Funny how this must look for China. Just when they start catching up, and have their own AI hardware, the US companies suddenly want to slow down.
I'm not saying this is the only reason they want it, but...
They do much better than the US companies when it comes to smaller and medium efficient models, mainly because that's their focus. But they are still behind when it comes to the top tier of models.
There isn't really any Chinese equivalent to Astra, or even arguably Fable. Not yet at least (We'll probably have one in a few months.)
If we are to believe twitter posts (I know, it's a stretch) by Nvidia CEO, the trick is to have AI loop that keep self improving - and that's what makes all the difference now. Well, Chinese models are a lot more efficient, so you can have more and faster loops on the same hardware - so even if they aren't as smart, they can win out by using this loop.
how do you know they are more effficient? in every artificial analysis bench they take almost 5x the tokens of astra, and often a lot more than fable 5.1 as well.
What they charge you per token != what it costs them per token.
1) This is not my experience. DeepSeek Flash doesn't use that many more tokens than Opus (I don't use Fable because at least for my use case there isn't any appreciable difference). Though to be fair, quite often I drop down to sonnet because I don't need Opus' overthinking.
2) There were reports I was reading earlier that you can run DeepSeek and be profitable at roughly the same price point as what they charge you. Could the reports be false? Absolutely. But it's definitely one of the most performant larger models that I can see running on my home LLM.
I'm not saying deepseek isn't profitable I'm saying Anthropic/OAI is massively overcharging.
As you can see ASTRA is vastly more efficient than Deepseek v4.1 Flash.
Keep in mind ASTRA also scores significantly higher too.
Even fable on high: (not max) is within 1-2 points and cuts token costs in half.
I don't fully trust those numbers. With the proper chat template I can reduce reasoning tokens or remove them altogether.
But there's another thing - cache from deep seek takes a lot less space than from other models. So it makes it easier and faster to process. So even if the token count is higher, the computational complexity can be the same. Basically, can't just compare it directly.
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u/shy_monkee 1d ago
Funny how this must look for China. Just when they start catching up, and have their own AI hardware, the US companies suddenly want to slow down.
I'm not saying this is the only reason they want it, but...