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anthonypasqtoday at 7:15 PM2 repliesview on HN

I'd just like to point out that the largest model Cerebras has ever served is Kimi K2.6 which is 1T parameters, so that either means that theyve had a breakthrough on the hardware engineering side of things, or GPT-5.6 Sol is likely a lot smaller than people think.

If it truly is only ~1-2T parameters, then this kinda kills 2 narratives for me.

1. all the handwringing about open source catching up via Kimi K3 (3T params) is complete nonsense. All that matters imo for determining which labs are leading is intelligence per parameter. Anyone with a enough compute can train a giant model, but being able to squeeze capabilities into smaller models gives you a massive inference and training edge.

2. Inference margins are clearly insane, and this explains why OpenAI was able to lower the price of Luna by 80%. Id guess that thing is probably 120b params based on the TPS they are serving it at.


Replies

Gecko4072today at 7:58 PM

Would be extremely interesting if some of the closed models would be that small. Means maybe in future they could run locally.

manmaltoday at 7:22 PM

Isn’t the fact Fable is more expensive than Sol-Max by multiples already an indication that Sol is way smaller?

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