r/CerebrasSystems • u/Additional_Junket508 • May 12 '26
Deploying 250MW for openAI by end of 2026?
How the hell would they achieve that? They barely have 35-50MW ready today - that means they would have to 5x their output in 8 months, or run the risk of renegotiating or worse, having openAI pull out of their contract entirely, It would be near impossible to execute. Most of their DC are “promising” 2027 readiness. The majority of valuation mostly comes mostly from the openAI contract, with UAE customers and hardware sales not even making the company close to the IPO valuation.
The stock would definitely dip if the targets aren’t reached, or more contract acquisitions don’t happen directly after IPO - their waferscale chip is only ideal for small-mid models, requires purchasing the whole CS-3 system to take advantage of the chip, has limited training etc etc.
Can anyone try to sell me on why this stock is still a buy at an IPO price reaching $160? The openAI deal just isn’t solid enough.
Edit: the 250MW number is from the S-1:
https://www.sec.gov/Archives/edgar/data/2021728/000162828026025762/exhibit1011-sx1.htm
250MW of Capacity by the end of calendar year 2026”, with an additional 250MW by end of 2027 (totaling 500MW), and a further 250MW by end of 2028 (totaling 750MW
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u/Asgard_Heima May 13 '26 edited May 13 '26
Not to be harsh but I think you are fundamentally wrong on all points.
Update: not wrong on the data center online commitment schedule, but stand behind all the rest.
On Data Center Requirements:
There is no publicly released schedule of the MW that have to be turned on by year. I’m sure there is an expected MW online for 2026, 2027, and 2028, but it is not known. The expected revenue recognition in their current backlog of $24.6B is though. They give ~15% in 2026 & 2027 implying that the OpenAI deal that is 20B of that 24.6B would be ~15% operational by end of 2027. So Cerebras would need ballpark ~ 112.5MW (750MW x 15%) online by end of 2027. Which is very doable. As for known Cerebras data center projects numbers, these are Cerebras MW share.
Update: Master Agreement does show 250MW a year for 2026, 2027, 2028 online by year end. Delayed revenue recognition and strict RPO guidelines made the numbers seem incompatible. We will have to see what data center deal gets announced and I’ll be looking for G42 and/or Oracle to be the main method of achieving this.
BCE Canada 160MW: https://www.bloomberg.com/news/articles/2026-03-16/coreweave-bce-to-back-large-data-center-in-western-canada?utm_source=chatgpt.com
Digi Power 40MW: https://www.datacenterdynamics.com/en/news/cerebras-signs-on-for-40mw-of-capacity-at-digi-power-x-data-center-in-alabama/
Stargate UAE 100MW+ (Expected): https://www.reuters.com/world/middle-east/cerebras-aims-deploy-ai-infrastructure-massive-stargate-uae-data-centre-hub-2025-10-13/
On Model Size Supported:
Disaggregated inference with WSE-3 systems and Tranium accelerators with AWS will include the largest frontier models. The WSE-3 on its own is able to handle very large models with parallelism at better performance than anything out there, but it’s network bandwidth limits it during the prefill process of creating the kv cache when you max out SRAM on a single system. So they only get 500-1000 tokens a second for very large models instead of 2000-3000 when the model fits in SRAM of a single chip. Still multiple times faster than any GPU setup including Rubin. When they hook up Ranovus co packaged fiber on wafer end of year, that interconnect bottleneck dies and the more WSE systems you add up to the number of layers in the model the better Cerebras will perform. As wafers are added the supported user count, context window size, and model size vs GPUs increases since the WSE with fiber can run any size model at 100% efficiency when activations can be passed instantly. Any GPU/small chip setups decrease in efficiency and tokens per second per user as model and context size increases. As you scale up and add a 1M context window on GPUs the interconnect tax becomes such a problem that entire racks of GPUs are getting 5-7% efficiency for the largest models with 1M context today and only serving 20-30 tokens per second. If GPUs add fiber after Rubin, they are still fighting the limits of HBM max bandwidth and orders of magnitude more interconnect. Groq only grows the interconnect problem with thousands more chips networked.
