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Cerebras CS-4

cerebras.ai

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91–100 of 281 posts

Re: Cerebras CS-4

#91

Post by zarzavat »

eitally wrote: post #80
sreekanth850 wrote: post #25

AMD along with cerebras may probably compete with NVIDIA monopoly in near future. Also, NVIDIA will have competition form multiple companies. Just my prediction.

Maybe, but GPU is just one aspect of NVIDIA's dominance. If you are buying Vera Rubin GPUs, you're getting an NVL72 rack, which is only one of several racks that you're probably buying. You'll also need your NVIDIA racks with NVIDIA networking & storage gear, too. At the end of the day, they're "vertically integrated" for your accelerated computing data center (e.g. the "AI Factory"). This doesn't even count the soft…

Is CUDA still a moat? Are we not at the point where frontier models can reimplement software stacks, given you throw enough tokens at the problem.

Re: Cerebras CS-4

#92

Post by [deleted] »

api wrote: post #3
9cb14c1ec0 wrote: post #2

Just a reminder for everyone that we are only several years and 3 or 4 iterations into hardware being optimized for LLMs. We should all expect orders of magnitude improvement in speed and/or cost over the next 5 years. Then we can have fun conversations about "unlimited" "intelligence" and about what the price wars and profit margins of consumer AI products are when your average ChatGPT user costs the company $0.10 p…

This is part of why I think the data center build-out is a bubble. We've barely scratched the surface when it comes to hardware optimization. We'll see exponential improvements in energy efficiency and speed over the next decade. Exponential, not linear. GPUs really aren't that great for AI. They just happen to be the best chips we have in mass production right now for this work load, and it takes time to field new d…

[deleted]

Re: Cerebras CS-4

#93

Post by wmf »

avantnyc wrote: post #83

Cerebras should slowly also move to dgx/ryzen market for a desktop version for masses at affordable price yet providing substantial tokens/second on desktop

Desktop SRAM isn't really viable because it could cost $100K just to load the model.

Re: Cerebras CS-4

#94

Post by wmf »

ethanzhang1024 wrote: post #39

If cerebars is performing well, why didn't its predecessor, server S-3, become the largest API token provider on OpenRouter, surpassing the official model releases?

Cerebras provides high-speed inference at high cost. It's never going to be the cheapest and thus it will probably remain niche.

Re: Cerebras CS-4

#95

Post by drcode »

gpm wrote: post #57
aneryu wrote: post #52

It would be even better if a version available to individual users were released soon.

They do offer API services to individual users... though with a set of models that makes it unlikely that you want to use it. They are promising Qwen 3.8 27B any day now though*. if you have the money as an "individual user" to purchase one of their racks... save your money and retire. * Actually they sent out an email claiming they already have it, but I don't seem to have access, they're promising to release it to…

not only that, but I was so happy with their GLM 4.8 that they got rid of yesterday :(

Re: Cerebras CS-4

#96

Post by johnnyApplePRNG »

ewild wrote: post #40
logicallee wrote: post #37

Earlier quoted context omitted.

(Where did you see that?) This was also interesting: "CS-4 delivers more than 1,000 tokens per second on models exceeding 10 trillion parameters." Was it known that there were 10 trillion parameter models in use? I think the frontier providers keep the size of their models carefully hidden.

It's rumored fable is around that 10T number

Fable is most definitely nowhere near 10T.

The cost to train and infer that would be insane, even by today's standards.

Re: Cerebras CS-4

#97

Post by vatsachak »

zarzavat wrote: post #91
eitally wrote: post #80

Earlier quoted context omitted.

Maybe, but GPU is just one aspect of NVIDIA's dominance. If you are buying Vera Rubin GPUs, you're getting an NVL72 rack, which is only one of several racks that you're probably buying. You'll also need your NVIDIA racks with NVIDIA networking & storage gear, too. At the end of the day, they're "vertically integrated" for your accelerated computing data center (e.g. the "AI Factory"). This doesn't even count the soft…

Is CUDA still a moat? Are we not at the point where frontier models can reimplement software stacks, given you throw enough tokens at the problem.

You just proved that AI cannot currently do that

Re: Cerebras CS-4

#98

Post by moralestapia »

adventured wrote: post #88
moralestapia wrote: post #64

Earlier quoted context omitted.

Hence why taalas was one of the best strategic acquisitions of the year. I'm honestly baffled they were not acquired by somebody else (sorry AMD).

Taalas will be one of the great disaster investments of the early AI era. It'll be a near total write-down. The absolute worst market time to etch a model to a chip is right now (very rapid iteration). There is no scenario where they can keep up. The Taalas approach will be viewed as comically foolish within just a few years. Cerebras will win in terms of approach. It's 1998: hey, I can drastically speed up your web…

It's 2026: let's etch nginx into silicon and get 10,000,000 rps at a cost of 0.1 US/day.

Yes, please!

Re: Cerebras CS-4

#99

Post by dnautics »

aneryu wrote: post #52

It would be even better if a version available to individual users were released soon.

needs an sla that says power will never ever ever go out or else you will have a useless shattered plate of silicon.

Re: Cerebras CS-4

#100

Post by apitman »

drcode wrote: post #95
gpm wrote: post #57

Earlier quoted context omitted.

They do offer API services to individual users... though with a set of models that makes it unlikely that you want to use it. They are promising Qwen 3.8 27B any day now though*. if you have the money as an "individual user" to purchase one of their racks... save your money and retire. * Actually they sent out an email claiming they already have it, but I don't seem to have access, they're promising to release it to…

not only that, but I was so happy with their GLM 4.8 that they got rid of yesterday :(

What do they do with old ones? Their hardware physically can't run other models right?
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