NVIDIA is pretty established but there's also Intel, AMD, Google to contend with. Sure Cerebras is unique in that they make one large chip out of the entire wafer but nothing prevents these other companies from doing the same thing. Currently they are choosing not to because of wafer economics but if they chose to, Cerebras would pretty much lose their advantage. https://www.servethehome.com/cerebras-wse-3-ai-chip-launched... 56x the size of H100 but only 8x the performance improvement isn't something I would brag about. I expected much higher performance since all processing is on one wafer. Something doesn't add up (I'm no system designer). Also, at $3.13 million per node, one could buy 100 H100s at $30k each (not including system, cooling, cluster, etc). Based on price/performance Cerebras loses IMO.
I think the wafer itself isn’t the whole deal. If you watch their videos and read the link you posted the wafer size allows them to stack them in a block with integrated power and cooling at a higher density than blades and attach enormous amounts of memory. Not including the system, cooling, cluster, etc seems like a relatively unfair comparison too given the node includes all of those things - which are very expensive when considering enterprise grade data center hardware.
I don’t think their value add is simple “single wafer” with all other variables the same. In fact I think the block and system that gets the most out of that form factor is the secret sauce and not as easily replicated - especially since the innovations are almost certainly protected by an enormous moat of patents and guarded by a legion of lawyers.
Can their system attach memory? from what I read, it doesn't seem to be able to: https://www.reddit.com/r/mlscaling/comments/1csquky/with_waf...
Surprising. DRAM (and more importantly high-bandwidth DRAM) seems to be scaling significantly better than SRAM -- and I'm not sure if that could be seriously expected to shift.
I think they do have external memory that they use for training.
At the end of the day, Cerebras has not submitted any MLPerf results (of which I am aware). That means they are hiding something. Something not very competitive.
So, performance is iffy. Density for density sake doesn’t matter since clusters are power limited.
Correction: it's 8x the TFLOPS of a DGX (8 H100), not 1 H100. But it's true that if it stays at $3M it's probably too much and I don't think the memory bottleneck on gpus is large enough to justify this price/performance.
The company started in 2015 I think they are (were?) banking on SRAM scaling better than it has in recent years.
> wafer economics
What are they?
Is this related to defects? Can't they disable parts of defective chip just like other CPUs do? Sounds cheaper than cutting up and packaging chips individually!
Agreed, it just seems like Nvidia chips are going to be easier to produce at scale. Cerberas will be limited to a few niche use-cases, like HFT where hedge funds are using LLMs to analyze SEC filings as fast as possible.
they don’t need an advantage, they just need orders and inventory
get extorted by nvidia sales people for a 2026 delivery date that gets pushed out if you say anything about it or decline cloud services
or another provider delivering earlier
thats what the market wants, and even then, who cares? this company is trying to IPO at whay valuation? this article didnt say but the last valuation was like $1.5bn? so you mean a 300x of delta between this and Nvidia’s valuation if these guys get a handful of orders? ok
On the one hand, the financials are terrible for an IPO in this market.
On the other, Nvidia is worth 3trn so they can sell a pretty good dream of what success looks like to investors.
Personally I would expect them to get a valuation well about the 4bln from the 2021 round, despite the financials not coming close to justifying it.
Cerebras is well-known in the AI chip market. They make chips that are an entire wafer.
Cerebrus made a great (now deleted) video on the whole computer hosting the wafer: https://web.archive.org/web/20230812020202/https://www.youtu...
It’s fascinating.
TIL - web archive saves youtube videos
Wow 200k amps in a chip. Whole thing looks like an early computer from 50s.
I'd bet that making a chip the size of the waver has the benefit on not losing any silicon to dicing the wafer up like a desktop or GPU chips coming from a wafer. Major downside is you need to either have a massive x and Y exposure size or break the wafer into smaller exposures which means your still needing to focus on alignment between the steps, and if a defect can't be corrected then is that wafer just scrap?
