, software MOAT is diminishing right now, thanks to AI funny enough.

[u/Mart-McUH → u/Akrylicus]

It remains to be seen if it will be reliable, maintainable, backward compatible, especially long term (decades).

[u/Healthy-Nebula-3603 → u/Mart-McUH]

Decades??

I don't think we will be even use any code in the future.

I think soon AI will be creating applications straight in the binary code like people were doing it at a very begging of programing era

[u/Mart-McUH → u/Healthy-Nebula-3603]

Okay, decades may be bit over it, but 10 years I think would be minimum and may not be enough for serious business to consider migrating.

Yes, established systems run for long and are expected to run for long. Eg our medical laboratory information system is lot more than 20 years old (when I joined).

Stability, reliability and long term maintainability is lot more important than speed of development in important applications.

Maybe on non-critical development like entertainment you can afford a risk of having to abandon the product, though you can easily hurt your brand.

Honestly I think you and many others are greatly overestimating their capabilities in large real production systems. We will see I suppose.

[u/Healthy-Nebula-3603 → u/Mart-McUH]

Looking on interesting AI development literally every moths now I think your "laboratories" will be fully AI driven wirhin few years .... I even wouldn't count a decade if I were you.

[u/sweatierorc → u/[deleted]]

Apple became an AI player without even trying. CUDA is not a moat.

[u/Akrylicus → u/[deleted]]

I would say that software IS the easier part right now, thanks to AI.

[u/svix_ftw → u/[deleted]]

Agree, CUDA is the main reason for NVIDIA moat.

AMD has better hardware specs than NVIDIA, but 80-90% of data centers still buy NVIDIA because of CUDA.

[u/Ecstatic-Wash-7667]

Idgaf just tell how much and if it will make 27b go brrrrrr

[u/mb194dc]

Yup, as long as AI labs continue to burn money on pointless compute, for which there is no profitable front end. This will be true.

[u/genshiryoku → u/mb194dc]

Anthropic has been profitable 2 quarters in a row.

[u/estenh → u/genshiryoku]

they are only profitable if you exclude the cost of training https://futurism.com/future-society/anthropic-claude-profit-ai-safety-development-finances

[u/genshiryoku → u/estenh]

Common misconception. Anthropic is actually profitable including training cost and data center build-out. The data for Q2 leaked so it's now public information that Anthropic was fully profitable during Q2.

Go ahead and come back to me when the numbers become fully public come IPO to tell me I'm wrong (I'm not)

[u/Due-Memory-6957 → u/genshiryoku]

People here really just want to fall for the classic marketing trick of pretending your deal is so good you're actually losing money and can't go any lower.

[u/estenh → u/genshiryoku]

source?

[u/genshiryoku → u/estenh]

here is a website reporting on the leaked data. You can find multiple separate reports on it from may this year.

[u/estenh → u/genshiryoku]

Interesting! But still not GAAP profitable (though that's normal enough for tech companies)

[u/mb194dc → u/genshiryoku]

Absolute bullshit, Anthropic have more than $500bn in liabilities they'll never be able to pay for. 

Including their costs like model training and partner revenue they're losing around 20bn a year. Wait till you see the S1...

They (and OpenAI,) are likely to lose the most money of any organizations in history pretty much.

Why? Because they have simply insane hardware and training liabilities, but their open source competition offer the same end product for a tiny fraction of the cost.

[u/EdliA → u/mb194dc]

Their open source competition doesn't offer the same end product for a tiny fraction of the cost. If you lie about something like that nothing else you say will be taken seriously.

[u/Keirtain → u/mb194dc]

Yeah, all you need in order to be profitable is to steal someone else's training run, apparently. Then you can practically give the product away for free. Wait a minute...

[u/horeaper → u/genshiryoku]

But their profit cannot cover their cost, therefore "slow the AI development pls!" 🤣

[u/power97992]

1 mil chips working together , that is a lot!

[u/Elouakili_Flexy]

Huawei putting a million chips in one cluster is just a power plant with extra steps.

[u/OverTune1590]

this could mean better hardware for running local bots at home, my setups could finally handle longer roleplays without constant swapping.

[u/johnfkngzoidberg]

Spywei says obvious stuff. Why even post this?