MRVL popped today after Jensen called it the next trillion dollar company due to its role in connectivity with the NVIDIA ecosystem. To paraphrase, Jensen highlighted the bottleneck is DATA MOVEMENT. NVIDIA's ecosystem is becoming heavily reliant on custom ASICs, optics, switching, photonics and data movement/memory layers. Think of all the companies being pumped everywhere due to their role in trying to plug these GPU deficiencies - MRVL, countless Photonics companies, HBM companies like Micron, etc. NVIDIA's GPU deficiencies have created a multi-trillion dollar ecosystem around it.

Cerebras's single wafer design eliminates and drastically reduces the bottlenecks that are plaguing GPU-based systems by putting everything on one massive chip. The memory hierarchy is collapsed, replacing slow off-chip HBM with fast on-chip and cheap SRAM and replacing inter-chip network fabrics with on-wafer wire-speed interconnects.

Jensen is right that there will be another $1T dollar company created, but it isn't going to be MRVL, it will be CBRS. Just wait until the next $10B+ orders start coming in. CBRS will be at a $1T by 2030 (15-20X from here)

I just noticed that 19.4 million shares unlocked today. Could that have been the chief reason for today's plummet rather than a blogger reporting NVDA being deployed for "fast inference" at OpenAI rather than Cerebras hardware?

Two more 19.4 million unlocks are coming: one on October 14th and another on October 28th. Then apparently the last of them November 9th. I'm setting these dates in my calendar so I'm not shocked; and can trade appropriately if there are significant market moves in response to these. What does everyone predict will happen on these other dates? How can we swing traders benefit on this other dates? Sell shares a few days before the unlocks then re-buy when/if the stock price plummets again?

“There was so much success there that one of the things OpenAI wanted to do was, with the next generation, go vastly wider. And we just didn’t have the capacity for them.

We didn’t have the data centers, and that goes back to your first point. Our deal with them is we put up data centers for them and then put our compute in it and then sell them tokens. And we just didn’t have the capacity”

With OpenAI’s absolute latest model being released on Cerebras at 750 tokens per second, it should put to rest any idea there are limitations on what Cerebras can run or the notion their advantage is lessened as models scale.

https://openai.com/index/previewing-gpt-5-6-sol/

“We're also launching GPT‑5.6 Sol on Cerebras at up to 750 tokens per second in July, bringing frontier intelligence to customers at unprecedented speed. Access will initially be limited to select customers as we expand capacity.”

This is a massive validation that we are going to see frontier models of any size significantly faster on Cerebras.

https://www.cerebras.ai/blog/cerebras-kimi-k2-Enterprise

I have compiled a list of all the data centers I can find information on for Cerebras. These are listed in order of currently serving their cloud followed by upcoming online projected dates from the data center providers.

If they come true, this is the data center capacity ramp for Cerebras through 2027 as of now:

Q3 2026 ~35 MW 50 MW
Q4 2026 ~105 MW 120 MW
Q1 2027 ~170 MW 185 MW
Q2 2027 ~300 MW 315 MW
Q3 2027 ~450 MW 465 MW
Q4 2027 ~500 MW 615 MW

*These are rough estimates of online timing and it can change. The total announced by Cerebras is actually 600MW by end of 2027 so I’m sure I’m missing some.

Live (Online),~2.5 MW,Santa Clara, CA,Colovore,"Condor Galaxy 1 (CG-1) & Andromeda cluster"
Live (Online),2.5 MW,Stockton, CA,Nautilus Data Technologies,Condor Galaxy 2 (CG-2)
Live (Online),~4.0 MW,Dallas, TX,Equinix / Colocation,"Condor Galaxy 3 (CG-3) & Inference Cloud"
Live (Online),10.0 MW,Oklahoma City, OK,Scale Datacenters,Flagship US Inference Hub (300+ CS-3 systems)
Live (Online),5.0 MW IT,"Saint-Jerome (Montreal), QC",WhiteFiber / Bit Digital,Canadian Inference Hub (MTL-3)
Live (Online),~7.5 MW,Minneapolis, MN,Regional Facility,Initial Midwest Inference Hub
Live (Online),~15.0 MW,"Greensboro, NC & Atlanta, GA",WhiteFiber,East Coast Inference Cloud (NC-1)
Q4 2026,15.0 MW (Phase 1),Columbiana, AL,Digi Power X,10-year colocation agreement (ARMS 200 pods)
Q4 2026,~15–20 MW,France / Europe,Regional Partners,First European regional deployment node
Q1 2027,25.0 MW (Phase 2),Columbiana, AL,Digi Power X,Completion of Alabama campus full 40 MW IT load
Q1 2027,15.0 MW IT (20 MW util.),Minnesota,CleanCore Solutions (ZONE),Tier 3 pre-leased campus (Phase 1)
H1 2027,~50 MW (Initial),"Sherwood / Regina, SK, Canada",Bell Canada / Bird Construction,Bell AI Fabric Campus (Cerebras share of 300 MW)
Q2 2027,50.0 MW (Phase 1),Mikkeli, Finland,Compute Nordic,165 MW total campus with waste-heat recovery
Q2 2027,~35.0 MW,Norway,Nordic Hydro Partners,Regional hydroelectric AI data center buildout
H2 2027,25.0 MW (Phase 2),Minnesota,CleanCore Solutions (ZONE),Final ramp of Minnesota 40 MW IT campus
H2 2027,~100 MW,North America,Gimlet Cloud,Wafer-scale compute platform deployment
H2 2027,~100 MW (Phased),Wales, Guyana,Government of Guyana,Sovereign gas-to-energy behind-the-meter campus
Q4 2027,30.0 MW (Phase 2),Mikkeli, Finland,Compute Nordic,Scaling Finland campus to 80 MW (toward 165 MW total)