They fuse off sections of the wafer with defects just like other manufacturers do in monolithic CPUs (as opposed to chiplets like AMD).
Interesting that they’ve scaled on-chip memory sublinearly with the growth of transistors between their generations, I would’ve thought they would try to bump that number up. Maybe it’s not a major bottleneck for their training runs?
SRAM is scaling significantly more slowly than logic in recent process nodes.
Ahh that explains it, thanks. Seems like a potentially large problem given their strategy.
Making larger monolithic silicon doesn't get 2x as expensive to get 2x as large. Bigger silicon is massively more expensive. I'm not sure that making each piece require a large chunk of perfect wafer is a fantastic idea, especially when you're looking to unseat juggernauts who have a great deal of experience making high quality product already.
It is designed to handle defects.
https://www.servethehome.com/cerebras-wafer-scale-engine-ai-....
How does one cool that!? Heck power it...
Yep! Them, SambaNova, and Groq are super exciting mid-late stage startups imo.
Shhhhh, stop telling the normies about the future!
And especially don't tell them to start looking into who "sovereign clouds" actually are!
I’m going to go ahead and predict this flubs long term. Not only is what they are doing very challenging, I’ve had some random brokerage house reach out to me multiple times about investing in this IPO. When your IPO process resorts to cold calling I don’t think it’s a good sign. Granted I have some associations with AI startups I don’t think that had anything to do with the outreach from the firm.
Agreed, it seems like NVIDIA would be happy to make whole-wafer chips if it seemed like a good play.
My guess is there are a lot of bespoke limitations that the software has to work around to run on a "whole wafer" chip, and even companies that have 99% similar designs to Nvidia already are struggling to deal with software incompatibilities, even with such a tiny difference.
Does cerebras make gaming GPUs, or is it enterprise-only?
Very solidly enterprise-only. They make single chips that take an entire wafer, use something like 10 kilowatts, and have liquid cooling channels that go through the chip. Systems are >$1M.
The chip is huge. It wouldn't fit in any conceivable PC form card.
They sound more like NPUs or TPUs than GPUs. Though that doesn't answer the question about the market they are targeting.
They have zero moat
This is the first I've heard of Cerebras Systems.
From the article
>Cerebras had a net loss of $66.6 million in the first six months of 2024 on $136.4 million in sales, according to the filing.
That doesn't sound very good.
What makes them think they can compete with Nvidia, and why IPO right now?
Are they trying to get government money to make chip fabs like Intel or something?
You seemed surprised that this company is having an IPO to actually raise funds for operations and expansion, vs as just an "exit" where VCs and other insiders can dump their shares onto the broader public.
I might be a bit suspicious if a company in some low-capital-intensive industry was IPOing while unprofitable, but this is chip making. Even if they're not making their own fabs this is still an industry with high capital requirements.
We should be thrilled at a company actually using an IPO for its original intended purpose as opposed to some financialization scheme.
they don't make chips. they design and contract TSMC to fab the chips. The high capital is in design tools and engineers.
Thanks - I said that in my comment, but then just realized I had a typo of "fans" where it should have said "Even if they're not making their own fabs..."
Does this mean that they couldn't find VCs to raise more cash?
> Taiwan Semiconductor Manufacturing Company makes the Cerebras chips. Cerebrus warned investors that any possible supply chain disruptions may hurt the company.
They get their chips from the same company that Nvidia does.
Virtually any competitors to Nvidia would be in the same position.
It's not necessarily to TSMC's advantage for Nvidia to become a monopolist either, although they wouldn't be totally dependent on Nvidia even if they did because TSMC serves every chip market.
They both contract TSMC to fabricate their chips.
The actual design and R&D is still done by Nvidia, Cerebras, AMD, Groq, etc.
Think of TSMC like Kinko's - they do printing and fabrication which is very low margins.
The main PMF for Cerebras is in simulations, drug discovery, and ofc ML.
As I've mentioned before on HN, Public-Private Drug Discovery and NatLab research has been a major driver for HPC over the past 20 years.
