Where are the competitive models from Singapore, Japan, Taiwan, Korea, Russia, Canada, India, the UK? From anywhere that isn't China or the US?
There are none. Mistral Small 4 is pareto-competitive in its pricing bracket at $0.15/$0.60, at worst it's second to Gemma 4 26B A4B. The above countries have never had a model that is even close to being so.
This particular Mistral Medium looks to be uncompetitive at that pricing. I'm surprised it's so expensive given its size. Wonder if we'll see other providers offer it for cheaper.
but that doesn't mean Mistral has never produced anything useful.
You mentioned "pareto-competitive", and EXAONE certainly was that. The statement that the "above countries have never had a model that is even close to being so" is simply too broad.
You're talking about EXAONE 4.5 33B? Gemma 4 31B was released 1 week earlier and blows it out of the water. Which point in time/model size are you possibly talking about? The original K-EXAONE in January?
More than anything the availability speaks for itself. If it was indeed pareto competitive, all dozens of model providers would be doing their best to offer it for serverless inference. They don't. There's maybe one that does. Do you think a lot of companies wouldn't prefer a Korean model over a Chinese one? In this case, the market speaks. Go talk to people who run business based on putting billions or trillions of tokens through open weights models. And how much time they put into optimization of model selection to save money and latency. And ask why none of them are using EXAONE models. It's not because we're not aware of their existence. There's also reason to believe they've been benchmaxxing more than Chinese models, btw. Have you done the vibecheck?
I wish they were strong, I hope that in the future, they are. More diversity is better. So far they have not yet been a serious option at any point.
Yet ASML is always cited as a great Europe great achievement, but it's hardly ever mentioned that without American's EUV research and patents, and without Cymer there would be no AMSL as we known of.
In all honesty I believe ASML's success is mostly their own. Still, lamenting "being bought up by foreign countries" is a lame excuse.
Without Google’s funding its not obvious i DeepMind would have went anywhere.
Unless the moved to US for funding while keeping a back office in the UK.
It’s strange to expect anything significant to come out from Europe when VCs there are either very risk averse and/or don’t have enough cash to begin with. It’s not like government or EU funding can replace that since its almost always wasted or missdirected
It’s a company containing such remarkable talent that I’m sure they would not have run into significant issues raising capital on international markets.
It’s not like VCs are only allowed to invest in companies in their own country.
Usually to maximize its funding the company would move its HQ to the US and if they are lucky have an IPO there and eventually become effectively American after a few years (e.g. Unity)
Being near the Pareto frontier of inference cost vs. output quality.
This was released 6 days ago. The dust hasn't settled yet, and Mistral Small 4 was released earlier. Even if Deepseek V4-flash turns out to crush it, there was a period where it was Pareto competitive. None of the countries I named (i.e. no country that isn't China/US/Mistral) have had a Pareto competitive model at any point in time.
Although the Manus decision might change things for AI, Singapore-washing is quite rampant among Chinese companies, so I wouldn't call this place of origin an alternative market.
A few months ago China was being criticized left and right on how somehow it was not able to compete, and once DeepSeek showed up then all the hatred shifted onto how China was actually competing but exploring unfair competitive advantages.
Funny how that works.
Also, aren't the likes of OpenAI burning through over $2 of investment for each $1 of revenue?
Yes, but it would seem that Chinese models are much more efficiently trained than the US ones, (i.e. with fewer resources).
Europe doesn't invest nowhere near as much as the US does into tech, so we need to either figure out how to be at least as, and hopefully more, efficient as the Chinese models are (at least in terms of training) or there's little point in trying.
I suspect this is one of the reasons why Mistral's models are somewhat struggling; i.e. US style training costs, but nowhere near as much cash as OpenAI/Anthopic have.
There are multiple European Google alternatives as well for example, but being 80% as good just doesn't cut it. Chinese models win because they are 95-98% as good as the SotA US ones but at a fraction of the cost.