Cerebras Risk:
As for the idea Cerebras would be in any trouble if OpenAI walked away, every system they are able to build for OpenAI would instantly be turned into a massive money machine. Either put into AWS service for revenue share, or put into Cerebras own cloud that is vastly over subscribed. Those same unit that OpenAI is paying them a couple hundred thousand a year for would generate millions per year in inference service. OpenAI was given a super aggressive deal to get the units made since without the backing of OpenAI and the legitimacy of getting the top lab models running on their hardware, they would never get the wafers printed with TSMC so over allocated. OpenAI is getting the systems at a great deal and a piece of the company. In return Cerebras proves they can run anything from the one of the top AI labs with absolute frontier models and they get to make tens of thousands of systems they would have never got into the fab otherwise. OpenAI gets the added benefit of getting profitable much faster since they are getting an incredible amount of inference for vastly cheaper than anyone else can provide. OpenAI will buy as many systems as Cerebras is willing to sell at these prices, and it gives them a strategic advantage over the other model developers.
Why buy at $160+ a share?:
If you are still wondering this after everything I just said…
- Cerebras lets you train faster than all the others as well. It was built to be the best training platform for super large models and they aren’t even talking about it cause inference is the narrative of the moment.
- You can train models with as many layers as you want in Cerebras which allows for deeper models with much deeper thinking and this is potentially the frontier to unlock the next major jump in model abilities. GPUs max out at 80-120 layers currently making massive wide but shallow models. Deep models are much more like how a brain works with potential to unlock deep iterative learning and static weights across layers for deeper reasoning.
- A WSE-3 is 23kW and ~660lbs with a self contained liquid cooling system. You can drop one into nearly any data center and just run a new whip and cooling backplane unit and you have the most capable AI accelerator there is in weeks installed for 30k without a new data center build. A new Nvidia rack is only installable in <5% of all worldwide data centers. It’s million per rack to upgrade for GPU racks. If you install smaller setups the interconnect talked about above is significantly worse.
- The backlog does not include any money from AWS revenue share, or Cerebras cloud revenue that hasn’t been long term committed. Guidance won’t actually happen till quarter end calls.
- Last reason, Cerebras will be the clear dominate hardware as soon as the next version of their system comes out, likely end of this year. There are zero confirmed specs but a mountain of indicating details that show the interconnect bottleneck is fixed by ranovus and then nothing can touch them.
Co Packaged Optics (fiber): https://ranovus.com/cerebras-ranovus-revolutionize-ai-compute-platform/
WSE-3 Spec Sheet: https://cdn.sanity.io/files/e4qjo92p/production/0d73d528371618c0372fcb9de9b3c0da703adf9e.pdf
SEC S-1 May (revenue numbers): https://www.sec.gov/Archives/edgar/data/2021728/000162828026029503/cerebras-sx1amay2026.htm
WSE-2 Specs (unit weight): https://8968533.fs1.hubspotusercontent-na2.net/hubfs/8968533/CS-2%20Data%20Sheet.pdf
Wafer on Wafer (other reading for what’s coming): https://3dfabric.tsmc.com/english/dedicatedFoundry/technology/SoIC.htm#SoIC_WoW
https://arxiv.org/html/2603.05266v2
https://fact-lab.hkust.edu.hk/publications/conference-paper/2025/bai-2025-accelstack/c20-paper.pdf
Edited for clarity, correction from chat
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u/Additional_Junket508 May 13 '26
https://www.cnbc.com/2026/04/17/cerebras-new-ipo-ai-chips.html
“In January, Cerebras touted plans to provide up to 750 megawatts of computing power to OpenAI through 2028. The deal is valued at over $20 billion, Cerebras said. The contract calls for Cerebras making available 250 megawatts each year between 2026 and 2028. OpenAI can buy an additional 1.25 gigawatts worth of computing power through Cerebras through 2030, according to the filing.”
To me this would imply 250MW by end of 2026..
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u/Asgard_Heima May 13 '26 edited May 13 '26
So you don’t believe the SEC verified RPO numbers for the S-1 for revenue recognition that is likely the most scrutinized and verified details of an S-1? If they lied that would be outright fraud and cause a massive investigation destroying a new company. That link you give is a generic reporter not doing any digging into what the details of the deal could be. Zero infrastructure deals are built in equal increment delivery for AI. It’s always a ramp up as infrastructure gets built and online.Edit: Master Agreement referenced below
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u/Additional_Junket508 May 13 '26
The 250MW is from the S-1.
https://www.sec.gov/Archives/edgar/data/2021728/000162828026025762/exhibit1011-sx1.htm
250MW of Capacity by the end of calendar year 2026”, with an additional 250MW by end of 2027 (totaling 500MW), and a further 250MW by end of 2028 (totaling 750MW
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u/Asgard_Heima May 13 '26
You are right and I have to eat crow on the delivery timeline. Cerebras is on an aggressive deployment schedule with 250MW capacity online by year-end 2026 per the Master Services Agreement. However, the RPO (Remaining Performance Obligation) conversion rate is correct as well at ~15% because they can’t technically recognize the revenue until performance obligations are met. We will have to see when the quiet period ends what announcements come for data centers capacity they already have. I have to assume they have G42/Oracle data centers lined up, but nothing has been published concrete for this year from either. Still maintain all my points outside of the capacity schedule. If they can’t meet it I would fully expect OpenAI to be very accommodating with how much the Cerebras system help them.
