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426 points benchmarkist | 1 comments | | HN request time: 0s | source
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zackangelo ◴[] No.42179476[source]
This is astonishingly fast. I’m struggling to get over 100 tok/s on my own Llama 3.1 70b implementation on an 8x H100 cluster.

I’m curious how they’re doing it. Obviously the standard bag of tricks (eg, speculative decoding, flash attention) won’t get you close. It seems like at a minimum you’d have to do multi-node inference and maybe some kind of sparse attention mechanism?

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danpalmer ◴[] No.42179501[source]
Cerebras makes CPUs with ~1 million cores, and they're inferring on that not on GPUs. It's an entirely different architecture which means no network involved. It's possible they're doing this significantly from CPU caches rather than HBM as well.

I recommend the TechTechPotato YouTube videos on Cerebras to understand more of their chip design.

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accrual ◴[] No.42179717[source]
I hope we can buy Cerebras cards one day. Imagine buying a ~$500 AI card for your desktop and having easy access to 70B+ models (the price is speculative/made up).
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chessgecko ◴[] No.42179769[source]
One day is doing some heavy heavy lifting here, we’re currently off by ~3-4 orders of magnitude…
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accrual ◴[] No.42179793{4}[source]
Thank you, for the reality check! :)
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1. thomashop ◴[] No.42179931{5}[source]
We have moved 2 orders of magnitude in the last year. Not that unreasonable