That cluster is literally orders of magnitude smaller than the compute pools used by Anthropic or OpenAI.
replyFor training or for inference?
replyThey don't publish numbers, but Anthropic has a single DC with 200k+ GPUs for inference, GPT-6 Astra is said to have trained on 100k+ GPUs.
replyBoth, especially for training. Astra and Fable were presumably trained on cluster of 100,000k GPUs, or at least a couple of 10Ks.
reply3,800 GPUs is nothing in the frontier side.
I’m pretty impressed that they managed to get that close to the frontier with such a small cluster!
reply> I’m pretty impressed that they managed to get that close to the frontier with such a small cluster
replyChinese companies also managed to put together their models with relatively small clusters.
Perhaps US companies are desperately trying to brute force their way into workable models?
According to Grok thats 7-10 MW. Tiny numbers.
replyTo put that into context, the last wave of capacity SpaceXAI added 400-450 MW.
But how much of that are they using for training versus inference? They're serving quite a large user base.
replyThese cards are like $3k each? That's, what, $12M and you keep the hardware? Honestly doesn't seem too bad.
replyMore like $30k each.
replyOh the server chip is 10x. That makes a lot more sense.
replyThat’s kinda very small and light for modern trillion-param LLMs.
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