TSMC has a market cap of 0.9T USD. It would be the 7 largest US company by market cap if it were one. Manufacturing chips is extremely profitable, at least in the current climate. It used to be that software is more profitable than hardware, which is more commoditized, but AI gave hardware companies a renaissance of sorts.
It's not a simple process at all but requires a lot of engineering and engineers to do it.
https://companiesmarketcap.com/usa/largest-companies-in-the-... https://companiesmarketcap.com/tsmc/marketcap/
> Manufacturing chips is extremely profitable
It only became profitable NOW in the last 2-3 years.
Before that, foundry after foundry was shutting down or merging.
TSMC, UMC, Samsung, Intel Foundry Services, and GloFlo are the last men standing after the severe contraction in the foundry model in the 2000s-2010s due to it's extremely high upfront costs and lack of moat to prevent commodification.
TSMC margins are over 30% and growing [1] - that's very far from "low".
[1] https://www.macrotrends.net/stocks/charts/TSM/taiwan-semicon...
30% net due to a near monopoly and a recent upswing due to Nvidia.
Almost every other foundry system died because of low net margins.
Software (and fabless hardware like chip design) is expected to have 60-70% gross margins or the ability to reach that.
Semiconductors is part of TMT just like Software or Telecom, and this has an impact on available liquidity.
This is why TSMC is heavily subsidized by the Taiwanese government.
TSMC is neither software nor fabless. I'm not sure we are talking about the same company, there seems to be some disconnect here. For hardware business 30% margins are high, Apple is one of the most famous exceptions.
> For hardware business
When a foundry wishes to raise capital from the private or public markets, it's bucketed under TMT - which includes software and fabless hardware as well.
This means it's almost impossible to raise capital without a near monopoly and/or government support and intervention - which is what Taiwan did for TSMC and UMC - because the upfront costs are too high and the margins are much lower compared to other subsegments in the same sector.
This is why industrial subsidizes like the CHIPS act are enacted - to minimize the upfront cost of some very CapEx heavy projects (which almost everything Foundry related is).
> Think of TSMC like Kinko’s
What an amazingly reductive analogy :)
Kinko's is not the pinnacle of human engineering - TSMC is. A slight difference there.
Nvidia's moat is real but not big enough that one can't surpass it with a lot of engineering. It's not the only company making AI accelerators, and this has been the case for many years already. The first TPU was introduced in 2015. Nvidia has just managed to get a leader position in the race.
Saying it's "just" a lot of engineering effort to catch up isn't wrong, but it understates the reality. There are very few organizations on earth that have the technical and financial resources to meaningfully compete with even small parts of Nvidia's portfolio. Nvidia's products benefit from that breadth of strengths and the volumes they ship.
They don't just make accelerators, they'll sell you the hardware too (unlike TPUs). They don't just sell you the hardware, the software ecosystem will work too (unlike AMD or Intel). That hardware won't just do a lot of computations, it'll also have a lot of off-chip memory bandwidth (vs Cerebras or others). Need to embed those capabilities in a device that can't fit a wafer cabinet or a server rack's worth of compute, Nvidia will sell you similar hardware that uses a similar stack, certified for your industry (e.g. automotive). Take any of that away and you're left with a significantly weaker offering.
Also they benefit from the priority of paying fabs a lot of money and placing a lot of orders.
If anything, Nvidia is less dominant than they should be because they've managed to ensure absolutely no one wants to buy from them when there are viable alternatives.
People said the same about Cisco, Intel, IBM etc. It will only be a matter of time for companies to eat into the high margin stuff for specific use-cases and grow from there.
There's something weird about the market right now in that all the AI budgets being used to by GPUs are loss-leading. Orgs are treating the spend as a waste anyways, so I suspect they aren't going to be looking to cut costs. Make Cerebras a hard sell imo.
Compare it to the same period last year ($8.7M in sales). That’s a pretty solid growth rate.
Their tech is very impressive, look it up.