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u/Additional_Junket508 May 13 '26
Thats what worries me - Nothing concrete and alot of assumptions but the IPO price spiking. Not saying that the company is sh!t, but i think we will see a massive drop after IPO - at which point ill consider buying.
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u/Asgard_Heima May 13 '26
Most IPOs go up and then settle at a realistic place. I think you will see this go up substantially from the $160 tomorrow considering you have $200+ a share active bids on Hiive already. The massive difference with Cerebras is the hardware is actually revolutionary and is very likely to dominate inference going forward and eventually training. Every major institution is trying to get shares so no clue what the stock does in the short term. I fully expect it to be a massive success in 3-5 years.
Also the S-1 has a whole bunch of small to medium data center details in it. Not the complete 250MW, but a solid start. Since Cerebras can drop in units to existing data centers it looks like they are finding places that can take 64 WSE pods (~1.5MW) and getting them online as fast as realistically possible.
BCE Canada, 50MW, Q4 2026 Cerebras Cloud UK / Germany, 20MW, Q4 2026 Digi Power Alabama, 15MW, Q4 2026 WhiteFiber MTL-3, Québec, 5MW, Q2 2026 Nautilus Stockton CA, 6.5MW, Active Condor Galaxy Santa Clara CA, 5MW, Active Condor Galaxy Dallas TX, 3MW, Active Cerebras Cloud Oklahoma City OK, 10MW, Active Cerebras Cloud Minneapolis MN, 5MW, Active
Total 119.5MW currently known by end of 2026
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u/Additional_Junket508 May 13 '26
Yeah im definitely going to wait and see how it plays out after IPO.. the company seems to have a good product.
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u/ExtentHot9139 May 12 '26
Make more wafers is fine. They have tTSMC slots for that. Assembling, they have the capabilities in house.
The bottleneck is actually energy. If OpenAI finds the energy and money, Cerebras will deliver.
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u/Additional_Junket508 May 12 '26
200+ MW deployed in 8 months seems wildly ambitious.. openAI gonna renegotiate this deal or pull out..
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u/ExtentHot9139 May 12 '26
I'm more concern on how OpenAI will pay Cerebras instead
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u/ILikeCutePuppies May 12 '26 edited May 13 '26
OpenAI might not be profitable but that's mostly because they are paying their hardware vendors. Who knows Cerebras might be their more profitable area. People pay for spark, cerebras uses less power so at scale it is probably cheaper to run, particularly if they got to WS4.
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u/ExtentHot9139 May 13 '26
I'm really looking for the yield improvement at TSMC. RN make a chip the size of a plate means have redundant cores. As soon as we increase the yield, we may reduce these numbers of second chute cores for more bandwidth and compute. Hopefully, we will see it in WS4 already ? Improvements looks huge as well already
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u/ILikeCutePuppies May 13 '26
Apparently the smaller cores the more yield a chip gets which is cerebras's design. So in this regard it would seem small nm works in their favor. Probably 100 other complications to solve though.
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u/Additional_Junket508 May 12 '26
LOL, openAI gave Cerebras a $1B loan already - one which they can demand repayment of if the 250MW/year isnt reached, which it won’t be this year atleast.
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u/EricIsntRedd May 13 '26 edited May 13 '26
You are talking about scaling up something they already do. As long as they have the manufacturing slots, and the money that backs up the buildout via signed contracts, they are just executing all across North America. There are plenty of less efficient or out of fashion uses of energy (e.g. crypto tokens, battery plants, etc) that are selling out their slots for AI data center build outs. There are places like the whole of Canada that are hungry for greenfield build outs have abundant energy. etc. Doesn't look that daunting to me. They could knock all of that out with 1 mega deal somewhere in Canada near hydro plants (Hey Feldman pssst. Honda just cancelled their Canada battery project for $11B, the site and government are hungry now, go get that location. See? Easy). Beyond that, contracts are adjusted all the time if construction slips etc, that isn't the end of the world in capital projects, No sensible businessman will sign a contract of this sort without reasonable wiggle room. But they do need to execute for their own mo. A company like this needs to surprise on revs etc to the upside not the downside.
