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I've been watching a bunch of bycloud on YouTube recently, and although he's done a great job reviewing papers from the big AI labs, I feel like I'm missing something - how have all the labs seemingly made a model that's cheaper, faster AND has better performance? Historically `flash` variants (like codex spark as well) have been faster but perform worse

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That’s how increasing performance works. You make a model 10x faster, then you make it think 2x as much.

Its cost is now 1/10th per token, and 1/5th per task.

Basically they have shitty hardware so they have to do a lot of optimization. Think of it like replacing an O(n) algorithm with O(log n).

Anthropic / Open AI think the best path is the most intelligent models deepseek is more focused on tok/$

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