It's really cool and interesting to see the kind of engineering that goes into Xiaomi (and Deepseeks) inference optimizations. Z.ai has also published some interesting papers although I haven't had a chance to go through them yet.
It does inspire hope that the Chinese labs seem to be so open although the sceptic in me does wonder what their end game is.
Surely, from a purely economic perspective it would be wiser to keep this proprietary and benefit from the increased API traffic?
Their game? Sell me tokens instead of me buying them from an American lab for a higher price.
Publishing open weights gives me more confidence in the model, and ironically makes me less anxious about making sure I can replace the cloud usage with a local alternative. Whereas I’m very nervous right now with relying on 5.6-Sol - what if they triple the price, nerf it, etc.?
What Chinese firms are doing makes perfect sense from the commercial perspective actually because they understand how a classic commoditization spiral works. The reality is that models themselves are general commodities and there's just not enough difference between them. A company can get ahead of others by a few months, but then the rest quickly close the gap. It's a really low margin business because there's no way to differentiate yourself.
Chinese companies know that there's no profit in general purpose models in the long run, and they're treating models as shared infrastructure akin to Linux. They're amortizing the cost of research by keeping models open, and rapidly closing the gap and driving prices towards the marginal cost of inference. The money is going to be in customization niches. Companies will charge to tune models for specific use cases and charge support for that. There's also going to be money at the bottom for hardware vendors making chips and memory. But the middle tier of generic LLMs is seeing involution where there's relentless competition driving profits towards the bottom.
It does inspire hope that the Chinese labs seem to be so open although the sceptic in me does wonder what their end game is.
Surely, from a purely economic perspective it would be wiser to keep this proprietary and benefit from the increased API traffic?
Publishing open weights gives me more confidence in the model, and ironically makes me less anxious about making sure I can replace the cloud usage with a local alternative. Whereas I’m very nervous right now with relying on 5.6-Sol - what if they triple the price, nerf it, etc.?
Chinese companies know that there's no profit in general purpose models in the long run, and they're treating models as shared infrastructure akin to Linux. They're amortizing the cost of research by keeping models open, and rapidly closing the gap and driving prices towards the marginal cost of inference. The money is going to be in customization niches. Companies will charge to tune models for specific use cases and charge support for that. There's also going to be money at the bottom for hardware vendors making chips and memory. But the middle tier of generic LLMs is seeing involution where there's relentless competition driving profits towards the bottom.
At Xiaomi, MiMo is now led by Luo Fuli. She is a former Alibaba & DeepSeek employee: https://newsen.pku.edu.cn/news_events/news/people/15385.html (https://archive.vn/I8Pmu) / https://e.vnexpress.net/news/tech/personalities/who-is-luo-f... (https://archive.vn/sb3B6)
Don't know if it is due to Luo, but it is striking how similar performance & pricing of the models, DeepSeek v4 Pro & MiMo v2.5 Pro, is.
Someone did the math a few months ago and paying API prices was the same as the monthly subscription.
I’ve thrown $50 at it, use UltraSpeed liberally and have yet to exhaust it.
I've used Mimo extensively in the past few months, can't wait to see what v3 will bring.