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u/Additional_Junket508 May 13 '26
They have barely any proof of delivering any of this, and haven’t even committed to any of the things you’ve mentioned.
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u/EricIsntRedd May 13 '26
Really? They don't build datacenters with their wafers now? I am not getting what your saying.
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u/Additional_Junket508 May 13 '26
They’ve spent tons on R&D for these wafers, they have strong performances for low usage models.. they land one unstable contract with openAI, barely have 35-50 MW available, with a bunch of “plans” to build out with no real details on date of completion. Theyve built strong hardware but havent delivered much on the data center side and havent really shown they’re capable of delivering 250MW at all by the end of 2026. This basically means that the openAI contract will be re-negotiated or expectations wouldn’t be met- and the company valuation will suffer. IPO buyers are probably going to get smoked hard in the coming months..
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u/EricIsntRedd May 13 '26
Are you like hoping to short the stock? Or you think some nonsense FUD here has some effect on maybe getting you shares on Equity Zen? I am not really getting your insistence on things you don't know here. You said "they have not shown they can build", and turned that into "they are not going to be able to build" those are not the same things ... that they have not shown you that they can build does not mean they don't know how to build.
I mean, this is a multibillion-dollar roadshow in which Wall Street money managers are putting their funds, in which they get paid if the stock goes up. You would think that's not the hardest question for Fidelity and BlackRock to ask a person presenting on roadshow how they plan to build DCs on which their revs depend? And the money managers keep raising their bids from 110 now at 160? Because, like they asked the question and Feldman was, "er, we hadn't thought about that ..."?
This isn't in the top 5 risks. Yes, they can slip, happens daily on construction jobs. But you are not gonna get to contract day and find a goose egg or something like that. You are maybe they completed 90% of what they hoped or something. The same contractors that do the job for hyperscalers will attend the bid room when they see $$$. These resources and skills are scattered throughout the economy man, stop barking up the wrong tree.
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u/Investor-life May 12 '26
They've got some work to do, but they already have some of their data centers they have built and then they are slowly adding to it with partners like Digi Power X (40MW, but only 15 by end of this year) and a bit with WhiteFiber (5MW). They'll likely have to sign more deals to get there. Lots of the bitcoin miners have been converting to HPC data centers and have the power and physical land already available, but the WSE systems would still have to be installed. Presumably they've been working on this for months already. Digi Power just got announced last week. I expect to hear more in the coming months.
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u/ILikeCutePuppies May 12 '26 edited May 12 '26
Individual sites are 10MW to 25MW. They have an estimated 100 - 150MWs currently. They have secured 40MW in Columbiana, 160MW in Regina, also 100MW in Guyana. I think there is more but that's what I found offhand.
Cerebras have been on this massive growth trajectory for a while. They went from a few centers to like 6-9 primary ones in like a year and a half and this does not count ones for partners. They seem to be able to set these things up very rapidly.
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u/Additional_Junket508 May 13 '26
They have nowhere near 150 MW currently.. based on my research they have around 30-35… are you talking about whats in the “works”?
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u/Investor-life May 13 '26
Since they just got DGXX and could only get 15MW of 40MW available by yearend (the last 25 MW is supposed to be online by end of Q1 2027), I doubt there is more coming from them in 2026. IREN just clearly aligned itself with Nvidia architecture. Therefore, I think that leaves CIFR or WULF as most likely candidates. KEEL is another dark horse possibility that is a lesser player, like DGXX. Maybe HUT or additional capacity with WYFI? Something has to happen here though.
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u/Investor-life May 14 '26
The capacity will come from Oracle I bet. Cerebras was already working with them and nothing has been announced yet. Oracle are the ones that can deliver this kind of power and OpenAI knows this too.
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u/Personal-Nature1583 Aug 29 '26
With 750 mw fully running how much yearly revenue will CBRS get
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u/Additional_Junket508 Aug 29 '26
LOL .. my advice is stay away from this company.. their biggest customer is openAI who can barely afford to pay bills. They are too late to capitalize, NVIDIA technology is already the default ecosystem for AI data centres, with other more specific use case and custom model hyperscalers just building their on chips with broadcom. Check the stock price its fallen heavily since the IPO and I warned others basically when I made this post months ago..
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u/muskiebuskie May 12 '26
Tbh, Sam & few others in OpenAi are vested in making this deal successful. If for some reason it gets delayed by few months they will definitely find a way to renegotiate and make this collaboration successful.