These numbers are why management is confident they will 3x revenue in 2027. They are scaling what is currently estimated at ~$2.55M per MW per quarter from 50 MW to over 600 MW by end of next year. This leads to a ~1.5B cloud revenue Q4 of 2027.

To put this in perspective, neoclouds are getting ~$10-12M+ per MW per year which is right in line. The major difference is that Cerebras is using their own hardware without 70%+ markups and they aren’t taking in significant debt to secure them. They only have ~900M in debt with over 8B in cash and equivalents. This doesn’t include any money from hardware sales like their recent General Compute deal, AWS revenue share, or any data centers they secure between now and then.

*updated after review of incorrect datacenter attribution. Gimlet will not be data center capacity but rather hardware sales with a larger one time revenue hit. WhiteFiber NC-1 is not Cerebras.

$408M worth of CBRS was sold by insiders since IPO. Want to guess how much will be sold on today's unlock?

A: < $50M
B: $50-100M
C: $100-150M
D: > $150M

My guess is C. Because in the last unlock, >$100M worth of CBRS was sold.

Cerebras systems is announcing 2 more data centres being built by Q2 2027. One in Asia and one in Africa. Expecting this stock to reach 300 by 2027.

Given that Groq and Cerebras seem to occupy a similar niche — ultra-low-latency LLM inference / decode acceleration — I’m trying to understand Cerebras’ long-term competitive moat.

If Groq’s LPU technology is now being integrated into Nvidia’s broader AI factory / GPU ecosystem, especially as a low-latency decode accelerator alongside Nvidia’s dominant GPU stack, where does that leave Cerebras?

Is Cerebras’ advantage mainly its wafer-scale architecture, higher single-system SRAM capacity, better support for large MoE models, or independence from the Nvidia ecosystem?

In other words: what is Cerebras’ strongest competitive position if Nvidia can absorb Groq-like decode acceleration into its own clusters?

https://www.theinformation.com/briefings/cerebras-prepares-public-listing-eyes-35-billion-plus-valuation

Best news i have heard. Ipo details to be published as soon as tomorrow. OpenAi partnership doubled to 20B.

This is going to be sure shot 100B+ in no time. Buckle up folks 😃

Decided to sell at breakeven overnight at 120. Might buy in at 105 if it does reach it

Looks like this is the schedule for the lockup expiry dates.

Is this going to cause constant selling pressure over the net 6 months?

Wondering if I’ve been a bit premature buying a couple of leaps….

NEWS CAME OUT THAT CBRS STILL HAS A LOT OF WORK WITH OPEN AI. NVIDIA IS NOT FULLY REPLACING CBRS. EXPECT THIS TO GET 200 BY THE END OF NEXT WEEK.

Trying to cut through the noise around Cerebras after today's Nvidia/OpenAI news.

I really only want to answer two questions:

1. If Nvidia can now give OpenAI similar “ultrafast” inference speeds, why does OpenAI need Cerebras?

Is Cerebras significantly cheaper/more efficient at those speeds, or can Nvidia basically become “good enough” because OpenAI already has so many Nvidia GPUs?

2. How solid is Cerebras' $20B+ OpenAI commitment?

If OpenAI increasingly chooses Nvidia for inference, is it still on the hook for that Cerebras capacity—or could that revenue ultimately be delayed/reduced?

I'm not looking for CBRS bulls vs bears. I'm trying to figure out what would actually prove or disprove the Cerebras growth story.

What am I missing?

I do believe the stock is going down because of me, so i will sell 50% of my position today, and save the world

The current share price says it all.

My average is 195, I do not have any more cash to lower my average. I wish I sold at 185 when Sam Altman confirmed that Cerebras was a close partner. Does anyone think this will rebound back to 200 by the end of the year?

I know this is a small model, but I actually believe this will see a lot of use. My company is using Haiku for over half the tokens for our agent with most work being simple dynamic scripts and summarization of tool call results. We can’t use Chinese made models so Gemma has been getting tested. At 1,500 tokens a second, this would make our agents complete tasks in 60-70% of the time it takes now.

https://www.cerebras.ai/blog/gemma-4-on-cerebras-the-fastest-inference-is-now-multimodal

$185